Direction and spending
Clarify priorities, set experiment budgets and approval thresholds, and agree when to continue, stop, or expand a use case. Judge the result against the full cost, including software, staff time, and review.
AI STRATEGY, GOVERNANCE & ENABLEMENT
Put structure
around AI.
AI adoption involves more than choosing tools. Your team needs time and support to explore, a way to decide what’s worth pursuing, and clear expectations for anything the business comes to rely on.
I help you establish a practical approach to spending, tool access, company ownership, data quality, testing, and handover, so useful experiments can become tools the business can use and maintain.
When this is useful.
- People are using AI, but approaches and expectations vary across the team.
- You want to encourage experimentation without leaving spending open-ended.
- Employees are building tools, and you need clarity on ownership, access, and maintenance.
- You need a consistent approach to business data, checking outputs, and approving consequential actions.
- You want a plan for adoption that goes further than a list of tools or possible projects.
What we could put in place.
- A review of existing AI tools, uses, and responsibilities
- A prioritized adoption plan
- Spending guidelines and approval thresholds
- Plain-English guidance on tools, data handling, and human review
- A checklist for moving a prototype into business use
- Ownership, documentation, and handover expectations
- A team enablement and review plan
We agree the deliverables to suit the business. Few engagements need all of these, and the shape depends on how far along the team already is.
WHERE STRUCTURE HELPS
Four areas
we work through.
The central idea: give people room to experiment, with clear expectations for anything the business comes to rely on.
People and experimentation
Give people practical guidance, chances to learn, and a way to share what works. Establish who supports experiments and how a promising idea moves beyond one person’s desk.
Ownership and maintainability
Set expectations for company-controlled accounts, code, access, documentation, and handover. Make sure a useful tool can be understood and maintained by someone other than the person who built it.
Data and reliability
Identify appropriate data sources, assign responsibility for keeping them current, and agree how outputs get checked. Set testing and approval expectations in proportion to how the tool will be used.
FROM EXPERIMENT TO BUSINESS TOOL
Not every experiment
needs the same controls.
A personal prototype and a tool used to prepare client deliverables shouldn’t carry the same requirements. We agree what people can explore on their own, what needs review before wider use, and who takes responsibility once others depend on it.
Explore
A defined purpose, appropriate data, and an agreed budget.
Trial
Test real examples with a limited group and a named owner.
Operate
Agree access, documentation, checks, maintenance, and ongoing costs.
Finding out that an idea doesn’t work is a fair result of an experiment. The point is to notice early, keep what does work, and know when a tool has become something people depend on.
HOW THIS FITS
Distinct from a sprint,
a workshop, or a build.
An opportunity sprint identifies and tests where AI could create value in the business. This work establishes how the business experiments, spends, builds, and takes responsibility for what it comes to rely on. The two often follow each other, in either order.
Team workshops can be part of it, for hands-on practice on real tasks, and the guidance we agree gives those sessions something to build on. If the team then needs something built, a focused first build or a custom system picks up from there.
GROUNDED IN ACTUAL WORK
See what that can become.
built around the business.Entec Sales Intelligence Hub
The problem. Customer activity sat across SimPRO, Xero, and Outlook, with no single view of which accounts and inquiries needed attention.
What changed. A working hub that tracks key customers and inquiries, and prioritizes the next commercial action.
Read the story
AI Resource Hub
The problem. A team wanted to learn and keep up with AI, and the useful material was scattered across links, chats, and newsletters.
What changed. An internal resource hub with scheduled news updates.
LET’S TALK
How is your team
using AI today?
Tell me what people are already doing and where you’d like more structure. We’ll work out a sensible scope from there.