#3 AI Consulting

The Challenge

Most AI work stalls at the question stage. The reality is the data is scattered, the process is manual, the business case is unclear and nobody can point to the first step. The board asks for a plan, management asks for a number, and a vendor you speak to answers whatever you want to hear.

The trouble is that an AI problem is rarely one problem. It is a data-readiness problem, a process problem, an ownership problem and a change problem. Solve the wrong one and the ROI potential is gone: you buy a platform nobody adopts, or you automate a process you should have redesigned.

And there is one gap nobody can fill. Might be you're too close to the problem to see it clearly, and every vendor you speak to has a product to sell you before they have understood it.

The Solution

Start from the problem, not from a tool or a method.

Understand the situation, the constraints, the data reality and organisational tacit knowledge. Create mutual understanding of the problem and what influences the outcome. Design an experiment, or MVP that solves the problem. There is always more than one way to solve a problem, with different trade-offs. Execute with clear accountabliity. Without actions and measurement there's no controlled progress.

Rarely it is possible, let alone productive, to figure out things alone.

Kickstart focus on the problem

The "lense" and prescription, possible outcomes for the company

• Opportunity assessment: a prioritized mapping of AI use cases across the company.
• AI readiness and data audit: what data you hold, where it lives, and what it can be used for.
• Business case and investment plan: costs, benefits and ROI written out.
• Target operating model: ownership, decision rights and the governance that keeps AI use compliant.
• Vendor selection: evaluation criteria, an objective shortlist and an independent recommendation.
• Execution plan: a sequenced roadmap with owners, dependencies and milestones.
• First solutions: actual productivity increasing solutions.
• Handover: documentation, training and internal capability, so the work keeps running.

This is for

• SMEs with a specific, AI or data problem, a regulatory constraint or a project that has stalled.
• Boards and executive teams who need an independent view on specific AI investment or use case.
• Business units needing an outside expert, e.g. use cases, opportunity sizing, AI operating model.
• Companies standing between "we should do something" and "we know exactly what, and how".