Make AI useful enough to adopt, and bounded enough to govern.
Generative and agentic AI create new ways to interact with enterprise knowledge, analyse business performance and coordinate tools. The commercial opportunity depends on choosing a valuable workflow and being explicit about what the system may know, recommend and do.
From opportunity to an operating design
- Prioritise use cases by decision value, evidence readiness and cost of failure.
- Define the boundary between retrieval, analysis, recommendation and action.
- Specify evaluation criteria for factual support, analytical accuracy and appropriate abstention.
- Map permissions, sensitive-data exposure, approval points and escalation paths.
- Plan monitoring, change control and ownership after launch.
AI safety and security in the business workflow
Prompt injection, excessive tool authority and disclosure of sensitive information belong in the design discussion. So do plausible but unsupported analytical claims. A useful review connects those failure modes to business consequences and identifies which controls belong in software, identity systems or human approval.
The advisory focus is enterprise AI architecture, analytical reliability and governance. Specialist security testing, independent assurance and legal assessment can be scoped with the appropriate specialists where required.
Read the leadership guide to agentic AI governance →
What progress looks like
Start with one bounded use case, an explicit evaluation set and a documented decision on whether to proceed, revise or stop. Expand autonomy only when evidence supports the next level of responsibility.
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