ASK AYAN AI
A place to begin
the next question.
Curated perspectives; live AI assistant planned. Explore four starting points and follow the sources into a deeper conversation.
EXPLORE A QUESTION
How should my company approach AI?
Begin with a business task or decision worth improving. Describe the current baseline, the people affected and what a useful change would look like. Then examine readiness: knowledge, systems, ownership and the ability to adopt a new way of working.
Choose a bounded starting point with an owner and a way to evaluate the result. The transformation approach in the AI Lab provides a sequence for structuring that discussion.
READ FURTHER / AI Lab: transformation approach ↗ · From CTO to CTAIO ↗
When should enterprises consider private LLMs?
Treat the deployment model as a requirements decision. Clarify which information the system will use, the access boundaries it must respect and the operational capabilities available to support it.
Compare the options against those requirements, including quality, latency, total cost and responsibility for running the system. Private deployment alone does not answer every question about knowledge quality, governance or usefulness.
READ FURTHER / The Enterprise AI Stack Explained ↗ · NIST AI Risk Management Framework ↗
What makes a good AI strategy?
A useful strategy connects a business priority to a set of choices: what to pursue, what to defer, who owns the work and how progress will be assessed. It should make the next decision easier.
Keep technology choices connected to the workflow and the organisation adopting them. The point is a capability the business can use and improve, with evidence to guide further investment.
READ FURTHER / AI Lab: transformation approach ↗ · Explore the expertise ↗
How might agents change SaaS?
Agents introduce the possibility of software taking a sequence of actions toward a goal, rather than waiting for a person to direct each step. The design questions therefore extend to permissions, completion evidence and recovery.
Anthropic’s distinction between predictable workflows and flexible agents is a useful starting point. A product team can ask which user tasks justify that flexibility, and which are better served by an explicit process.
READ FURTHER / Agentic AI and software development ↗ · Building effective agents ↗
ABOUT THIS EXPERIENCE
Useful sources.
Clear boundaries.
This page is a curated knowledge explorer. The answers are editorial starting points with links to further reading; they are not generated in response to a live conversation.
A future assistant is planned around approved published material, with source links and a clear boundary between documented perspectives and questions that need a direct conversation.
For a question about your own organisation, share the context directly. The details of the business, the people and the current systems usually matter.
START A CONVERSATION
Some questions deserve
a direct conversation.
Connect with the context behind the question.
