Most enterprises can run a prompt. Almost none can run an agent. Our enterprise AI training doesn’t stop at one team — it works across the whole organisation, engineering to leadership, until your systems stop answering and start acting.
There is a difference between buying a course and bringing in people who have measured the gap first. Our enterprise AI training is the second.
Before we train anyone, we run an assessment of where your organisation stands across eight pillars, from strategy and data readiness to governance and agentic capability.
Our Maturity Framework →Role, level, tooling and timeline decide what gets taught, per function and per business unit. Modules a group does not need are dropped, and every exercise runs on your own codebase, backlog or process, never a sandbox.
What success means is agreed before day one and measured against the same eight pillars we opened with. Checkpoint scores, capstone results and a readiness map per cohort, rolled up for leadership when more than one runs.
These are the eight pillars we score in the AI Delta Maturity Framework™ assessment, and the weakest ones decide where the training starts.
AI sits on the board agenda. Accountability for the outcome is rarely assigned to a single owner.
You are ready whenOne named person signs off the AI roadmap and the budget behind it.
Start with Gen AI Executive LeadershipPeople complete the training. The process around them stays the same, so the old way remains the fastest way.
You are ready whenThe new way is still how the team works in week six.
Start with Gen AI FoundationsUse cases are approved before the data behind them is ready. Ownership, quality and access are settled late, and timelines slip there.
You are ready whenRetrieval runs on your own data without someone cleaning it by hand first.
Start with Gen AI ArchitecturePilots prove the technology. Fewer of them are handed to an owner with a budget and a date to become standard practice.
You are ready whenA pilot has an owner, a budget line and a date it becomes the default.
Start with Mastering Gen AI in ProductAccess is granted broadly. Daily use concentrates in a few teams while the rest of the organisation stays at first contact.
You are ready whenEvery function has people using it daily, not one enthusiastic team.
Start with AI Productivity & WorkflowInvestment is visible in the budget. Return is harder to attribute, and the reporting line between the two is usually missing.
You are ready whenOne number answers what AI returned this year and finance agrees with it.
Start with Product ManagementAn AI system makes a decision that reaches a customer. The approval path and the escalation owner are often defined after the fact.
You are ready whenEvery agent has an owner, a boundary and a log that someone reads.
Start with AI Governance & SDLAgentic AI appears on most roadmaps. Few organisations have agents in production that customers or employees depend on.
You are ready whenAgents are in production and people depend on them, not on a roadmap.
Start with Agentic EngineeringAgentic AI does not land through one team. Enterprise AI training works when engineering, product and leadership close their own gaps together.
From the first LLM call to multi-agent systems running in production, in the language the team already uses.
What agents make possible, what they cost, and how the week around them gets redesigned.
Strategy, governance and the questions a board asks before the first incident does.
On site when the team sits together, live online when it does not. Same exercises and same assessment either way.
Every cohort is closed. Everyone in the session works on the same systems and the same constraints, so the examples are yours and nothing said in the room leaves it.
Delivered by people who have put these systems into production and hit the walls your teams are about to hit.
Participants earn the same verified certificate as any other route, which is what makes the training worth their evenings as well as your budget.
Strategic advisory and fractional AI leadership for organisations that want the expertise in the decision, not only in the training room.
Training runs on your own code and processes under NDA. Nothing you share leaves the engagement, and nothing is retained after it ends.
It starts with the eight-pillar assessment rather than a catalogue. Cohorts are private to your people, taught live by practitioners who have put agentic systems into production, and every exercise runs on your own code and processes. Several cohorts run in parallel, one per function or business unit, and each one closes with a capability report measured against the same pillars.
Deployment is usually the strongest score, with real pilots and real results. Data and infrastructure readiness is usually the weakest. The pilot works, and the foundation to scale it does not exist yet. That missing foundation is where enterprise AI training starts.
It is the gap enterprises can show the least for, with almost no proof of it working at scale yet. The teams that are ahead already run dozens of agents, while most are still at two or three. For a plain definition, see MIT Sloan’s guide to agentic AI.
Wherever your assessment comes back weakest. The track breakdown above maps each pillar to the programs that close it, and cohorts are sequenced from there.
Enterprise AI training runs on three tracks: engineering, product and operations, and leadership. One group takes one program, or the organisation runs a sequence across roles and units.
Built and quoted per engagement, not per seat. What moves the number is the size of the cohorts, how many run in parallel, how many weeks the sequence spans, and whether delivery is on site or live online. The eight-pillar assessment sets the scope before pricing is discussed.
No. Only the engineering track requires it. The product, operations and leadership programs require no coding at all.
Yes. On-site enterprise AI training travels, and live online sessions run to the group's working hours.
Yes. We roll out enterprise AI training in parallel cohorts, split by function or business unit, on one shared calendar with a single point of contact.
Live sessions, closed to your people, with every exercise on your own systems. Cohorts run part-time across the calendar or as one intensive block, and every enterprise AI training cohort closes with a capstone and a credential.
Only what the hands-on exercises need, and only under NDA. Nothing is retained after the engagement ends.
Which functions have to move first, and what do they need to be able to do? We come back with the sequence, the cohorts and your enterprise AI training plan.