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Work in practice

Building practical AI capability through real work

Teams are already experimenting with tools like ChatGPT and Claude, but businesses need a shared way to turn that experimentation into useful capability, better work and clear priorities.

Industry
AI capability and organisational learning
Case study version

The situation

The challenge

Individual use can be uneven and disconnected. Leaders may see many AI possibilities without knowing where the value is, what people need to learn, or what guardrails and ownership need to be in place.

The response

What we did

Use readiness conversations, team surveys, applied workshops, role-based learning and practical training modules to understand current use, surface real business opportunities, build judgement and capability, and choose one priority to take forward.

The learning model connects training to real work rather than generic prompting. Capability, governance and implementation can then build from the same organisational context instead of becoming separate initiatives.

The shift

What changed or became possible

  1. 01

    A clearer shared view of how AI is already being used

  2. 02

    Practical capability built around real roles and business work

  3. 03

    A priority opportunity identified with next steps for capability, governance or implementation

Your business

What could AI change in your business?

Start with a conversation. We will look at what is happening now, where AI could create real value and what the best first move might be.

Start a conversation