Canada is a huge and diversified market. Its merchandise imports were approximately C$789 billion in 2025. At the same time, Canada is deliberately diversifying its trade relationships beyond the US and strengthening its economic ties with the Indo-Pacific.

This creates an opportunity for the Philippines.

We should identify products where the Philippines has a genuine advantage and develop long-term relationships with Canadian buyers. These include tuna and seafood, coconut products, bananas, pineapple, mangoes, sugar, processed food, electronics and electrical components, garments, furniture, medical products and selected automotive components.

Canada, in turn, can supply products that are strategically important to the Philippines. The most obvious example is potash and fertilizer. Canada is one of the world’s leading suppliers of potash, while the Philippines is heavily dependent on imported fertilizer.

There is an obvious opportunity to connect these two realities.

From Barter to Strategic Trade

The idea of exchanging Philippine products for Canadian products is not new. But rather than thinking of it as simple one-for-one barter, we should develop a more sophisticated countertrade or commodity-clearing arrangement.

Philippine exporters could supply tuna, coconut products, sugar, bananas and other agricultural products to Canadian buyers. Canadian companies could supply potash, fertilizer, wheat, pulses, lumber and agricultural machinery to Philippine buyers.

The transactions would still be commercial transactions, priced against international benchmarks and properly documented. The difference is that the two governments would create a framework encouraging reciprocal trade and long-term supply commitments.

Physical barter can become complicated because different commodities have different prices, grades, shipping costs and delivery schedules. A better approach is to establish reciprocal commercial commitments over a defined period.

In simple terms: Philippine exports help pay for strategic imports.

Why Fertilizer Should Be at the Center

If we want to improve Philippine agriculture, we have to address productivity. Our farmers cannot become competitive if their production costs remain too high and their yields remain too low.

Fertilizer is one of the critical inputs. Canada’s enormous potash industry provides an opportunity to establish a more predictable and potentially diversified source of fertilizer for Philippine agriculture.

Imagine a long-term arrangement in which Canadian suppliers provide agreed quantities of potash or other fertilizer products to the Philippines while Philippine exporters develop corresponding long-term markets in Canada for agricultural products.

The objective should not be to obtain fertilizer at any price. It should be to obtain it competitively, reliably and in quantities that support measurable improvement in agricultural productivity.

Better fertilizer availability can mean higher yields. Higher yields can mean lower unit production costs. Lower production costs can make Filipino farmers more competitive. Higher productivity can increase farm income. And higher farm income can create demand for businesses and services in rural communities.

Tuna for Timber? It Makes Economic Sense.

The Philippines has a well-established seafood-processing industry and is capable of producing high-value tuna and other seafood products. Canada has a globally significant forest-products industry, while the Philippines has enormous requirements for housing and construction materials.

Why shouldn’t we explore a long-term commercial arrangement in which Philippine seafood exports help support the purchase of Canadian lumber and engineered wood products?

The same principle can apply to Canadian wheat and pulses. The Philippines needs wheat for bread, noodles, biscuits and other food products. Canada is a major producer of wheat and pulses.

The Philippines can supply tropical products that Canada cannot efficiently produce domestically. Canada can supply temperate agricultural products that the Philippines cannot produce competitively.

This is not a zero-sum relationship. It is economic complementarity.

Coconut, Banana, Pineapple and Mango

The Philippines should look beyond raw agricultural commodities. Our objective should be to export more value-added products.

Instead of simply exporting coconuts, we should increasingly export coconut water, coconut milk, coconut cream, coconut oil, desiccated coconut, coconut flour and coconut sugar.

Instead of simply exporting bananas, we can expand banana chips, dried bananas, banana flour, banana puree and other processed products.

The same principle applies to pineapple and mango.

Processing creates jobs. Processing increases the value captured in the Philippines. And processing creates opportunities for rural enterprises.

Where PITC Could Make a Difference

This is where the Philippine International Trading Corporation (PITC) could potentially play an important role.

PITC is a government-owned trading corporation under the Department of Trade and Industry. Its government profile includes exports, trade services and special trading arrangements among its functions, while its charter provides authority relating to international trading activities. The Philippines also has historical experience using PITC in countertrade arrangements.

Rather than creating another government bureaucracy, the government should examine whether PITC’s existing mandate can be strengthened and specifically utilized for this purpose.

If legally and institutionally validated, PITC could be tasked to develop and manage a Philippines–Canada Strategic Trade Mission. Its role could include identifying Canadian buyers and suppliers, matching them with Philippine producers and importers, structuring reciprocal commercial arrangements, monitoring commitments and reporting results.

DA and DTI could establish the agricultural and trade priorities. PITC could develop the transactions. Private companies could actually buy and sell the products. Financial institutions could provide trade finance. Appropriate government agencies could provide oversight and audit.

This would keep the government in its proper role: facilitating and organizing the market, not replacing private business.

Saving Foreign Exchange—But More Importantly, Creating More

The Philippines needs foreign currency to pay for fertilizer, fuel, food, machinery and other essential imports. At the same time, we have exportable products that can generate foreign exchange.

The objective should therefore be to use our export capacity more strategically.

If Philippine tuna, coconut products, fruits, sugar and manufactured goods generate export earnings that help finance the purchase of Canadian fertilizer, wheat, lumber and machinery, we create a productive cycle.

We are not simply spending dollars. We are using trade to obtain the inputs that can help us produce more and eventually import less.

That distinction is important.

The Bigger Objective: A Rural Middle Class

For me, however, the most important reason to pursue this proposal is not the trade statistics. It is the Filipino farmer.

For decades, many rural Filipinos have remained trapped in low-productivity agriculture. They often face high input costs, uncertain markets, inadequate post-harvest facilities, weak logistics and limited access to technology and financing.

We should change that.

A farmer who has access to reliable fertilizer, better technology and a dependable market can become more productive. A productive farmer can earn more. A farmer who earns more can invest.

That investment creates demand for tractors, transport, storage, machinery repair, retail stores, banking, education, housing and other services.

In other words, agricultural productivity creates a rural economy. And a stronger rural economy creates a rural middle class.

A growing rural middle class can provide greater economic independence and opportunity for Filipino families. It can also strengthen communities and create citizens with greater expectations for competent, transparent and accountable government.

Economic development cannot eliminate corruption by itself. But a society with a broader and more economically independent middle class is better positioned to demand good governance.

That is why improving rural livelihoods should be considered not merely an agricultural policy, but a national development strategy.

What Should Government Do?

The government should establish a small inter-agency working group involving DA, DTI, PITC and other relevant agencies to identify the most promising opportunities.

The group should determine:

1. What products can the Philippines competitively export to Canada?
2. Which Canadian products do we strategically need?
3. What are the current Canadian import volumes and prices?
4. Who are the major Canadian buyers?
5. What tariffs and standards apply?
6. What Philippine producers can meet the required volume and quality?
7. What fertilizer and other agricultural inputs could be secured through long-term contracts?
8. What transactions can be launched within the first 12 months?

The first objective should not be a massive government program. It should be five to ten successful commercial transactions that demonstrate that the concept works. Once the model is proven, it can be expanded.

A Practical Five-Year Vision

By 2030, the Philippines could have a much deeper economic relationship with Canada built around agricultural exports, strategic agricultural inputs, food security, manufacturing and electronics, forest products and construction materials, agricultural machinery and technology, and investment and industrial partnerships.

The opportunity could eventually involve billions of Canadian dollars in additional two-way trade, but the numbers should follow actual product-level competitiveness rather than political targets.

The program should be judged by measurable outcomes: increased Philippine exports; lower or more predictable input costs; higher agricultural productivity; higher farmer incomes; more rural jobs; increased food processing; greater private investment; improved supply-chain resilience; and measurable foreign-exchange benefits.

From Trade to Transformation

The Philippines has often treated international trade primarily as an issue of exports and imports. We should think bigger.

Trade can be an instrument for national productivity.

Canada has resources, technology, capital and agricultural products that the Philippines needs. The Philippines has people, agricultural resources, tropical products, manufacturing capabilities and a strategic location that Canada can benefit from.

The two countries can build on these complementary strengths.

The proposal is not about asking Canada for favors. It is not about government replacing private business. And it is not about barter for barter’s sake.

It is about creating a mutually beneficial commercial relationship that uses each country’s strengths to address the other’s needs.

The guiding principle should be simple:

Export what we can produce competitively. Secure what we need to become more productive. Invest the resulting gains in our people.

