AI & Blockchain Visibility for Project Leaders

Digital transformation is now a strategic imperative for Filipino organizations.

AI and blockchain technologies are being deployed across enterprises to reshape business models and competitive advantage. Yet as adoption accelerates, a critical gap emerges: the risks these technologies introduce remain largely invisible.

Recent data underscores this urgency. A 2024 IBPAP survey found that 56% of Philippine IT-BPM firms are

actively implementing AI.¹ Most deployments are in pilot or early implementation phases—precisely when unmanaged risks surface. At the same time, the Bangko Sentral ng Pilipinas maintains an indefinite moratorium on new blockchain licensing, citing heightened systemic risks and the need for stronger oversight.² The message is clear: adoption is

accelerating, but risk governance has not kept pace.

For project professionals, this represents both a challenge and an opportunity. Project leaders who can translate technical complexity into actionable risk intelligence create real value protecting not just their projects, but their organizations' ability to operate with stakeholder trust.

Why AI and Blockchain Create New Risks

Traditional project risks remain familiar: cost overruns, schedule delays, scope creep, stakeholder misalignment. These continue to demand attention.

But, AI introduces different threats. Models produce decisions whose underlying logic is often opaque. Bias embeds itself in training data and surfaces only when consequences become visible. In fact, data changes over time—a phenomenon called "data drift"—and model performance degrades without warning. Most critically: with AI, you cannot easily explain why a system made a particular decision. The decision-making logic remains hidden.

Blockchain adds another layer. Smart contracts execute automatically without human review. Once deployed, they cannot be changed—even when errors are discovered. Code vulnerabilities persist indefinitely, and their consequences compound rather than diminish.

These are not marginal concerns. They directly threaten core project objectives: cost, schedule, quality, and stakeholder confidence. A biased AI model exposes businesses to reputational damage and regulatory exposure. A smart contract code defect represents potential financial loss and project failure.

The Translation Problem: Where Project Leaders Create Value

Most organizations treat emerging technology risks as an engineering challenge to be resolved by technical teams. However, this assumption is incomplete.

Technical teams understand the technology. Business stakeholders understand what failure costs. Neither perspective alone produces effective risk management. Project leaders occupy the middle ground: translating technical reality into business consequence.

Effective risk translation demands specificity. It’s not enough to say, "An AI model bias exists." We must articulate the impact: "Bias in our concrete curing prediction model leads to inaccurate scheduling, causing average delays of 3 to 5 days and additional labor costs of up to ₱250,000 per day."

Specificity in risk definition enables transparency and auditability. When paired with strong governance and regulatory alignment, they empower stakeholders to engage with meaningful risk mitigation strategies.

This translation is especially critical now. According to IBPAP, 56% of IT-BPM firms are implementing AI but most remain in early deployment phases.³ This is the highest-vulnerability window, when unmanaged risks are most likely to surface. That’s why risk governance must begin at project initiation — not be deferred to later stages.

And, project leaders who excel at translating risks do more than manage projects — they shape how their organizations approach emerging technology adoption.

4 Practical Steps to Update Your Risk Register for AI & Blockchain

Evolving risk frameworks for emerging technologies doesn’t require reinventing the wheel. You simply need focused, structured action.

1. Link Technical Risks to Business Impact

   Use the 3C’s—Cause, Context, Consequence—to describe risks with precision and relevance to business.

2. Build in Transparency and AuditabilityRequire dashboards with clearly defined models and metrics. Integrate model performance metrics into baseline planning. Make code and audit review findings mandatory project stage gate criteria before deployment.

3. Strengthen Governance Protocols

   Create feedback loops to surface emerging risks; Place sufficient prioritization on addressing AI and Blockchain identified risks alongside traditional risks.

4. Align with Regulatory Signals

   Ensure your risk register reflects the latest regulatory context—accurate, updated, and relevant to your business and technology area.

The Leadership Imperative

Project risk management, when executed properly, does more than improve success rates. It reduces uncertainty and improves predictability. Yet many organizations approach emerging technology risks with denial, assuming technical teams will manage risks even without explicitly integrating findings into their project governance.

Project professionals have the opportunity to create value precisely by translating technical complexity into actionable risk intelligence. You aren’t expected to become a data scientist or blockchain engineer. You simply need to ask uncomfortable questions: What happens if this model fails? What audit trails exist? What recovery options remain?

Organisations that succeed in digital transformation share one defining characteristic: their project leaders maintain visibility into emerging technology risks. They integrate those risks into enterprise governance and escalate them with the same priority as schedule and cost.

This visibility safeguards more than project outcomes - it protects stakeholder trust and the organizational license to operate.

The question isn’t whether your organization will adopt AI and blockchain. The question is whether those adoptions can be managed with the discipline that separates successful digital transformation from expensive failures.

Taking the Next Step

Managing emerging technology risks demands discipline, frameworks, and continuous learning. Visit PMI Online (www.PMI.org) to access various online resources to support your growth, including detailed information about the PMI Risk Management Certification. This certification path helps you build advanced risk management skills for traditional projects, AI, Blockchain, and beyond. As digital transformation accelerates, formal expertise in risk management will set you apart and strengthen your influence on governance.

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References: 1 - IT & Business Process Association of the Phils (IBPAP). IT-BPM Adoption of AI: Highlights from IBPAP Member Survey. Mid-2024 Survey; 2 - Bangko Sentral ng Pilipinas. Moratorium on Virtual Asset Service Provider Licensing. Memor. Aug 20, 2025; 3 - IBPAP survey indicates most AI implementations remain in pilot or early deployment phases as of mid-2024, representing the highest-risk period for uncontrolled risk emer-gence; 4 - Bangko Sentral ng Pilipinas. The extension under-scores the BSP's commitment to protect consumers and uphold financial system stability, citing heightened risks and the need for strengthened supervisory capacity, 2024.