Richard Wong, PhD 

Enterprise AI Strategy 

Designing AI as a core enterprise capability—aligned to business value, governance, and long-term resilience. 

Executive Summary 

AI strategy is not about deploying models or adopting tools—it is about aligning data, technology, governance, and organizational capabilities to drive measurable enterprise outcomes. I work with boards and executive leadership to design AI strategies that are economically grounded, risk-aware, and scalable across the enterprise, ensuring that AI investments translate into durable business value. 

Why AI Strategy Often Falls Short 

Many organizations invest heavily in AI yet struggle to realize meaningful impact. Common failure modes include: 

• Disconnected pilots that lack economic justification

• AI initiatives misaligned with core business priorities

• Insufficient governance and accountability structures

• Underdeveloped operating models and unclear decision rights

• Organizational resistance and gaps in executive AI literacy

A successful AI strategy addresses these challenges holistically treating AI as an enterprise capability rather than a collection of isolated experiments. 

My Enterprise AI Strategy Framework 

My approach to AI strategy is structured around five integrated pillars that ensure alignment, scalability, and trust. 

1. Business & Economic Alignment 

AI initiatives must be anchored in clear value hypotheses and economic discipline. This includes defining expected returns, prioritizing use cases based on strategic importance, and aligning AI investments with capital allocation and planning cycles. 

2. Data & Technology Foundation

Effective AI strategy requires a realistic assessment of data readiness, architecture, and model lifecycle management. This pillar focuses on building fit-for-purpose data foundations, making informed build-versus-buy decisions, and ensuring technical scalability without unnecessary complexity. 

3. Governance & Risk

AI governance is inseparable from AI strategy. This includes responsible AI principles, model risk management, regulatory readiness, and clear accountability for AI decisions—particularly in regulated or high-stakes environments. 

4. Operating Model

AI must be embedded into how the enterprise operates. This pillar defines ownership models, decision rights, centralized versus federated approaches, and integration with existing business and technology functions. 

5. Talent & Culture

Sustainable AI capability depends on people. This includes leadership roles, capability development, executive education, and cultural alignment to ensure AI adoption is supported—not resisted—across the organization. 

How I Engage with Executive Leadership 

I work with senior leaders in advisory and strategic roles, including: 

• Executive AI strategy assessments

• Enterprise AI roadmap and operating model design

• Board-level AI briefings and decision support

• AI governance and risk framework development

• Engagements are tailored to organizational context, maturity, and strategic objectives. 

Selected Strategic Outcomes 

My work will support outcomes such as: 

• Enterprise-wide AI strategies aligned with corporate and financial planning

• AI governance frameworks integrated with enterprise risk management

• Decision intelligence and forecasting embedded into executive workflows

• Improved alignment between AI investments and business priorities

AI Strategy Principles 

My approach to enterprise AI strategy is guided by several core principles: 

• AI must be economically justified

• Governance must scale with capability

• AI decisions are business decisions

• Risk management enables sustainable innovation

• Strategy precedes tooling

• Focus is always on outcomes, not experimentation for its own sake. 

These principles ensure AI remains a source of competitive advantage rather than operational or reputational risk. 

Who This Is For 

This work is most relevant for boards, CEOs, Chief AI Officers, CIOs, CROs, and senior leaders responsible for enterprise transformation, risk management, and long-term value creation. 

Call to Action 

Interested in developing or refining your enterprise AI strategy?

Start a conversation.