If done properly, the ultimate result should not simply be more containers moving through Philippine ports.

It should be more productive farms, higher rural incomes, more jobs, stronger communities and a larger Philippine middle class.

That is the real value of expanding trade with Canada.

And that is why the Philippines should seriously pursue a strategic Philippines–Canada trade and countertrade initiative now.

[The author is member of the Agribusiness Committee of the Management Association of the Philippines or �����Թ�.  He is the Chair and President of BNL Management Corporation. Feedback at <map@map.org.ph> and <romeogdavid@gmail.com>].

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Layer 2: Governing Predictive Machine Learning

Objective: ensure that probabilistic outputs remain accurate, stable, and ethically sound over time.

Predictive systems are used to score credit applicants, price insurance contracts, detect financial fraud, forecast demand, and screen job candidates. Unlike BI, they generate probabilities rather than facts and degrade over time as customer behavior and real-world conditions change.

Core controls

• Drift monitoring. Two types of drift require attention. Data drift occurs when the statistical properties of input data change, such as when a new customer segment is added. Concept drift occurs when the relationship between inputs and outcomes shifts, for example, due to changing economic conditions. Both can gradually reduce model effectiveness.
• Explainability (XAI). Techniques, such as SHAP and LIME, help identify which factors drove a particular outcome. For high-impact decisions, such as those in credit, underwriting, and hiring, the organization must be able to justify the outcome to a customer, a regulator, or a court.
• Fairness and bias audits. Test models across population segments before deployment to detect disparate impact, defined as a disproportionately adverse outcome for a protected group, even if unintentional. Ongoing testing is required after deployment.

Typical failures include silent performance decay, in which model accuracy declines without detection; feedback loops that reinforce historical human bias; overfitting; and excessive false positives, which raise operational and customer costs.

Board and Risk/Audit focus: The central issues are algorithmic bias liability, consumer protection compliance, and model risk management. In the Philippines, the BSP’s credit risk management guidelines under Circular No. 855 address credit scoring models and risk-rating systems. Beyond the circular’s specific requirements, BSP supervisory expectations in recent years have pointed banks toward full life cycle model risk management: an inventory of models, independent validation, ongoing monitoring, and clear accountability. To support effective oversight, Boards should require regular management reporting on the complete model inventory, the status of independent validation, and the results of ongoing model monitoring and bias audits. This keeps Directors informed about how risks are managed in practice and enables timely, risk-based oversight. (The BSP has also issued guidance on the ethical and responsible use of AI. Boards should confirm whether it is binding or an expectation.)

Layer 3: Governing Generative AI

Objective: reduce hallucinations, safeguard proprietary intellectual property and personal data, and prevent confidential information from leaving the enterprise.

Generative AI is easy to adopt because any employee with a browser (or by downloading the free AI mobile apps) can enter sensitive information into external tools. The primary governance challenge is preventing data from leaving the organization, not model effectiveness.

Core controls

• Model gateway. A model gateway sits between users or applications and foundation models. It screens prompts and files to ensure that confidential information and customer personally identifiable information (PII) do not reach external models or become part of vendor training data. It also provides centralized logging and access control.
• Guardrails. Real-time guardrails screen inputs and outputs for toxicity, jailbreak attempts, prompt injection attacks, and likely hallucinations. While these controls reduce risk, they do not eliminate it. Generative models may still produce convincing but fabricated content, so critical use cases require human review and validation against verified enterprise sources.

Typical failures include hallucinated or fabricated data, such as fabricated citations and figures; data exfiltration and loss through unauthorized tools; and copyright infringement, either from generated content or from employee-submitted material.

Board and Risk/Audit focus: Boards should align governance with strategy and confirm that AI investments support business objectives. Oversight of AI vendors is critical. Boards must require robust due diligence on any external AI vendor, focusing on three key contract terms: (1) clear data-use restrictions to prevent vendors from retaining or reusing enterprise data, (2) enforceable commitments to zero data retention, and (3) strong indemnification and liability provisions for intellectual property infringement. Boards should also expect management to regularly review vendors’ security practices and audit rights as part of ongoing oversight.

Enterprise risk policies should address “Shadow AI,” defined as employee use of unapproved AI tools, and management should demonstrate its ability to detect and manage such use. The Board should also expect a plan to comply with emerging AI regulations in the Philippines and in other jurisdictions where the organization operates. The 2024 EU AI Act is binding only where the organization operates in or serves the EU; elsewhere, it serves as a reference point.

Layer 4: Governing AI Agents

Objective: enforce boundaries on autonomous decisions and actions.

Agents differ from earlier layers by taking action, as systems that combine models, tools, permissions, and instructions, not just models. They can query systems, execute code, modify records, and send communications, often chaining multiple steps without human intervention. The risk shifts from incorrect answers to incorrect actions executed rapidly across systems.

Core controls

• Agent registry – Records which agents are live, who owns each agent, the authority each agent holds, and which data and systems each agent may access. An agent not in the registry should not be running.
• Human oversight – Scaled to risk, two common models are Human-in-the-Loop (HITL), where a person approves actions before execution, and Human-on-the-Loop (HOTL), where a person supervises and can intervene or stop the agent. Governance should set verification thresholds so that high-risk actions, such as executing transactional code or altering databases, require approval, while lower-risk activities are monitored.
• Observability – Maintain complete logs of what each agent did, why, and with what data, so the enterprise can reconstruct and audit actions.
• Failover and shutdown process – If an agent must be stopped, the supported business process must continue via manual fallback, rollback procedures, or a degraded mode. A “kill switch” is effective only if it has been tested and the process remains operational.

Typical failures include unconstrained agent behavior and processes that fail when agents are unavailable. The latter is often overlooked; organizations that automate processes and lose manual capabilities trade resilience for efficiency.

Board and Risk/Audit focus: Boards should ask about agent observability, guardrails, “kill switches”, and process resilience. Internal audit should verify that these controls exist and have been tested.

Cross-Cutting Priorities for the Board

Several themes cut across all four layers:

Maintain an inventory. Organizations cannot govern what they cannot see. Register reports, models, generative AI use cases, and agents, and assign owners.

Tier controls by materiality. Not every dashboard requires the rigor of a credit model, and not every generative AI use case requires the oversight of an autonomous agent. Classify use cases by potential impact and apply controls proportionally. This aligns with risk-based approaches, such as ISO 31000.

Assign clear accountability. Governance fails when responsibility is diffused. Specify who owns data quality, validates models, approves AI use cases, and has the authority to halt an agent’s operation.

Plan for the entire life cycle. Failures in Layers 2 and 4 often surface after deployment. One-time approval is insufficient; ongoing monitoring, periodic revalidation, and a defined retirement process are essential.

Treat vendors as part of the control environment. Many of the AI capabilities an enterprise uses are delivered by third parties. Contract terms, vendor assurance reports, and exit options serve as governance controls.

Know what binds you. Distinguish three tiers: binding law and regulation (for example, the Data Privacy Act of 2012, SEC reporting rules, and BSP circulars for banks); supervisory expectations and guidance; and voluntary frameworks (for example, ISO 31000 and the NIST AI Risk Management Framework, or AI RMF 1.0). Management should identify which layer each obligation comes from and who owns compliance.

Protect personal data by design. AI governance also requires lawful processing of personal information. Before personal data enters a model, tool, or vendor, management should confirm the lawful basis, purpose limitation, data minimization, and retention in accordance with the 2012 Data Privacy Act and National Privacy Commission guidance. This applies to training data, prompts, and outputs, not just to actual leaks.

Divide oversight without diluting accountability. Board Committees enable deeper review but do not replace the full Board’s accountability. Subject to each company’s charters and Board Committee workloads, the Risk Committee can lead on the AI risk profile, appetite, and scenarios; the Audit Committee on reporting reliability, controls, and independent assurance; and the Corporate Governance Committee on policies, decision rights, ethics, and Director capability. Mandates will likely overlap, so coordination is needed. Some Boards may designate one Director to coordinate AI oversight.

Questions for Directors and Executives to Ask

• Can we trace the figures in our financial and regulatory reports to their source, and who attests to their accuracy?
• Do we have a complete inventory of the models in use, and which ones influence customer or employment decisions?
• How would we know if a model’s performance was silently deteriorating or if it was producing disparate outcomes?
• What happens to confidential data when an employee uses a generative AI tool, and what does our contract with the vendor allow them to do with it?
• How many AI agents are operating today, who owns each one, and what are they authorized to do?
• If we had to turn off an agent tomorrow, would the process it supported continue to run?
• What evidence shows that our controls are working on an ongoing basis, and who has independently tested them?
• What material AI risks remain after controls, and what is management doing about them?
• Are the business benefits we expected from our AI investments materializing?

