Use-case discovery
Identifying where AI can assist with research, writing, documentation, analysis, workflows, and internal operations.
AI adoption
I help organizations identify practical uses for AI, integrate tools into everyday workflows, and improve operations without turning the work into empty AI theater.
Overview
Useful AI adoption starts with real work, not hype.
Many organizations know they should be experimenting with AI, but struggle to move beyond scattered prompting, unclear expectations, or disconnected pilots. I help teams approach adoption more deliberately by focusing on workflows, bottlenecks, and tasks where AI can genuinely save time or improve quality.
The aim is not just to introduce tools, but to help people use them well, understand the limits, and build working habits that are efficient, responsible, and grounded in the team’s actual needs.
What I help with
Practical adoption, not abstract excitement.
The work is tailored around how your team already operates, where friction exists, and where AI can support better output.
Workflow optimization
Redesigning recurring processes so AI supports faster drafting, synthesis, triage, and routine knowledge work.
Adoption guidance
Helping teams choose tools, set expectations, build prompting practices, and think through quality control and risks.
Trainings and capacity building
Designing hands-on AI trainings so staff can build confidence, understand limits, and use tools more effectively in everyday work.
How I work
Start with the workflow, then fit the tools to it.
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Map the work
We identify repetitive, slow, or cognitively heavy tasks where AI could reduce effort or improve consistency.
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Test deliberately
I help design small, practical experiments around real tasks rather than vague demos disconnected from day-to-day work.
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Embed and refine
The goal is to create usable practices, guidance, and operating habits that a team can sustain after the pilot period.
Engagements
Trying to figure out where AI can actually help your team?
I can help assess opportunities, design sensible adoption steps, and focus the work on measurable improvements rather than novelty.