Enterprise AI01
Find the answer. Keep the permissions.
Enterprise search across scattered sources, with access rules and source citations built in.
Enterprise AI · Technology · Commercial judgment
Your enterprise constraints
decide your AI strategy.
I help enterprises find what limits performance and design AI around the systems they already run. I also help consulting firms connect what they sell with what they deliver.
Selected work
What that looks like in practice.
Enterprise workflow02
Redesign onboarding around what you own.
A connected customer workflow using the systems already in place.
Consulting firms03
Connect the sale to the work that follows.
Clear ownership of relationships, forecasts and margin across sales and delivery.
How I work
Six decisions.
One clear outcome.
AI builds the fact base.
People make the call.
AI in every step.
Automation only in the last.
01Outcome & BaselineAgree what needs to change and measure the baseline.
Under the hood · Stage 01 / 06
AIReads approved systems and data, interprets the conversations and assembles a sourced fact base.
PeopleSet the outcomes, review the sources and validate the baseline.
OutputThe agreed outcomes, grounded in a validated baseline, source data, success measures and accountable owners.
02ConstraintsFind what limits progress and what it costs.
Under the hood · Stage 02 / 06
AIIdentifies constraints across the documented process and quantifies their impact from supplied data or clearly marked estimates.
PeopleValidate each constraint, challenge inferred data and confirm its effect on the outcome.
OutputValidated constraints and their quantifiable impact on enterprise top line or bottom line.
03DirectionAgree where AI belongs and who stays in control.
Under the hood · Stage 03 / 06
AICompares operating models, native capabilities and ecosystem options against the fact base and constraints.
PeopleAgree the extent of AI adoption and who will administer it.
OutputThe agreed extent of AI adoption, permitted technologies, data strategy and human authority.
04Transformation JourneyPrioritize the workflows worth changing.
Under the hood · Stage 04 / 06
AIBrings outcomes, the fact base, constraints and the agreed scope together to propose workflows, quantify value and surface dependencies.
PeopleBusiness judges top line, bottom line and team uptake. Technologists judge development and re-architecture. Leadership signs off.
OutputA prioritized sequence of use cases, linked to constraints and outcomes, with dependencies and ownership agreed.
05ArchitectureDesign the system and test it with the business.
Under the hood · Stage 05 / 06
AIHelps select a stack against the fact base and builds demonstrations of the proposed workflows.
PeopleTechnical stakeholders validate the design. Business stakeholders validate the change through demos.
OutputAn AI architecture validated by technical and business stakeholders.
06Return & RolloutCost the work, build in stages and measure.
Under the hood · Stage 06 / 06
AIHelps assemble the cost models and compares measured results with the outcome contract.
PeopleBenefit owners approve assumptions, review results and decide what proceeds.
OutputA fully costed transformation journey with measurable ROI against the targeted enterprise outcomes.
Every output carries its source.
Each decision should be traceable to the evidence and the people behind it.
What informs this approach
Start with the constraint. Eli Goldratt’s Theory of Constraints starts from the goal, finds the limit that matters, and revisits it when the system changes.
Use AI before automation. AI helps build the fact base, question requirements and simplify work. Automation comes after the workflow is clear.
“Automation applied to an inefficient operation will magnify the inefficiency.”
Bill Gates, The Road Ahead (1995).
From Lift Off
The thinking behind the work.
Start a conversation
Bring me one constraint.
I’ll tell you what I’d do first.