If management cannot promptly answer these questions, it indicates a governance gap or an unclear owner.

Conclusion

AI governance should not be separated from data governance. As systems become more autonomous, AI governance is an extension of the same discipline. Each layer introduces new risks while retaining previous ones. Effective organizations build data quality, add model reliability and fairness controls, protect data in generative AI, and set clear boundaries for agent autonomy.

Boards do not need to understand the mechanics of neural networks or the state management and orchestration for AI agents. But they must ensure that management can demonstrate accountability, define controls, test them, and show how the organization would respond to failures.

Ultimately, Boards should:

• Demand clear accountability across all layers of data and AI governance.
• Require evidence that strong controls are in place and functioning as intended across all layers.
• Insist that management regularly test response plans for failures or incidents and report the results to the Board.
• Track both sides of the mandate: that AI delivers the expected business value and that residual risks remain within an organization’s risk appetite.

By following this checklist, Directors can proactively safeguard the organization and foster responsible innovation.

Thanks to Anton Bonifacio, Pam Cabudoy, Pete Maniego, and Dan Natindim for their valuable comments.

(The author is Governor and Secretary of the Management Association of the Philippines or �����Թ�.  He is a retired banker and Globe and Ayala executive, and a member of the Analytics and AI Association of the Philippines and the Institute of Corporate Directors. He serves as an Independent Director at GT Capital Holdings, Puregold Price Club and Megawide Construction. Feedback at <map@map.org.ph> and <iamgilgenio@gmail.com>.)

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Most organizations didn’t adopt AI with a single decision. Business Intelligence (BI) dashboards evolved into predictive systems, then generative AI tools, and now autonomous agents acting on the enterprise’s behalf. Each new capability introduces distinct risks and requires tailored controls. Governance designed for one stage will not protect the organization at the next. These layers often coexist and mature unevenly across the business; they are not a strict ladder. Boards should regularly assess which layers are in use, how they connect, and whether governance has kept pace. By staying proactive, Directors help the organization anticipate and manage emerging risks.

Boards govern and challenge; management implements. That role has two sides. On performance, directors ask whether data and AI are advancing strategy, productivity, customer outcomes, and resilience. On conformance, they ask whether risk appetite, accountability, controls, and assurance are in place. Governance demands both performance and conformance.

This article presents a framework for data and AI governance, organized into four layers: BI, Predictive Machine Learning, Generative AI, and AI Agents. For each layer, it outlines objectives, core controls, common failure modes, and key questions for Boards and Risk or Audit Committees.

The Governing Principle: Risk Moves from the Data to the Decision

As systems progress from reporting to predicting, generating, and acting, the primary risk shifts from data accuracy to the soundness and limitations of system decisions. In BI, risks center on data quality and access. For predictive models, reliability and fairness are paramount. Generative AI introduces risks of data loss, privacy breaches, and inaccurate content. For agents, the main concerns are the extent of their autonomy and our ability to monitor and intervene.

The layers are cumulative. An agent using a generative AI model that relies on predictive scores and enterprise data inherits the vulnerabilities of all underlying layers. Governance that focuses only on the newest layer leaves foundational risks unaddressed. Boards should require evidence of strong controls and oversight at every layer. This comprehensive approach enhances organizational resilience and accountability.

Layer 1: Governing BI

Objective: a single source of truth with high accuracy and auditability.

BI is the oldest and most overlooked layer, yet it underpins financial reporting, regulatory submissions, and most management decisions. Errors at this stage are carried forward into all downstream models and agents.

Core controls

• Role-based access so that people see only the data their roles require.
• Data governance as an enterprise program with defined data owners, stewards, and quality standards.
• Data dictionaries and metadata management so that terms, such as “active customer” or “net revenue”, have the same meaning everywhere.
• Master data management to maintain authoritative records for customers, products, suppliers, and counterparties.
• An enterprise data catalog that documents what data exists, where it comes from, and how it moves (data lineage).

Common failures include inaccurate source records and broken extract-transform-load (ETL) data pipelines. Outdated logic is especially problematic because calculations that were once correct may continue to produce inaccurate results after changes to products, policies, or accounting standards.

Board and Risk/Audit focus: Boards should ensure compliance with applicable financial reporting standards (such as IFRS/PFRS) and with the reporting and internal control requirements of the relevant securities regulator, such as the SEC. Data retention mandates, access controls, and the maturity of the data governance program should also be on the agenda. Audit Committees should ask whether the data used to prepare financial and regulatory reports is traceable from source to disclosure.

Layer 2: Governing Predictive Machine Learning

Objective: ensure that probabilistic outputs remain accurate, stable, and ethically sound over time.

Predictive systems are used to score credit applicants, price insurance contracts, detect financial fraud, forecast demand, and screen job candidates. Unlike BI, they generate probabilities rather than facts and degrade over time as customer behavior and real-world conditions change.

Core controls

• Drift monitoring. Two types of drift require attention. Data drift occurs when the statistical properties of input data change, such as when a new customer segment is added. Concept drift occurs when the relationship between inputs and outcomes shifts, for example, due to changing economic conditions. Both can gradually reduce model effectiveness.
• Explainability (XAI). Techniques, such as SHAP and LIME, help identify which factors drove a particular outcome. For high-impact decisions, such as those in credit, underwriting, and hiring, the organization must be able to justify the outcome to a customer, a regulator, or a court.
• Fairness and bias audits. Test models across population segments before deployment to detect disparate impact, defined as a disproportionately adverse outcome for a protected group, even if unintentional. Ongoing testing is required after deployment.

Typical failures include silent performance decay, in which model accuracy declines without detection; feedback loops that reinforce historical human bias; overfitting; and excessive false positives, which raise operational and customer costs.

Board and Risk/Audit focus: The central issues are algorithmic bias liability, consumer protection compliance, and model risk management. In the Philippines, the BSP’s credit risk management guidelines under Circular No. 855 address credit scoring models and risk-rating systems. Beyond the circular’s specific requirements, BSP supervisory expectations in recent years have pointed banks toward full life cycle model risk management: an inventory of models, independent validation, ongoing monitoring, and clear accountability. To support effective oversight, Boards should require regular management reporting on the complete model inventory, the status of independent validation, and the results of ongoing model monitoring and bias audits. This keeps Directors informed about how risks are managed in practice and enables timely, risk-based oversight. (The BSP has also issued guidance on the ethical and responsible use of AI. Boards should confirm whether it is binding or an expectation.)

Layer 3: Governing Generative AI

Objective: reduce hallucinations, safeguard proprietary intellectual property and personal data, and prevent confidential information from leaving the enterprise.

Generative AI is easy to adopt because any employee with a browser (or by downloading the free AI mobile apps) can enter sensitive information into external tools. The primary governance challenge is preventing data from leaving the organization, not model effectiveness.

Core controls

• Model gateway. A model gateway sits between users or applications and foundation models. It screens prompts and files to ensure that confidential information and customer personally identifiable information (PII) do not reach external models or become part of vendor training data. It also provides centralized logging and access control.
• Guardrails. Real-time guardrails screen inputs and outputs for toxicity, jailbreak attempts, prompt injection attacks, and likely hallucinations. While these controls reduce risk, they do not eliminate it. Generative models may still produce convincing but fabricated content, so critical use cases require human review and validation against verified enterprise sources.

Typical failures include hallucinated or fabricated data, such as fabricated citations and figures; data exfiltration and loss through unauthorized tools; and copyright infringement, either from generated content or from employee-submitted material.

Board and Risk/Audit focus: Boards should align governance with strategy and confirm that AI investments support business objectives. Oversight of AI vendors is critical. Boards must require robust due diligence on any external AI vendor, focusing on three key contract terms: (1) clear data-use restrictions to prevent vendors from retaining or reusing enterprise data, (2) enforceable commitments to zero data retention, and (3) strong indemnification and liability provisions for intellectual property infringement. Boards should also expect management to regularly review vendors’ security practices and audit rights as part of ongoing oversight.

