Human-centred AI enablement
I help organizations move beyond AI pilots to meaningful, sustainable adoption. If your team has the tools but isn't seeing progress, that's the problem I solve – by building confidence and capability with AI through hands-on training, change management and workflow integration.
Why adoption fails – and what works
Most AI initiatives stall not because the tools are wrong, but because the organization isn’t ready to use them. Teams lack training. Workflows haven’t changed. There’s no governance, no internal champions and no clear path from experiment to everyday practice. Deloitte's Tech Trends 2026 report revealed that organizations spend 93% of their AI budgets on technology, and just 7% on the people who need to use it.
I come from marketing, product and operations. That means I approach AI adoption the way any organizational change needs to be approached – with the right mix of guidance, structure, leadership engagement and measurable outcomes. The goal isn't just AI adoption, it's building a workforce that's confident, capable and empowered to use AI as part of how they work every day.
What my approach includes:
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Training and skill-building tailored to your team's actual workflows.
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Internal champions who sustain adoption after the engagement ends.
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Governance and usage frameworks that work in your environment.
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Leadership education so executives can set realistic expectations and measure progress.
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Clear milestones from pilot to integrated practice.
Three layers of AI credibility
Credibility in AI isn’t built on buzzwords or tool stacks. It’s built on a track record of driving adoption – at scale, in complex environments.
Proven adoption leadership
I’ve driven the adoption of new methodologies inside a major carrier – building programs from zero, training large distributed teams, navigating compliance requirements, cultivating internal champions and proving results to senior leadership. That experience is the direct foundation for the AI enablement work I do today.
Structured AI education
Section AI Academy – coursework spanning AI for marketing, research, data analysis, writing, product management, strategic decision-making and agentic workflow design. Cross-functional breadth, not a single-discipline crash course.
Daily AI practice
AI is integrated into research, strategy, content production and client delivery as standard operating method. Clients get AI-enhanced output from day one – no separate engagement required.
How we work together on AI
I offer four engagement types, depending on where your organization is and what your people need. Each can be applied to a central team or scaled across a distributed workforce.
AI Enablement Workshop
A half-day or full-day facilitated session for teams of up to 15–20 people. We start with a current-state assessment of how the team is using AI, move into hands-on demonstration applied to your actual workflows, and close with a use case inventory and adoption roadmap with quick wins and 90-day priorities.
AI Readiness Assessment
A diagnostic engagement evaluating your readiness across people, process, tools, data and governance. We conduct stakeholder interviews, workflow analysis and a governance review. You walk away with a prioritized implementation plan – not a generic framework.
Structured AI Training Program
A 4–8 week cohort-based program that combines live instruction with applied practice. Moves teams from basic AI awareness to confident, workflow-integrated usage.
Retained AI Advisory
Ongoing embedded AI adoption leadership on a monthly retainer – training, coaching, workflow redesign, governance development and internal champion cultivation. Structured in 90-day cycles.
Working in insurance or insurtech? AI adoption in that environment comes with specific organizational and regulatory considerations. And if your distribution model relis on agents, brokers or advisors, the challenge of getting AI adopted at scale is exactly where my background is deepest. Learn more about my insurance offering.