AI initiatives are multiplying
Different teams are exploring tools and pilots, but no one owns the overall direction.
Flagship offer
Fractional Head of AI leadership for companies that need sustained senior judgment.
Stuart Schaefer brings executive-level AI leadership for organizations that need long-term strategy, architecture, orchestration, governance, and implementation direction without waiting for a full-time hire.
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Generate a premium executive meeting or architecture review image: senior leaders evaluating AI strategy on a large display, realistic, confident, boardroom-safe.
When this fits
When a fractional Head of AI is the right move.
This model works when AI has become important enough to need senior ownership, but not yet structured enough to justify a full-time executive hire.
Leadership wants revenue and profit impact
The organization needs prioritization, judgment, and a clearer path from AI activity to pricing revenue, cost reduction, friction reduction, and ROI.
Architecture and governance decisions matter
The company needs system direction before weak choices compound.
Vendors need evaluation
Leadership needs grounded assessment rather than sales-driven advice.
Ownership is unclear
There is AI activity, but not yet an executive-level operating model.
The company is not ready for a full-time CAIO
A fractional model gives access to senior capability without a premature org commitment.
Scope
What Stuart does in a fractional Head of AI role.
The role is designed as a long-term executive advisory relationship, typically one year or longer, that brings senior AI judgment into the organization in a practical, operationally useful way.
- AI roadmap and prioritization tied to pricing revenue, profit, cost, and friction reduction
- Architecture direction across data, context, models, agents, embedded AI, explicit AI tools, systems, and workflows
- Governance, quality standards, review points, and accountability
- Workflow and adoption design to fit real business execution
- Vendor, platform, build, and buy evaluation
- Output quality, evaluation, and reliability oversight
- Executive communication and decision support
- Implementation guidance close enough to move from idea to execution
Outcomes
What this should change.
- Clearer AI priorities and success criteria
- Better pricing, margin, cost, and workflow decisions
- Better alignment between executives, business owners, technical teams, and vendors
- Fewer dead-end pilots and tool experiments
- Stronger governance, review, and control environment
- More reliable AI-supported operating systems
- Faster movement on high-value initiatives
- Greater confidence in AI-related investment decisions
The goal is not to add more AI activity. The goal is to make AI activity more selective, more reliable, and more valuable.Operating principle for the engagement
Why Preedix
Technical depth with enterprise operating judgment.
Many organizations can find strategy language. Fewer can find senior AI leadership that combines architecture depth with real operating and financial experience.
Preedix brings that combination. The work is grounded in AI architecture, machine learning, deep learning, genAI, agents, embedded AI capabilities, explicit AI tools, data and context design, workflow design, controls, governance, and cloud deployment, but also in enterprise operations, finance, planning, and execution.
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Engagement shape
How the engagement works.
Engagements are typically structured as executive retainers with a defined leadership cadence and focused work around priority initiatives. The preferred fit is a long-term advisory relationship of one year or more.
- Regular executive advisory sessions
- Revenue, profit, cost, and friction reduction agenda
- Architecture and decision reviews
- Priority use case evaluation and success testing
- Governance and control guidance
- Cross-functional alignment with business and technical leaders
- Limited hands-on support for critical initiatives
Request an advisory conversation
Bring senior AI leadership into the room.
If your organization needs clearer priorities, stronger controls, architecture direction, or AI-First orchestration for revenue and profit improvement, start the conversation here.
Typical starting points
- Executive AI roadmap ownership
- AI-First orchestration across tools, workflows, and governance
- Revenue, profit, cost, and friction reduction priorities