Enterprise risk policies should address “Shadow AI,” defined as employee use of unapproved AI tools, and management should demonstrate its ability to detect and manage such use. The Board should also expect a plan to comply with emerging AI regulations in the Philippines and in other jurisdictions where the organization operates. The 2024 EU AI Act is binding only where the organization operates in or serves the EU; elsewhere, it serves as a reference point.

Layer 4: Governing AI Agents

Objective: enforce boundaries on autonomous decisions and actions.

Agents differ from earlier layers by taking action, as systems that combine models, tools, permissions, and instructions, not just models. They can query systems, execute code, modify records, and send communications, often chaining multiple steps without human intervention. The risk shifts from incorrect answers to incorrect actions executed rapidly across systems.

Core controls

• Agent registry – Records which agents are live, who owns each agent, the authority each agent holds, and which data and systems each agent may access. An agent not in the registry should not be running.
• Human oversight – Scaled to risk, two common models are Human-in-the-Loop (HITL), where a person approves actions before execution, and Human-on-the-Loop (HOTL), where a person supervises and can intervene or stop the agent. Governance should set verification thresholds so that high-risk actions, such as executing transactional code or altering databases, require approval, while lower-risk activities are monitored.
• Observability – Maintain complete logs of what each agent did, why, and with what data, so the enterprise can reconstruct and audit actions.
• Failover and shutdown process – If an agent must be stopped, the supported business process must continue via manual fallback, rollback procedures, or a degraded mode. A “kill switch” is effective only if it has been tested and the process remains operational.

Typical failures include unconstrained agent behavior and processes that fail when agents are unavailable. The latter is often overlooked; organizations that automate processes and lose manual capabilities trade resilience for efficiency.

Board and Risk/Audit focus: Boards should ask about agent observability, guardrails, “kill switches”, and process resilience. Internal audit should verify that these controls exist and have been tested.

(The author is Governor and Secretary of the Management Association of the Philippines or �����Թ�.  He is a retired banker and Globe and Ayala executive, and a member of the Analytics and AI Association of the Philippines and the Institute of Corporate Director. He serves as an Independent Director at GT Capital Holdings, Puregold Price Club and Megawide Construction. Feedback at <map@map.org.ph> and <iamgilgenio@gmail.com>).

The post Governing Data and AI: What does it mean for Boards? A Four-Layer Framework for Boards and Executives appeared first on Management Association of the Philippines.

Imagine walking into a room wearing a Rolex Daytona. From across the table, everything looks right: the proportions, the ceramic bezel, the weight of the bracelet. Someone notices it. Someone compliments your taste and quietly revises upward what they assume about your career or success.

But one person in the room knows with certainty that it is not a Rolex: you.

That private discomfort resembles the anxiety surrounding irresponsible use of generative AI. The presentation is polished. The report sounds intelligent. The strategy deck contains the right frameworks. Your colleagues are impressed. Yet somewhere inside, you know you could not have produced it yourself, and you may not fully understand what you have presented.

As AI improves, that gap between appearance and substance will become harder to see and more important to confront.

When output stops proving competence

Modern counterfeit watches can be convincing because they reproduce many of the signals visible to an outside observer. The philosophical problem is not simply that an imitation exists. It is that the distance between the genuine article and its appearance has become small enough to create information asymmetry.

AI is creating a similar problem in knowledge work. The spreadsheet works. The essay reads beautifully. The code runs. The proposal uses the language of an experienced consultant. Nobody necessarily knows how much of the intellectual machinery came from an AI system. Perhaps nobody cares until the questions begin.

Why did you choose this model? What assumption drives the forecast? What evidence contradicts the thesis? What happens when the client’s constraint changes? Eventually, someone opens the caseback.

We have long treated a finished artifact as evidence of the process behind it. A well-reasoned article implied that someone had read, discarded weak arguments and struggled toward a conclusion. A financial model suggested that its author understood the assumptions underneath it. Working software implied some knowledge of programming.

Generative AI weakens that inference. The output may still be excellent, but output alone no longer proves competence. We can now acquire many outward symbols of intellectual accomplishment without building the internal models that once produced them. The applause can remain real even when the capability is borrowed.

AI can build real capability

An easy anti-AI argument fails here because AI can create genuine capability. In a randomized experiment published in Science, Shakked Noy and Whitney Zhang found that professionals using ChatGPT completed certain writing tasks 40 percent faster while their output quality rose by 18 percent. A Harvard Business School field experiment with Boston Consulting Group found that consultants using GPT-4 finished appropriate tasks about 25 percent faster and produced markedly better work.

The qualification matters: appropriate tasks. The Harvard researchers described a jagged technological frontier. AI performed extraordinarily well in some areas and proved unreliable just beyond them. Competence therefore includes knowing when the machine has crossed that frontier.

Watchmaking offers a useful comparison. A modern Rolex is not produced through romantic, preindustrial craftsmanship. Skilled watchmakers work alongside automation, advanced metallurgy, proprietary machinery, laboratories and rigorous testing. Technology did not eliminate the craft; it became part of the craft.

The relevant question is not whether a machine helped. It is what the machine allowed the person to become capable of doing.

Two people might ask AI why the Daytona matters. One copies ten reasons into a social media post. The other keeps asking: Why does a column-wheel chronograph matter? What are the trade-offs between finishing, robustness and serviceability? Why can provenance make one reference more valuable than a technically superior watch? Then that person reads independent sources, challenges the answers and develops an informed view.

Both used AI. Only one outsourced curiosity. The other accelerated it. AI becomes corrosive when it ends inquiry and powerful when it generates the next question.

Protect the friction that teaches

A 2025 MIT Media Lab preprint offers an early warning. In a small study of essay writing, participants using a large language model showed weaker brain connectivity than participants who wrote without tools. They also recalled less of their own work and reported less ownership of it. The paper has attracted methodological criticism and should not be treated as a final verdict, but it asks the right question: What happens when producing an answer repeatedly replaces constructing one?

The answer is not to preserve inefficient work for its own sake. Accountants need not abandon spreadsheets. Architects need not reject computer-aided design. Writers need not surrender spellcheck. AI should remove transcription, formatting, routine correspondence, first-pass summaries and other cognitive drudgery.

The harder task is distinguishing wasteful friction from formative friction. Reading 30 papers to find three useful insights sounds inefficient, yet the seventeenth paper may give a researcher an intuitive command of the literature that no summary can supply. Writing a difficult first draft may reveal that an argument is not yet understood. Debugging software by hand can build the mental models that later help an engineer recognize bad generated code.

Some inefficiencies are apprenticeships in disguise. We should automate the friction that consumes human capacity while protecting the friction that creates human capability.

Open the caseback

AI also changes where intellectual advantage lives. When almost anyone can generate a plausible answer, the scarce skill becomes judgment: knowing what to ask, which assumption is missing, what would falsify a claim and when the machine is confidently wrong.

For leaders, the ethical boundary is not whether someone used assistance. Companies employ researchers. Writers work with editors. Executives rely on teams. The boundary is whether we create a false impression of capability where that capability materially matters.

Using AI to format a proposal compromises little. Selling a cybersecurity architecture to a bank without understanding its threat model compromises a great deal. Improving the grammar of an academic paper is different from outsourcing the intellectual work that the degree is meant to certify.

A practical discipline follows. Use AI to remove drudgery, but retain responsibility. Interrogate any claim important enough to repeat. Never outsource the final judgment. Occasionally work without the tool, not as punishment but as calibration. Can you still explain the concept, defend the decision and recognize when the answer is wrong?

Rolex famously linked its Oyster watch with swimmer Mercedes Gleitze’s 1927 English Channel feat. The story worked because the object pointed back to an achievement. The watch was a signal, but there was something underneath the signal: engineering, testing and human endurance.

Our use of AI should meet the same test. Let the machine make us faster, expose us to unfamiliar fields, challenge a thesis and clear away boilerplate. Then open the caseback. Do I understand this? Could I defend it? Did the tool sharpen my judgment or merely improve its appearance?

In an age when almost anyone can produce an answer, we may learn to value something deeper: how carefully a person thinks, how intelligently they question and whether, after the machines have done their work, there is still a capable human being underneath.

Even if nobody else opens the caseback, you still know what you are wearing.

[The author is Member of the �����Թ� NextGen Committee, Managing Partner and CEO of Springboard Philippines, a professor at De La Salle University, and author of Careless Machines: 24 Rules to Keep Your Judgment in the Age of AI. Feedback at <map@map.org.ph> and <jake@springboardph.com>].

