Author
Michael Hibbert
Founder & Principal Advisor, Hibbert Advisory Group
Michael Hibbert is a product leader and executive advisor with 15+ years of experience guiding organizations through AI strategy, product leadership, digital transformation, and growth initiatives across media, technology, SaaS, and professional services.
- 15+ years of product strategy and executive advisory experience
- Led mobile portfolio expansion at The New York Times
- Supported global OTT streaming initiatives across Paramount Global
- Founded JobFit AI, an AI-powered career intelligence platform
- Advises CEOs, founders, and leadership teams on AI adoption and product strategy
Articles by Michael Hibbert
AI Strategy for Executives
How Executives Should Prioritize AI Investments
Leadership teams need a disciplined framework for AI investment—not reactive funding driven by vendor demos or board pressure.
AI Strategy for Executives
Building a Business Case for AI Initiatives
A credible AI business case connects investment to measurable outcomes, resource requirements, and risk—not technology capability descriptions.
AI Strategy for Executives
AI Opportunity Assessment Frameworks for Leadership Teams
Structured assessments give leadership teams an independent, evidence-based view of AI opportunities before vendor commitments.
AI Strategy for Executives
When to Build vs Buy AI Capabilities
Build versus buy is a strategic decision—not an engineering preference. Executives must evaluate differentiation, data, cost, and speed.
AI Strategy for Executives
Aligning AI Strategy with Corporate Strategy
AI strategy fails when disconnected from corporate priorities. Alignment requires explicit linkage to growth, efficiency, and competitive goals.
AI Governance & Risk Leadership
Establishing AI Governance Without Slowing Innovation
Effective governance enables speed through clarity—not bureaucracy that stalls every initiative in committee review.
AI Governance & Risk Leadership
Board-Level AI Oversight and Accountability
Boards increasingly require AI oversight. Executives must provide portfolio visibility, risk reporting, and outcome accountability.
AI Governance & Risk Leadership
Data Privacy and Compliance in AI Adoption
Compliance must shape AI opportunity selection—not be retrofitted after deployment. Executives own the accountability.
AI Governance & Risk Leadership
Managing Vendor Risk in AI Procurement
Vendor selection for AI requires evaluating more than feature demos—data handling, lock-in, and long-term viability matter.
AI Governance & Risk Leadership
Responsible AI Principles for Business Leaders
Responsible AI is operational discipline—not marketing language. Leaders define principles that govern real decisions.
AI Adoption & Organizational Change
Leading Organizational Change During AI Adoption
AI adoption is a change management challenge. Executive sponsorship and communication determine whether initiatives survive first-quarter resistance.
AI Adoption & Organizational Change
Overcoming Employee Resistance to AI Workflows
Resistance is predictable. Leaders who address concerns directly convert skeptics into adoption champions.
AI Adoption & Organizational Change
Training and Enablement Strategies for AI Tools
Training is not a one-time launch event. Sustained enablement builds the literacy AI programs require.
AI Adoption & Organizational Change
Measuring AI Adoption Success Beyond Pilot Metrics
Adoption metrics must connect to business outcomes. Activity metrics without outcome linkage obscure failure.
AI Adoption & Organizational Change
Building AI Literacy Across Leadership Teams
Leadership literacy enables better decisions. Executives do not need engineering depth—they need judgment frameworks.
AI Product & Innovation Leadership
Integrating AI into Product Roadmaps
AI features must compete for roadmap priority on business merit—not hype or competitive panic.
AI Product & Innovation Leadership
Defining AI Product Metrics That Matter
Model accuracy is insufficient. Product metrics must connect AI capabilities to customer and business outcomes.
AI Product & Innovation Leadership
Product Leadership for AI-Enabled Platforms
AI-enabled platforms require product leadership that governs capability, quality, and economics simultaneously.
AI Product & Innovation Leadership
Competitive Positioning with AI Capabilities
Competitive AI positioning requires proprietary advantage—not matching every competitor announcement.
AI Product & Innovation Leadership
From Prototype to Production: Scaling AI Features
Prototypes prove possibility. Production requires quality, monitoring, cost discipline, and operational readiness.
AI Transformation & Execution
Moving from AI Strategy to Implementation
Strategy documents without implementation governance produce plans—not outcomes. Execution requires explicit accountability.
AI Transformation & Execution
Sequencing AI Initiatives for Maximum Impact
Initiative order matters. Poor sequencing wastes investment on initiatives that prerequisites have not enabled.
AI Transformation & Execution
Partnering with Technology Teams on AI Delivery
AI delivery fails when business and technology operate in separate tracks. Partnership requires shared accountability.
AI Transformation & Execution
Fractional Leadership Models for AI Programs
Fractional leadership provides executive governance for AI programs without the timing and cost of full-time hires.
AI Transformation & Execution
Sustaining AI Program Momentum After Launch
Launch is the beginning—not the end. Sustained momentum requires governance, measurement, and continuous portfolio management.
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