Whitepaper16 MIN READ
Choose the work before the agent
Compare agentic work with simpler alternatives, expose the dependencies behind a promising demonstration, and fund a bounded experiment with a clear decision at its end.
Category
Strategy & transformation
Deciding where agents belong, what readiness looks like, and how to sequence adoption without over-committing.
Agentic AI raises a different strategic question from earlier automation waves. The technology can act, not only recommend, so the decision is less “which model?” and more “which workflows deserve delegated action, under what supervision, with what evidence that the delegation is working?” This category covers opportunity discovery, readiness assessment, operating-model design, build-versus-buy-versus-partner choices, workforce impact and the transformation roadmap that ties these together. The emphasis is on making adoption decisions explicit and reversible where possible.
Published in this category
Whitepaper5 MIN READ
The evidence behind the go-live decision
A working paper for leaders who need to explain why an agent workflow is ready for its next release. Includes a proposed evidence-pack structure, decision table and review agenda.
Strategy & transformation6 MIN READ
Before the pilot: five questions for agent readiness
A compelling demo leaves important questions open. Use a five-dimension rubric to examine the data, authority, evidence, ownership and people behind your next agent initiative.
Strategy & transformation6 MIN READ
Stop choosing AI use cases; start defining workflows
A list of AI ideas is not an operating plan. Define the work, decisions, authority and evidence before deciding whether an agent belongs in the workflow.
Architecture & engineering7 MIN READ
An AI feature, an AI agent and an agentic system are not the same thing
Classify AI by the action path it creates, not the label on the product. The distinction determines ownership, controls, evaluation and release evidence.
Strategy & transformation6 MIN READ
How to write an RFP for agentic AI without buying a promise
Specify the workflow, evidence, responsibility and exit conditions suppliers must meet, then evaluate them through representative scenarios.
Strategy & transformation6 MIN READ
Do you need an agent centre of excellence?
A centre can concentrate scarce expertise and reusable controls, or become an approval queue detached from real work. Choose the mandate before the structure.
Strategy & transformation6 MIN READ
A quarterly watchlist for agentic AI leaders
A useful quarterly watchlist tracks changes that could alter real decisions: system authority, evidence, incidents, standards, providers and organisational readiness.
Strategy & transformation6 MIN READ
Redesigning roles around human–agent collaboration
Do not divide work into “human” and “AI” columns. Redesign tasks, decisions, authority, handoffs and learning so each role remains operable and accountable.
Strategy & transformation6 MIN READ
Why promising AI pilots become permanent experiments
A successful demonstration does not create a live service. Pilots stall when they test capability without resolving ownership, integration, economics and operating evidence.
Governance & privacy6 MIN READ
The board’s questions about AI agents should begin with authority
Boards do not need to review prompts or model scores. They need a clear account of what each agent may do, whose mandate it carries and how control is recovered.
Strategy & transformation6 MIN READ
What public-sector buyers should request from an agent supplier
Buy evidence, controllability and lifecycle obligations—not a confident demo or an unrestricted promise of autonomy.
Impact measurement6 MIN READ
The hidden total cost of operating an AI agent
Model usage is one line in a wider cost stack that includes integration, evaluation, control, human work, incidents, change and exit.
Strategy & transformation6 MIN READ
The no-agent test: when ordinary automation is the better choice
Agents earn their complexity only when a workflow needs bounded adaptation. A disciplined no-agent test can reveal when rules, search or ordinary software is safer and cheaper.
Strategy & transformation6 MIN READ
A transformation roadmap built around decisions, not technology releases
Model launches are not transformation milestones. Organize the roadmap around workflow, evidence, authority, operating and expansion decisions.
Strategy & transformation6 MIN READ
Turning an AI workshop into a decision artefact
Design an AI workshop backwards from a named decision, then capture evidence, assumptions, disagreements, owners and triggers in an artefact that survives the meeting.
Strategy & transformation6 MIN READ
Where AI agents fit in finance operations—and where they should stop
Finance agents can prepare, reconcile and investigate, but posting, paying and attesting require deliberately separated authority.
Impact measurement6 MIN READ
What conference participation proves—and what it does not
Attendance, speaking and sponsorship are evidence of activity; useful conference claims require separate measures of learning, relationships, follow-through and resulting decisions.
Strategy & transformation6 MIN READ
AI readiness is local to the workflow
Enterprise readiness scores hide the conditions that make one workflow viable and another reckless. Assess readiness where data, authority, people and operations meet.
Strategy & transformation6 MIN READ
A responsible-autonomy workshop for one real workflow
Responsible autonomy becomes concrete when a cross-functional team maps one workflow’s actions, consequences, evidence and intervention choices.
Strategy & transformation6 MIN READ
How to qualify an AI technology partner before designing a joint offer
Qualify a technology partner through evidence of fit, controls, delivery behaviour and commercial alignment before combining brands or promising a joint service.
Strategy & transformation6 MIN READ
Build, buy or partner for an AI agent? Ask these questions first
Choose a sourcing path by separating the workflow advantage you must own from the capabilities you can responsibly obtain elsewhere.
Evaluation & assurance6 MIN READ
What makes an AI assurance partnership useful?
A useful assurance partner improves the quality of a specific AI decision while leaving ownership, evidence and operational accountability with the organisation.
Evaluation & assurance6 MIN READ
Portable evaluations are protection against platform lock-in
Keep workflow cases, graders and decision rules separate from the platform so alternatives can be compared without rebuilding the standard of proof.
Strategy & transformation6 MIN READ
Vendor-neutral does not mean anti-vendor
Neutral advice compares dependencies and evidence against the client's decision; it does not pretend every platform is interchangeable or that vendors add no value.
Strategy & transformation6 MIN READ
What a polished agent demo does not tell you
A demonstration shows one possible path. A buying decision needs evidence about representative work, failure, authority, recovery and operation.
Governance & privacy6 MIN READ
The responsibility map every AI partnership needs
A useful responsibility map connects each AI decision and artefact to a named accountable owner, a performing role, required contributors and evidence of completion.
Strategy & transformation6 MIN READ
How to prioritise an enterprise portfolio of agent opportunities
Rank agent opportunities by decision value, workflow evidence, feasibility, consequence and reuse—not by enthusiasm, executive volume or demo polish.
Strategy & transformation6 MIN READ
Who owns an AI agent after launch?
Live agents cut across product, operations, risk and technology. One accountable service owner needs explicit decision rights supported by named control owners.
Strategy & transformation6 MIN READ
Adoption is part of agent reliability
An agent is not reliable if people avoid it, over-trust it or route around its controls. Adoption evidence belongs beside technical performance evidence.
Know what your agents will do before you let them do it.
Bring one agent workflow and the decision in front of you. Gaurav Tiwari replies personally within 1 working day.