The post The Superclone Rolex Theory of AI appeared first on Management Association of the Philippines.

The discussions centered on infrastructure, trade facilitation, digitalization, and regional economic integration. These are important priorities that I fully support.

However, I noticed something missing. No one had raised the issue of corruption.

When I finally brought it up, the room erupted in applause. That reaction was revealing. It suggested that many business leaders recognize the problem, yet we remain reluctant to discuss it openly.

We can build more roads, ports, airports, and digital platforms. We can simplify trade procedures and attract billions in investments. But if corruption, unethical practices, and weak governance remain embedded in our systems, how much of that investment will translate into sustainable economic progress?

Investments follow confidence. Confidence comes from integrity, strong institutions, and capable supply chains.

This is why ethics and supply chain leadership must become central to our national and regional competitiveness agenda.

Supply Chains Determine Competitiveness

Supply chain management (SCM) is often misunderstood as simply purchasing goods, managing warehouses, or transporting products.

In reality, supply chains connect the entire business ecosystem, from planning demand and sourcing materials to managing suppliers, manufacturing, distribution, and delivering products and services to customers.

They determine how efficiently companies operate, control costs, respond to disruptions, and serve their markets. A company may have excellent products, strong financial resources, and outstanding marketing. But without a capable supply chain, it will struggle to compete.

The same applies to countries. Nations compete not only through natural resources, labor costs, infrastructure, and investment incentives, but also through the reliability, transparency, efficiency, and resilience of their supply chains.

Global investors need dependable ecosystems that allow them to source materials, manufacture products, move goods across borders, and serve customers with confidence.

With geopolitical tensions, economic uncertainty, and accelerating technological changes, supply chain leadership has become a boardroom priority. Companies and countries will increasingly compete through their supply chains.

Making the Philippines the Supply Chain Services Capital of the World

For nearly 25 years, our advocacy through the Procurement and Supply Institute of Asia (PASIA) has focused on developing professionals, strengthening organizational capabilities, and advancing best practices in SCM, procurement, and logistics.

Through PASIA Institute and our business solutions arm, PASIA Shared Services, we have supported more than 500 companies in improving their capabilities and operations. Today, we have established a leading regional presence in supply chain, procurement, and logistics capability development and services.

Our vision, however, goes beyond supporting individual businesses. We believe the Philippines can become the Supply Chain Services Capital of the World—not simply by becoming a manufacturing or logistics hub, but by becoming a global center for supply chain expertise, services, and solutions.

SCM is a specialized, knowledge-based profession. It requires expertise in planning, procurement, strategic sourcing, supplier management, logistics, technology, and business transformation.

The Philippines has the people, professional talent, and service capabilities to compete globally in this field. By combining our people, proven processes, and technological capabilities with artificial intelligence, we can offer integrated supply chain services and solutions to businesses worldwide.

This includes large multinational corporations as well as small and medium enterprises (SMEs), which often lack the resources to establish sophisticated supply chain operations independently.

Through AI-powered shared services, SMEs can gain access to professional expertise, advanced technology, strategic procurement, supply chain planning, and logistics capabilities previously available mainly to larger organizations.

This democratization of supply chain expertise can help smaller businesses become more efficient, competitive, and capable of participating in global markets. It also presents an opportunity to create high-value employment, develop Filipino professionals, expand our services exports, and contribute to economic growth.

Just as the Philippines established itself as a global leader in business process outsourcing, we can build a new generation of knowledge-intensive, AI-enabled supply chain services for the world.

We need not wait until every domestic supply chain challenge has been resolved before pursuing this opportunity. By serving global markets, we can simultaneously strengthen our own capabilities, develop new industries, and create expertise that benefits Philippine businesses and institutions.

However, technology and expertise alone will not be enough. Our global competitiveness must be built on trust.

Ethics: The Foundation of Sustainable Competitiveness

Corruption and unethical business practices weaken supply chains, distort supplier selection, increase procurement costs, compromise quality, and undermine confidence in institutions.

In the public sector, these failures can affect essential infrastructure, healthcare, education, and public services. In the private sector, unethical sourcing and supplier relationships expose companies to financial losses, operational disruptions, reputational damage, and legal risks.

Conversely, ethical supply chain practices strengthen transparency, accountability, fair competition, and responsible decision-making. They build confidence among investors, customers, business partners, employees, and the public.

Ethics is not merely a compliance requirement. It is a competitive advantage and a foundation for sustainable investments and economic growth.

If we aspire to serve global businesses as their trusted supply chain partner, ethical leadership must become part of our professional identity and organizational culture.

Artificial intelligence can help us improve transparency, detect irregularities, evaluate suppliers, and strengthen decision-making. But technology must operate within ethical frameworks and remain subject to human accountability. Ethics must extend beyond declarations into measurable actions and results.

PASIA’s Higher Drive for Ethics and Supply Chain Leadership

Recognizing this need, PASIA is intensifying its advocacy through a comprehensive Ethics and Supply Chain Leadership initiative for private and public organizations. We will formally launch this drive during PASIAWorld 2026 on October 8–9.

Our objective is to help organizations institutionalize ethical practices, strengthen leadership capabilities, and demonstrate measurable improvements.

The initiative will encompass ethical standards, organizational and professional assessments, structured training, examinations, independent validations, and maturity index reporting. It will also facilitate industry collaboration, benchmarking, best-practice sharing, targeted interventions, and recognition programs.

These mechanisms will help organizations understand their current capabilities, identify improvement opportunities, and measure progress toward ethical and effective SCM.

We invite companies, industry associations, government institutions, global development partners, foundations, donors, and individuals to support this advocacy through partnerships, funding, expertise, and participation. This is a shared responsibility requiring collective action.

Dare to Lead                                                                                                                       

PASIA Institute & Shared Services

The Philippines has the opportunity to become the Supply Chain Services Capital of the World by serving businesses globally with Filipino expertise, AI-powered solutions, and ethical leadership.

We have the people, processes, and potential. What we need is the collective determination to lead.

As PASIA approaches its 25th anniversary in 2027, we are strengthening our commitment to this vision.

I invite business leaders, policymakers, supply chain professionals, and development partners to join us at PASIAWorld 2026 on October 8–9 at the SMX Convention Center MOA, as we advance our theme:

“ASEAN Supply Chains in Flux: Synergy, AI & the New Competitive Edge — Building Intelligent, Resilient and Ethical Supply Chains.”

Together, we can build trusted businesses, attract sustainable investments, create high-value opportunities, and develop supply chains that contribute to stronger economies and better lives. Let us dare to lead.

(The author is a member of the Management Association of the Philippines (�����Թ�) Trade, Investments and Tourism Committee, and �����Թ� International Relations Committee. He is Founder and Chair of PASIA and PASIA Shared Services. He has held leadership roles at 3M, Coca-Cola, Chevron/Caltex, Ariba, China Bank, and LBC. He currently serves as Senior Supply Chain Advisor under the U.S. Department of State’s LEAP Program and champions ethical, AI-enabled supply chain services and the development of Filipino expertise for global markets. Feedback at <map@map.org.ph> and <charlie.villasenor@transprocure.com>).

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The trade agreements past and present guaranteed market access to every firm. What we want to explore is what happens between the day the market opened, and the day a firm starts earning something from it. In that space is where most trade agreements die quietly – not in the negotiating room but in that gap between a legal right and an operating capability. Market access is a condition; market advantage is a capability. Access is granted but advantage is built.

RCEP cannot build that advantage for businesses. It cannot find the customers, develop products, create trust, or decide where they should compete. It cannot execute the strategy. Those remain the job of business. How then can we convert access into advantage? It starts by not assuming that access means a jump into immediate growth – a mistake we often make with large regional initiatives.  There is no flying leap; we need to climb stairs made up of small, even slow and unglamorous but sequential steps — something that even an ordinary firm with ordinary resources should be able to do. Let us go through these five steps.

SEE. First, see where the real opportunities are – not just in market size but where demand is growing, where capabilities are complementary, where supply chains are reorganizing, where technology, capital and talent are moving, and where a company, an industry or an economy has something distinctive to contribute. Opportunity is not evenly distributed, and the first competitive advantage is knowing where to look.

CHOOSE. We cannot pursue everything – we must choose our battles. We do not run after every market, or every sector, not even after every opportunity. We look at where we can actually win because we have the capabilities and capacities. Strategies require these choices.

