1. Train senior leaders and employees
- Deliver practical, business-oriented sessions on Generative AI, LLMs, assistants and agents.
- Explain where AI creates value, where it does not, and how to think about human-in-the-loop workflows.
- Cover agent design, knowledge/context, data, tools, limitations, prompting/instruction design and Responsible AI.
- Use examples that are relevant to business functions rather than purely technical demonstrations.
2. Shape real business opportunities
- Work 1:1 or in small groups with ELT members and employees.
- Understand the current process, pain points, users, value opportunity and success criteria.
- Assess whether AI is appropriate and where it can meaningfully improve the outcome.
- Define the assistant/agent concept: purpose, workflow, outputs, knowledge/data, human involvement and guardrails.
3. Help create first prototypes
- Support participants in turning shaped concepts into working prototypes using approved enterprise AI tools.
- Help structure instructions, knowledge, workflow, inputs/outputs, testing and iteration.
- Identify when additional technical, security or Responsible AI expertise is required.
4. Build internal capability
- Create reusable examples, templates and practical learning materials.
- Coach internal AI Senseis / champions and help them become more self-sufficient.
- Run office hours, clinics or group shaping sessions.
- Help successful use cases become reusable patterns for the wider organization.
