AI strategy and governance that executives can defend
Most organizations have AI activity but no AI strategy. I help leaders decide where AI creates real value, sequence the work, and put the governance, policies, and accountability in place so adoption is responsible and scalable.
Book an AI strategy call Free resourcesKey takeaways
- A prioritized, ROI-driven AI use-case portfolio, not scattered pilots.
- A governance framework: policies, guardrails, ownership, and risk controls.
- An AI operating model and Center of Excellence to scale adoption safely.
What AI strategy & governance covers
AI strategy connects business goals to a practical plan: which use cases to pursue, in what order, with what data and budget. Governance is the other half, the policies, controls, and accountability that keep AI use safe, compliant, and trusted. Done together, they turn AI from risky experimentation into a managed capability.
How I help
AI Readiness Assessment
Evaluate data, processes, skills, and risk to find high-ROI, low-friction starting points.
Use-Case Prioritization
Score and sequence opportunities by value, feasibility, and risk into a clear portfolio.
AI Roadmap
A staged plan tying investment to outcomes, with quick wins and a path to scale.
AI Governance Framework
Policies, guardrails, review gates, and ownership for responsible, compliant AI.
AI Center of Excellence
Stand up the team, standards, and reusable playbooks that scale adoption.
AI Risk & Vendor Review
Assess model, data, and vendor risk so choices hold up to scrutiny.
Who it's for
- Executives who need an AI strategy they can present to a board
- Organizations stuck between scattered pilots and governed production use
- Leaders standing up AI policy, governance, or a Center of Excellence
- Teams that need to prioritize AI spend against real business value
Outcomes you can expect
A defensible AI strategy tied to ROI, a governance framework your risk and legal teams trust, and an operating model that lets adoption scale without losing control.
Frequently asked questions
What is an AI governance framework?
A set of policies, guardrails, review steps, and clear ownership that keep AI use safe, compliant, ethical, and aligned to business goals.
How do we prioritize AI use cases?
Score each by business value, feasibility, data readiness, and risk, then sequence into a portfolio with quick wins first and a path to scale.
Do we need an AI Center of Excellence?
Once you have more than a couple of AI initiatives, a CoE standardizes adoption, sets guardrails, and prevents duplicated, ungoverned effort.
Where should we start?
Usually an AI readiness assessment, which surfaces the highest-ROI, lowest-friction use cases and the gaps to address first.
Build an AI strategy you can defend
Let's prioritize your use cases, set the guardrails, and map the path from pilots to governed, scalable AI.
Book an AI strategy call