Strategy frame
Where AI compounds advantage in this business vs. where it's noise.
AI business consulting that joins strategy, build, and governance — for leadership teams ready to compound advantage from AI. Serving owners and leadership teams across Ohio.
AI is now a business question, not an IT question. Pricing, packaging, hiring, capacity, customer experience, and competitive positioning are all shifting. Across Ohio leadership teams need to make those calls deliberately — not by reaction.
My AI business consulting work joins strategy with build. We frame the bets (where AI compounds advantage, where it's a feature, where it's a distraction), score and pick the high-leverage use cases, ship production builds, and install the governance to manage cost, risk, and quality.
Common engagement shapes: AI strategy + roadmap (4–6 weeks), production builds of 2–3 priority use cases (8–16 weeks), and ongoing AI advisory retainer with quarterly bet reviews.
Operator background, not a deck-only consultant. Every credibility marker below is something I've actually built or run — not theory.
Where AI compounds advantage in this business vs. where it's noise.
Every candidate scored on leverage, cost, risk, and time to value.
Two or three to ship in the next 90 days. Cut the rest.
Production builds against real data and real workflows.
Evals, cost tracking, quality monitoring, ownership.
Quarterly bet review. Double down, adjust, or kill.
Anonymized examples of engagements that fit this scope. Names and identifying details withheld.
SaaS leadership repositioned around AI-augmented workflows: pricing, packaging, and GTM messaging. Net new revenue grew faster than the underlying motion would have predicted.
Mid-market company installed AI literacy across leadership and key teams. Within a quarter, internal AI use was driving measurable hour savings across multiple functions.
Operator under pressure from AI-native competitor. Identified the moats, reinforced them with AI-augmented customer experience improvements, and held share.
Use case selection and production builds.
AI-powered workflow automation.
AI bets in the context of the broader strategy.
Operations leadership including AI program ownership.
Reporting and metrics for AI investment.
Process work upstream of any AI rollout.
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