Your company already pays for AI. Most of your team doesn't use it, or uses it once, badly, and stops. We fix that.
Liorant trains your people to do real work with the AI tools you already licence, measures the change in hours saved, and leaves your team able to keep going after we leave. Not a webinar. A working capability, built on your documents, your workflows, and the principles that stay true when the tools change.
Companies buy licences, run one all-hands demo, and call it enablement. Adoption stalls within weeks. The reason is consistent: generic training teaches the buttons of a specific tool, not the judgement to use AI on the work that actually fills your team's day.
The barriers firms name most — lack of qualified people, unclear ROI, poor readiness — are training problems before they are technology problems. "Have a licence" and "get value" are not the same thing.
The gap isn't access to AI. It's the ability to use it well, on your own material, repeatedly, without us in the room.
See how Liorant delivers a working AI system in 4 weeks →Three things separate our enablement from a vendor webinar.
Every session runs on your documents, processes, and actual bottlenecks. Legal drafts against your clause library. Marketing briefs against real campaigns. Ops automates the process that eats their week. Never generic demos.
Prompts change, interfaces get redesigned, models get replaced. How to decompose a task, judge an output, decide when to automate, and keep a human accountable does not. We teach the part that survives every product update.
Enablement that can't show a before-and-after is theatre. We time your team on real tasks before and after training, and report the difference in hours and euros — not attendance sheets or satisfaction scores.
Liorant runs enablement as instructional design, not a presenter winging it — a structured curriculum with role-specific tracks, a reusable prompt library in your own voice, and office hours that turn early friction into habit. The difference between a team that watched a demo and a team that changed how it works.
Training is the fastest way to get started with an AI strategy, and every format uses the same shape.
We learn your team's roles, the tools you already licence, and where the real time goes. No slides, no pitch.
Scoped, fixed, and built on your material. We run role-based sessions, install a working prompt library, and coach your people through their first real tasks.
A before/after measurement of time on real tasks, plus a scored backlog of the highest-value automation opportunities we surfaced — priced by impact ÷ effort.
Teams start at different places. Enablement meets them where they are and moves them up. Every rung runs on your real work and reports the same way. You don't have to climb the whole ladder.
Liorant is not a reseller and takes no platform's side. We train your team on whatever you already licence — and if you run more than one, we teach your team to choose the right tool for each task instead of forcing everything through one vendor.
This matters commercially. Vendor-run training optimises for that vendor's product and its renewal. Ours optimises for your team's output. Provider-agnostic isn't a neutrality stance — it's what keeps the training valuable after the contract you signed this year.
Won't this be obsolete in six months? For tool-specific training, yes — and that's exactly what we don't sell. We teach the principles of the discipline, because we work in these systems daily and understand which layer actually lasts.
Every one of those is a principle, not a feature. A team that owns them re-derives the specifics for whatever tool arrives next — the way someone who understands accounting doesn't panic when the software updates. The tools underneath will change; because your team understands the principles, the capability stays.
The first engagement produces reusable assets — a role-based curriculum, your own prompt library, and a trained champion — that we replicate across departments at a fraction of the first team's effort. Adding a team is a new track on an existing spine, not a project from zero.
Every Liorant engagement reports in the same language, so a client who buys two services recognises one measurement system. We report the change in real-task time and adoption rate — not attendance, satisfaction scores, or certificates.
If you licence more than one, we teach your team to route each task to the right tool. If you licence none yet, discovery includes an honest "do less / licence smart" recommendation before you spend.
Enablement includes teaching your team to use AI within the rules that apply to you. Responsible use is a competency we teach, not a disclaimer we attach.
We train staff on acceptable-use boundaries, human-oversight obligations, and how to recognise a higher-risk use before it becomes a liability. Obligations phase in through 2026–2027; your team should know them, not just your legal owner.
Enablement reflects the national AI framework and its responsible-use expectations, so teams operating there work within the local standard from day one.
For US-facing teams via partners, training maps to the NIST AI Risk Management Framework's govern / map / measure / manage functions.
No. Every session runs on your own documents and workflows, and your team practises on their real tasks with us coaching. You leave with a working prompt library and a measured change in hours — not notes from a talk.
Yes. Liorant is provider-agnostic. We train on Microsoft Copilot, Google Gemini, Anthropic's Claude, and the no-code layer — and, more usefully, on how to choose the right one for each task instead of forcing everything through a single vendor.
The tool-specific parts date quickly, which is why we don't build the training around them. We teach the principles of working with AI — task decomposition, context, verification, human accountability, measurement — which stay true across every product update. Your team re-derives the specifics for whatever comes next.
We time your team on real tasks before and after, and report the difference in hours saved per week and in euros, alongside actual adoption rates. If the numbers don't move, the training didn't work — and we'll tell you.
Yes, and it's designed to. The first engagement produces a reusable curriculum, a prompt-library method, and a trained champion. Each additional team is a track on that spine, so rollout gets faster and cheaper — typically 30–40% less delivery effort by the third team — while quality holds.
You keep the adoption report and a scored backlog of the highest-value automation opportunities we found inside your workflows. You can act on them with anyone. If you want the top opportunity built into a working system, it becomes the starting point for a Rapid AI Activation — no second discovery, no rework.