CONNECT. Then, connect because opportunity requires relationships, customers, partners, distributors, investors, suppliers, technology providers, financial and other institutions, and governments. Regional integration does not happen because countries sign agreements. It happens because people and businesses begin doing things together. No company—and for that matter, no economy—creates competitive advantage entirely by itself.

INTEGRATE. Connection is not enough, however. The greater opportunity is to participate in the regional value chain – be a part of the system, shifting and moving up and across trade routes to value networks.

SCALE. Finally, scale. One successful transaction can be merely opportunistic, but repeated transactions create a business. A business that can replicate its model across several markets begins to create competitive advantage. When something works, replicate it, deepen it, invest in it, expand into adjacent markets. We keep participating, whether in bigger or smaller roles, until participation becomes an advantage, and that advantage begins generating the next opportunity.

In other words, there are no quick fixes; only a painstaking equation until we arrive at better solutions. Access means we can enter. Participation means we are doing business. Integration means we have become part of the system. Scale means we can replicate and deepen that position, and advantage means what we have accumulated make it easier for us to compete again.

We now see an impressive regional architecture waiting to be used – but access does not automatically ensure participation. While underutilization is a symptom, it is not necessarily the root problem. Procedures can be cumbersome and rules can be too difficult to understand. Information does not reach the businesses that need it and regulatory differences remain. Compliance can cost more than it saves, and smaller companies simply do not have the resources to navigate the system.

On the flipside, there is something less visible but equally important – the economics of confidence. A business will tolerate complexity if the opportunity is sufficiently attractive. It will invest across borders if it has confidence in the market, the partners and the operating environment. If the opportunity is uncertain, even the most beautifully designed agreement may remain underused; so, the challenge is not simply to make RCEP easier to use. It is to make participation valuable enough that businesses want to use it. When accessed, we begin fueling the regional growth engine.

This is NOT A ZERO-SUM GAME. Regional integration does not have to mean every economy competing for the same piece of the pie. It can mean creating a larger pie by connecting complementary strengths. A market gives us somewhere to sell. An engine gives us a system that keeps generating opportunities. Businesses do not invest in agreements. They invest in opportunities.

INTEGRATION DOES NOT HAPPEN AUTOMATICALLY.

One cautionary note is that we should recognize the danger in becoming too enthusiastic about the opportunity just because we have seen regional initiatives elsewhere that promised enormous potential. We should ask the question: did they fully realize the intended benefits? These experiences matter not because they tell us integration does not work, but because they tell us what can prevent it from failing. Experience, after all, is an economic asset.

Five lessons stand out:

Access without utilization creates very little value. An agreement can exist, but if businesses do not understand it or cannot navigate it, its potential remains largely theoretical.

Integration without competitiveness is fragile. Connecting businesses does not automatically make them competitive. If the economics do not work, the relationship will not last.

Cooperation without commercial logic can become ceremonial. We can have forums, memoranda, delegations and announcements but eventually, somebody has to buy something. Somebody has to invest. Somebody has to produce. Somebody has to create value. That is where integration becomes real.

Regional integration must not become an exclusive club for the largest companies. If MSMEs and smaller businesses cannot participate, then we may create integration—but not necessarily broad-based development.

And finally, efficiency alone is not enough. We need resilience as well, because time and again we have been shown that the most efficient value chain is not necessarily the most resilient one. In a world of geopolitical tensions, disruptions, climate events and rapidly changing technologies, the regional growth engine must be designed to absorb shocks as well as generate growth.

EAST ASIA: WHERE THE OPPORTUNITY IS

RCEP can be a genuine moment in this region’s trade evolution, but it is not the answer, and it is not the opportunity. It is the infrastructure that allows us to pursue the opportunity. The opportunity is East Asia itself, with its enormous markets, inter-connected supply chains, investment flows, technology and complementary economies. The goal is to become more deeply connected to how East Asia produces, consumes, invests, innovates and grows — and in doing so, to transform market access into market advantage, and market advantage into sustained and shared growth.

As had been said, RCEP opens the door, but it does not walk us through it. It creates a common framework within which businesses can increasingly think across markets. It does not create the whole chain, but it lowers some barriers and creates a platform. Businesses have to build the rest.

RCEP requires work.  We must understand the rules, the documentation, the standards and the market requirements. That same work can likewise turn bureaucracy from an obstacle into capability, but only when we stop thinking of it as the cost of RCEP and start treating it as the price of learning how to play in a much larger economic system. For governments, that means creating the conditions for businesses to connect and compete. For institutions, it means turning the agreement into usable knowledge, relationships and opportunities. For companies, it means going beyond what markets can we enter, to asking what role we can play in this regional system.

I believe we are ready to build the engine and for RCEP to become much more than an agreement that gives us access. RCEP must become the platform on which we build something much bigger – an integrated East Asian growth engine capable of generating opportunity, creating value, building resilience and compounding growth across the region. We should share the aspiration that if we can do this right this time, or at least, give it a serious try – that success will create the conditions for the next frontier — a borderless trade.●

(The author is Co-Vice Chair of the �����Թ� Trade, Investments and Tourism Committee; Chair of the �����Թ� CEO Conference Committee; President and CEO of Health Solutions Corporation; and former Undersecretary of the Department of Tourism. Feedback at map@map.org.ph)

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Much has been said about enabling policy environment in trade, but we need to ask what that environment means from the perspective of the people and businesses who must live with the policies. When the world changes, the first question for them is not ‘what agreement do we have’ but what has changed—and what does that change make possible?’ Then, let us ask what we do with the opportunities made possible by these changes.

This is an important conversation because the world is changing faster, and the global economy is rewiring, trade routes are being reconfigured, capital is moving differently, and technology is changing not only what we produce, but where and how value is created. These fundamentally challenges many of our traditional assumptions about markets, supply chains and competitiveness.

Our questions should go beyond where can we sell to where should we produce, who should we partner with, where should we invest, and more importantly, where do we belong in the system that creates value? Nowhere is this more consequential than in East Asia – a region that has become much more than a collection of national markets. It is an inter-connected economic system where capital, technology, components, services, talent and investments move across the borders of fifteen countries.  Each bring different capabilities, resources, markets and strengths. That economic system did not emerge overnight but was built layer by layer over decades.

FROM AGREEMENTS TO AN ECONOMIC ARCHITECTURE

AFTA is the beginning when it reduced tariff barriers within ASEAN. Then came the ASEAN+1 agreements, extending the region’s connections to major economic partners. It continued with trade facilitation, customs cooperation, digitalization and the ASEAN Single Window – all adding another layer because they recognized that lowering tariffs will not mean much if goods still cannot move easily.

While every layer addressed a problem, it also revealed the next ones. AFTA showed us that tariffs are not the only barrier to trade. The ASEAN+1 agreements expanded our connections, but multiple agreements with different rules of origin created complexities of their own. That look at trade agreements’ history matters, because it tells us the problem was never lack of market access. It had been utilization, connectivity, rules, capabilities and actual business integration. They opened the growth corridors yet remained less effective in realizing the potential inside them.

This is not because they were flawed, but because the environment is a moving bus, not a stationary bike. The cycle of changes and remedies constantly outpace each other. The opportunity before us is to think bigger than trading across border and to create value across them, because competition itself is shifting from within individual markets to within inter-connected networks.

This is where the Regional Comprehensive Economic Partnership (RCEP) becomes strategically important. My perspective is that RCEP is less about creating another FTA, and more about bringing the existing architecture into one broader framework. Its potential is greater integration, achieved not by everyone doing the same thing, but by an assembly line of strengths becoming more valuable because they are connected. A component does not have to originate entirely in one country. A company does not have to do everything by itself. That complementarity is where the productive conversion of opportunity lies.

This is the mindset shift that RCEP invites us to consider – not competing for pieces of a regional market but building the regional market together. Businesses need to look beyond bilateral trade toward regional value chains, sourcing, partnerships and regional markets, and be part of one larger economic space. One country’s strength can become another economy’s opportunity. Just think about the possibilities of 15 economies brought together within a broader regional framework. That is what RCEP can bring to the table.

We are not lacking in examples. The automotive industry, for instance, illustrates the way Asian industries have evolved. A vehicle may carry the identity of one country, but its value is increasingly created across many – technology and capital from one economy, components from several others, assembly in another, with logistics, financing and services spread across the region. The automotive sector no longer operates as separate national industries. It operates as a regional production system.

