AI training, consulting or implementation: what do you need?

Training: build capability

Useful when people have access to AI tools but lack a repeatable way to use them. Look for practice on relevant tasks, feedback and outputs that can be reused. Assess progress through a practical task, not attendance alone.

Consulting: clarify a decision

Useful when you need to prioritise opportunities, assess feasibility or define a roadmap. Ask what decisions the engagement will enable and which evidence supports them. A presentation without owners or next steps leaves the adoption problem unresolved.

Implementation: create an operating workflow

Useful when inputs, outputs and acceptance criteria can be defined. Agree the connected systems, tests, human review and handover. Success is a process that works under agreed conditions, rather than a convincing demonstration.

Combine them deliberately

A team might first identify a use case, then learn how to review AI output while a pilot is built. Keep responsibilities clear and measure both team adoption and system performance. Choose the smallest engagement that addresses your current constraint.

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