Practical thinking on enterprise AI adoption, from the operators building A³ and the specialists working alongside enterprise teams.
We write about the decisions enterprises are making now: why pilots stall, how teams evaluate AI partners, what capability actually looks like, and what changes when AI moves from demo to production.
The stallWhy enterprise AI pilots fail, and what production actually requires
The model was never the constraint. Seven forces hold the gap between a working demo and a department that runs on it — and a diagnostic clears none of them.
The stallThe demo is not the hard part
Every stalled AI pilot dies in the same place — the handoff from “it works” to “we run on it.” Here's what that gap actually is.
The stallThe AI pilot-to-production checklist
Most readiness checklists test the model. The model is rarely what fails. Six gates that test the organisation instead — each with a pass condition you can answer today.
The stallAI proof of concept vs proof of value
A POC answers whether the software can. A PoV answers whether it's worth it. Most enterprises run the first and report it as the second — and pay for that at budget review.
The stallHow to kill a stalled AI pilot without losing the budget
The real fear isn't admitting the pilot failed. It's that killing the pilot reads as killing the mandate. Here's how to separate the two.
Vendor selectionHow to choose an enterprise AI vendor without an RFP
The standard process costs a year and selects for proposal-writing rather than delivery. Here's what actually predicts whether a partner ships — and how to test it in one session.
Vendor selectionNine red flags in an AI vendor demo
Most of what separates a real capability from a rehearsed one is visible inside twenty minutes, if you know which question exposes each.
Vendor selectionAI vendor evaluation criteria: the twelve questions that matter
Generic software criteria fail on AI vendors, because the output is probabilistic and the value sits in the workflow rather than the licence. Here's the scorecard that replaces them.
Vendor selectionBuild, buy or partner: the enterprise AI decision
Most decision memos frame this as two options. The third is the one that usually wins, and it's the one nobody models properly.
The mandateYour first 90 days with an enterprise AI mandate
You have a title, a board expectation and no map. Here's the sequence that produces a defensible win instead of an impressive strategy deck.
The mandateAI governance that doesn't kill adoption
Two failure modes: no policy at all, or a policy so broad that nothing gets approved. The fix is governing by risk tier rather than by tool.
CapabilityWhy corporate AI training fails, and what builds capability instead
People come back with certificates and cannot apply anything to the work in front of them. The reasons are structural, and they are fixable in the brief.
CapabilityCertificates versus capability
A certificate measures exposure. Capability is measured by whether the workflow changed. Here's where certification genuinely helps — and where it quietly substitutes for the thing you were buying.
Vendor go-to-marketWhy enterprise buyers choose before your first call
Around four in five buying teams have a preferred vendor before they contact sales. For a vendor without brand recognition, that changes what outbound is for.
Vendor go-to-marketCo-selling with an adoption partner
Three partnership shapes, who carries delivery in each, and the commercial terms in plain language — including what to require before you sign.
Reading helps. Seeing the capability tested is better.
When you're ready to move from ideas to evidence, bring us the problem and we'll build the right session around it.