Using AI on the business as well as in it: understanding where artificial intelligence can improve the system of work itself.
Searching for AI use cases starts with the technology. A better approach is to find valuable work that causes problems, understand what is really happening, and use AI to help investigate before deciding what should change.
Read articleOnce you understand how work actually happens, do not simply allocate the existing tasks between people and technology. Redesign from the outcome, decide what work is genuinely necessary, and only then determine where people, conventional automation and AI belong.
Read articleAI can remove visible friction while making unnecessary or poorly designed work less likely to be questioned.
Automation works best when it follows a clear understanding of how work really happens, including the judgement, exceptions and friction hidden by the formal process.
Read articleGenerative AI can expose gaps in organisational understanding by asking what must be investigated before improvements are recommended.
AI analyses representations of organisational work, so evidence, interpretation, hypotheses and recommendations must remain distinct.
A practical way to investigate one recurring piece of work before deciding whether AI or another intervention is appropriate.
AI capability must be separated from the authority an organisation deliberately delegates, including clear escalation boundaries.
Meaningful human oversight depends on retaining independent judgement, not merely placing an approval checkpoint in a workflow.
Access to organisational systems cannot capture all the history, context and situated judgement needed for consequential work.
As organisations begin delegating work to artificial agents, managing the technology is no longer enough. Someone still needs to manage the work, the authority given to the agent and the consequences of its actions.
Read articleDelegating work to AI still requires domain, managerial and technical supervision focused on the organisational outcome.
AI can do more than perform existing work. It can help organisations examine how work actually happens before deciding what should be changed or automated.
Read articleA practical prompt for using generative AI to investigate how a piece of organisational work actually operates before deciding how it should be improved.
Read articlePrioritising valuable organisational problems keeps the intervention space wider than a portfolio framed around AI use cases.
Starting with the work allows AI to emerge as an appropriate conclusion of diagnosis rather than a predetermined solution.
When organisational evidence is incomplete, AI should help design the next investigation instead of supplying a plausible guess.
Using AI tools effectively is different from knowing what organisational work is worth improving and whether change made it better.
A first conversation is free, and usually enough to tell you whether there's a leverage point worth pulling.