AI Adoption

From decision to agent in production.

Measuring maturity serves to decide, and deciding serves to build. AI Adoption is the adoption journey through which we put into operation what AI Rating and AI Assessment have validated: agents, automations and integrations on the systems the company already uses, with risk gates active from day one.

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Governed adoption

Deploying AI agents today is within reach of many providers. Delivering them while leaving behind an up-to-date systems register, escalation criteria to the human operator, audit-ready logs and an internal owner who knows how to shut them down is a different matter, and it's what we deal with.

Governance does not slow delivery down; it makes it defensible in front of a board, an enterprise client, a supervisory authority.

The four services of the adoption journey

End-to-end execution

AI Shift

We take a project from PoC to production: team setup, systems integration, go-live and post-launch support.

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Agent-based automation

AI Agents

Conversational, document, process and analytical agents, running on real processes and integrated with CRM, ERP, ticketing and email.

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Operational autonomy

AI Training

Role-based paths that put teams in the position to use agents, monitor them and stop them when needed.

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Widespread adoption

AI Culture

Change management and shared language, because a solution nobody uses inside the company produces no return.

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You enter after having measured

Adoption starts from a baseline. If you already have an AI Rating or AI Assessment we go straight to delivery, otherwise we build them first, because working on processes that were never mapped produces agents that automate a problem instead of solving it.

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Deliverables and timing

Agents live on the agreed processes

Integrations with CRM, ERP and ticketing systems

AI systems register kept up to date and risk-classified

Escalation criteria to the human operator

Technical documentation and operational runbook

Handover to the internal team, with training included

From two to six weeks for an operational agent, from four to eight for an MVP in production, depending on process complexity and integrations.

Governance from day one: every agent enters the systems register with risk classification, purpose and owner. See the AI Governance framework →

Frequently asked questions

Do we need an AI Rating before starting?

No, you need a baseline. If it's missing we build it during scoping, before writing any code.

How long before an agent goes to production?

From two to six weeks for an operational agent, depending on process complexity and required integrations.

Will we stay dependent on you after delivery?

Handover to the internal team is part of the delivery, with documentation, runbook and training. We reduce technology lock-in by choosing portable architectures and keeping the company owner of data and configurations.

How does this connect to the EU AI Act?

Every system we deliver enters the register with risk classification, purpose and owner. We run gap analysis and alignment; certification is issued by a third-party body.