It is not an isolated example. Electronics tells us the same story, and the list of industries with similar models is expanding. They show that creating value is no longer in just one place but through networks. That changes the question from how much can we export to this market to where do we want to sit in the growth story of East Asia.  Economies and companies combining complementary capabilities across borders create, move and capture value, and their outputs serve customers thousands of kilometers away.

Agreement by itself, does not create growth. The region provides the opportunity, businesses the capabilities, the connections, the pathways – and execution creates the advantage. Singapore did not become a powerful regional hub simply because it had access to markets. It built an ecosystem around that access – logistics, infrastructure, finance, institutions, talent and trusted relationships. RCEP in this context, is a platform – not the engine.

The trade agreements past and present guaranteed market access to every firm. What we want to explore is what happens between the day the market opened, and the day a firm starts earning something from it. In that space is where most trade agreements die quietly – not in the negotiating room but in that gap between a legal right and an operating capability. Market access is a condition; market advantage is a capability. Access is granted but advantage is built.

RCEP cannot build that advantage for businesses. It cannot find the customers, develop products, create trust, or decide where they should compete. It cannot execute the strategy. Those remain the job of business. How then can we convert access into advantage? It starts by not assuming that access means a jump into immediate growth – a mistake we often make with large regional initiatives.  There is no flying leap; we need to climb stairs made up of small, even slow and unglamorous but sequential steps — something that even an ordinary firm with ordinary resources should be able to do. Let us go through these five steps.

SEE. First, see where the real opportunities are – not just in market size but where demand is growing, where capabilities are complementary, where supply chains are reorganizing, where technology, capital and talent are moving, and where a company, an industry or an economy has something distinctive to contribute. Opportunity is not evenly distributed, and the first competitive advantage is knowing where to look.

CHOOSE. We cannot pursue everything – we must choose our battles. We do not run after every market, or every sector, not even after every opportunity. We look at where we can actually win because we have the capabilities and capacities. Strategies require these choices.

CONNECT. Then, connect because opportunity requires relationships, customers, partners, distributors, investors, suppliers, technology providers, financial and other institutions, and governments. Regional integration does not happen because countries sign agreements. It happens because people and businesses begin doing things together. No company—and for that matter, no economy—creates competitive advantage entirely by itself.

INTEGRATE. Connection is not enough, however. The greater opportunity is to participate in the regional value chain – be a part of the system, shifting and moving up and across trade routes to value networks.

SCALE. Finally, scale. One successful transaction can be merely opportunistic, but repeated transactions create a business. A business that can replicate its model across several markets begins to create competitive advantage. When something works, replicate it, deepen it, invest in it, expand into adjacent markets. We keep participating, whether in bigger or smaller roles, until participation becomes an advantage, and that advantage begins generating the next opportunity.

In other words, there are no quick fixes; only a painstaking equation until we arrive at better solutions. Access means we can enter. Participation means we are doing business. Integration means we have become part of the system. Scale means we can replicate and deepen that position, and advantage means what we have accumulated make it easier for us to compete again.

We now see an impressive regional architecture waiting to be used – but access does not automatically ensure participation. While underutilization is a symptom, it is not necessarily the root problem. Procedures can be cumbersome and rules can be too difficult to understand. Information does not reach the businesses that need it and regulatory differences remain. Compliance can cost more than it saves, and smaller companies simply do not have the resources to navigate the system.

On the flipside, there is something less visible but equally important – the economics of confidence. A business will tolerate complexity if the opportunity is sufficiently attractive. It will invest across borders if it has confidence in the market, the partners and the operating environment. If the opportunity is uncertain, even the most beautifully designed agreement may remain underused; so, the challenge is not simply to make RCEP easier to use. It is to make participation valuable enough that businesses want to use it. When accessed, we begin fueling the regional growth engine.

This is NOT A ZERO-SUM GAME. Regional integration does not have to mean every economy competing for the same piece of the pie. It can mean creating a larger pie by connecting complementary strengths. A market gives us somewhere to sell. An engine gives us a system that keeps generating opportunities. Businesses do not invest in agreements. They invest in opportunities.

INTEGRATION DOES NOT HAPPEN AUTOMATICALLY.

One cautionary note is that we should recognize the danger in becoming too enthusiastic about the opportunity just because we have seen regional initiatives elsewhere that promised enormous potential. We should ask the question: did they fully realize the intended benefits? These experiences matter not because they tell us integration does not work, but because they tell us what can prevent it from failing. Experience, after all, is an economic asset.

Five lessons stand out:

Access without utilization creates very little value. An agreement can exist, but if businesses do not understand it or cannot navigate it, its potential remains largely theoretical.

Integration without competitiveness is fragile. Connecting businesses does not automatically make them competitive. If the economics do not work, the relationship will not last.

Cooperation without commercial logic can become ceremonial. We can have forums, memoranda, delegations and announcements but eventually, somebody has to buy something. Somebody has to invest. Somebody has to produce. Somebody has to create value. That is where integration becomes real.

Regional integration must not become an exclusive club for the largest companies. If MSMEs and smaller businesses cannot participate, then we may create integration—but not necessarily broad-based development.

And finally, efficiency alone is not enough. We need resilience as well, because time and again we have been shown that the most efficient value chain is not necessarily the most resilient one. In a world of geopolitical tensions, disruptions, climate events and rapidly changing technologies, the regional growth engine must be designed to absorb shocks as well as generate growth.

EAST ASIA: WHERE THE OPPORTUNITY IS

RCEP can be a genuine moment in this region’s trade evolution, but it is not the answer, and it is not the opportunity. It is the infrastructure that allows us to pursue the opportunity. The opportunity is East Asia itself, with its enormous markets, inter-connected supply chains, investment flows, technology and complementary economies. The goal is to become more deeply connected to how East Asia produces, consumes, invests, innovates and grows — and in doing so, to transform market access into market advantage, and market advantage into sustained and shared growth.

As had been said, RCEP opens the door, but it does not walk us through it. It creates a common framework within which businesses can increasingly think across markets. It does not create the whole chain, but it lowers some barriers and creates a platform. Businesses have to build the rest.

RCEP requires work.  We must understand the rules, the documentation, the standards and the market requirements. That same work can likewise turn bureaucracy from an obstacle into capability, but only when we stop thinking of it as the cost of RCEP and start treating it as the price of learning how to play in a much larger economic system. For governments, that means creating the conditions for businesses to connect and compete. For institutions, it means turning the agreement into usable knowledge, relationships and opportunities. For companies, it means going beyond what markets can we enter, to asking what role we can play in this regional system.

I believe we are ready to build the engine and for RCEP to become much more than an agreement that gives us access. RCEP must become the platform on which we build something much bigger – an integrated East Asian growth engine capable of generating opportunity, creating value, building resilience and compounding growth across the region. We should share the aspiration that if we can do this right this time, or at least, give it a serious try – that success will create the conditions for the next frontier — a borderless trade.●

(The author is Co-Vice Chair of the �����Թ� Trade, Investments and Tourism Committee; Chair of the �����Թ� CEO Conference Committee; President and CEO of Health Solutions Corporation; and former Undersecretary of the Department of Tourism. Feedback at map@map.org.ph)

The post BUILDING AN INTEGRATED EAST ASIAN GROWTH ENGINE Converting Market Access to Market Advantage through RCEP appeared first on Management Association of the Philippines.

To be sure, the Philippine Statistics Authority (PSA) reports that the distribution of income in the country has improved in recent years. However, economic inequality persists and continues to be substantial.

The Oxford Committee for Famine Relief, or OXFAM, paints a much gloomier picture. Its latest report shows that the Philippines has the worst distribution of income and wealth in the ASEAN region where severe income inequality continues, despite steady macroeconomic growth. In its 2026 country report, OXFAM Pilipinas notes that the country’s recent upgrade to upper-middle-income status means very little “(to) millions of Filipinos who remain poor, excluded from public services, and highly vulnerable to climate and economic crises.”

OXFAM noted in particular that the richest 1 per cent of Filipinos earned nearly 20 per cent of the total national income, while the share of the lower 50 per cent of the population stood at just 14 per cent of the national income.

This situation is patently unsustainable, and there is an urgent need for the state to remedy this anomaly. Regrettably, the state has been unable (or worse, unwilling) to take the necessary corrective measures.  Foremost among the reasons for the state’s inaction is that many government officials have found common cause with culprits and criminal elements in the community, many of whom being prominent corporate figures, and engaged with them in various forms of corruption, the most audacious among which being the recent flood control scandals by which billions of pesos in project costs have been siphoned off from government coffers,

The Accountability of Business

Business is equally culpable, however.

The long-standing goal of business is the maximization of profits, the portion of the economic value produced by the firm that accrues to its owners, or shareholders, in the case of public corporations. All too often, business firms seek to achieve this goal by appropriating economic value from their other stakeholders by implementing what are collectively known as Shareholder Strategy.

Shareholder strategies are concerned solely with the financial interests of corporate shareholders and focused primarily on the twin goals of increasing revenues on the one hand and controlling costs on the other.

Traditional shareholder strategies emphasize maximizing returns on investment. This is done primarily by putting a lid on operating costs while maintaining a steady inflow of revenue. These business practices tend to contribute to economic inequality. Among them are the following:

• Controlling labor costs by paying workers the prevailing legal minimum wage rates;
• Scrimping on product development, quality improvement and customer services, measure that deprive customers of value for their money;
• Price gouging, a revenue-generating practice employed by monopolies that harms mainly the firm’s poor customers; and
• Ignoring costs of environmental damage resulting from the firm’s operation, a cost-avoiding practice that is more harmful to people who live in shanties than to those who live in airconditioned comfort.

An alternative strategy, one that is increasingly being pursued by progressive corporations, is called Stakeholder Strategy.

Stakeholder strategies are those that aim to maximize profits (or shareholder wealth, in the case of public corporations) by creating value for all of the firm’s other stakeholders, notably their manual workers. For example, by paying higher wages than the prevailing legal minimum rates, workers become more highly motivated and productive, and the firm more profitable in the long run.

Corporate Social Responsibility, or CSR, is a widely practiced business model that integrates social and environmental issues into the operations of the firm. By adhering to CSR, business firms pursue their usual objectives while at the same time taking on the responsibility of addressing society’s problems of poverty, economic inequality and environmental degradation.

The doctrine of CSR obligates business firms to assume the following four types of responsibility to society.

• Ethical responsibility – the general philosophical or religious belief that business firms are morally bound to do good to others;
• Philanthropic responsibility – the firm’s commitment to render financial or material assistance to those in need – the poor, the sick and the hungry;
• Economic responsibility – an obligation consisting of the different strategies by which business firms can help hasten economic growth and promote welfare; and
• Environmental responsibility – which includes the corporate obligation to reduce global warming by minimizing carbon emission, implementing proper waste disposal, and by shifting to renewable sources of energy.

These corporate responsibilities commit the firm to do good to others by sharing economic value with them that otherwise would have been part of profits, an apparent departure from the long-standing dictum that the sole function of the firm in modern society is to maximize profits

We continue to subscribe to the traditional theory that the goal of the firm in a Capitalistic society is to maximize profits, but maintain that the most efficacious way of doing so is by creating value for all other stakeholders in the firm – its workers, its customers, its business partners, and the community.

A more revolutionary approach to addressing economic inequality and global warming is one proposed by eminent French economist Thomas Piketty.

In his landmark book, Time for Socialism: Dispatches from a World om Fire, Piketty observes that the rampant abuses of business firms in capitalistic economies stems from a free market economy that has become too free-wheeling. He advocates a hybrid economic system that combines features of Capitalism and Socialism in order to put in check the rampant abuses of business firms, and to hold erring public officials accountable for their misdeeds. In this mixed system, the state plays a more dominant role in managing the economy for the greater interest of society

This idea is intriguing, but we fear that its implementation will be too disruptive and will introduce unforeseen forces that are too difficult to control. We prefer a gradual, incremental change strategy that will bring about predictable, steady improvements, rather than one that will bring the system to the desired state in one fell swoop.

(The article reflects the personal opinion of the author and does not reflect the official stand of the Management Association of the Philippines or �����Թ�. The author is a member of the �����Թ� Shared Prosperity Committee and Retired Professor of Economics and Management at UP Diliman. Feedback at <map@map.org.ph> and <nspoblador@gmail.com>).

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For board directors in the Philippines and ASEAN, this is not abstract. It goes to the heart of governance credibility, particularly in economies where growth is rapid, ownership structures are concentrated, and public trust remains fragile.

Beyond the Word

Integrity is often equated with personal honesty. But in the boardroom, it demands far more. It means:

• Consistency between values and decisions
• Independence of mind, not just formal independence
• The courage to challenge dominant voices
• Transparency, even when uncomfortable
• Loyalty to the institution above personal or political relationships

In many ASEAN contexts, this last point is critical. Boards often operate within networks of long-standing relationships, family, business, or political which can blur lines between loyalty and objectivity. Integrity, therefore, is not simply about character. It is about discipline under pressure.

Integrity in Practice

In real terms, integrity is visible in everyday board decisions:

• Challenging Management: In hierarchical cultures, questioning leadership can be seen as disrespect. Yet effective oversight depends on it. A board that does not ask difficult questions is not governing; it is endorsing.
• Managing Conflicts of Interest: Across ASEAN, related-party transactions and cross-directorships are common. Integrity requires not only disclosure but clear boundaries and, when necessary, recusal.
• Approving Strategy: Boards must look beyond profitability. Rapid expansion common in emerging markets can expose companies to regulatory, environmental, and reputational risks, if not carefully scrutinized.
• Acting on Early Warning Signs: Whistleblower complaints, audit findings, or operational anomalies must be addressed early. Delay is often the difference between manageable risk and full-blown crisis.
• Aligning Incentives: Aggressive growth targets are frequent in developing markets and unintentionally encourage misconduct, if not balanced with ethical safeguards.

Lessons from Regional and Global Failures

Governance failures, both global and regional, reveal the cost of treating integrity as a formality.

Globally, Enron showed how passive boards and conflicts of interest can destroy an institution. Volkswagen demonstrated how weak ethical culture can override even sophisticated governance structures.

Integrity failures are not confined to corporations. They occur whenever those entrusted with stewardship of public or private resources prioritize personal gain over institutional purpose.

Closer to home, the ongoing controversy surrounding flood-control projects offers a stark reminder that integrity failures carry consequences beyond financial loss. Reports suggest that despite massive public spending, many communities remained vulnerable to flooding, raising questions about whether public resources were used effectively and for their intended purpose.

Across Southeast Asia, similar patterns recur:

• Concentrated ownership limiting independent oversight
• Boards reluctant to challenge controlling shareholders
• Cultural emphasis on harmony discouraging dissent

These cases differ in context but share one core issue: Integrity was present in policy but absent in practice.

Why Integrity becomes Lip Service in ASEAN? Why does this gap persist?

• First, cultural dynamics: In many ASEAN societies, respect for hierarchy can limit open challenge. Consensus is valued, but it can sometimes suppress necessary dissent.
• Second, ownership structures: Family-controlled and closely held companies remain common. This can blur the line between governance and management.
• Third, growth pressure: Emerging markets prioritize rapid expansion. In the process, governance discipline can lag behind business ambition.

As a result, integrity risks becoming symbolic visible in disclosures but not embedded in decisions.

From Statement to Discipline

For boards in the Philippines and ASEAN, the challenge is clear: Integrity must move from aspiration to practice.

This requires:

• Genuine independence of thought
• Safe space for dissent and challenge
• Strong oversight of related-party transactions
• Alignment between incentives and values
• Continuous reflection on board effectiveness

Most importantly, integrity must be demonstrated consistently, not selectively.

Integrity is not tested when decisions are easy. It is tested when choices are difficult, when relationships, performance, and principles collide. Boards must therefore confront a fundamental question: Is integrity something we declare or something we demonstrate? In ASEAN, where trust in institutions is still evolving, the answer matters deeply. Organizations do not fail because they lack values.

They fail because those values are not reflected in decisions. The test of governance is not what boards declare but how they decide. For boards, integrity must move beyond the annual report into the boardroom itself. Only then can directors fulfill their true role as guardians of trust in ASEAN’s growing economies.

(The author is a member of �����Թ� Diversity, Equity & Inclusion (DEI) Committee and �����Թ� Education Committee. She is Past Vice Chair and President of the Institute of Corporate Directors (ICD). She was the first female Chair of the Bases Conversion & Development Authority (BCDA).  She is President of Mageo Consulting Inc., a company providing corporate finance advisory services. Feedback at <map@map.org.ph> and <magg@mageo.net>.)

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