LATYNEX
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What actually happens during an AI implementation project, in order

LATYNEX Digital · Published 23 Sept 2026

The real sequence, not a marketing timeline — no fixed week counts, the honest order of the work.

See AI Implementation for Business

Direct answer

AI Implementation for Business follows the same five-stage sequence as every LATYNEX implementation engagement, applied to AI specifically: inspect what's already in use, understand the gaps, agree a scoped plan in writing, configure inside your own accounts, then hand off. There's no fixed week count published here — a one-workspace entry-package project and a multi-team rollout move through the same stages at genuinely different paces, and promising a number without knowing the scope would be a guess.

1. Inspect what's already happening

What AI tools the team already uses — often personal ChatGPT or Claude accounts nobody coordinated — read-only where possible, before anyone proposes a change.

2. Understand the current setup

What's genuinely working, what's duplicated across tools, what has no owner, and where client or company data might already be going into a personal AI account without anyone deciding that was okay. Delivered in writing, in plain language.

3. Implementation plan, agreed before anything changes

Which tools get configured, what usage rules apply, which 2–3 workflows get built first, and what's deliberately left out of this phase. Scope and price are agreed in writing before configuration starts — nothing moves before you approve it.

4. Configure inside your own accounts

Workspace setup, roles, company instructions and the agreed workflows, built through access you grant and can withdraw. Anything touching customer data or money waits for explicit approval before it goes live.

5. Handoff

Written documentation of what was configured and why, an onboarding session for the team, and a clear line on what's yours to run from here — LATYNEX doesn't hold the keys to your own AI workspace.

What changes the pace, honestly

How many tools are already in informal use, how many teams need coordinating, whether a written usage policy needs building alongside the setup, and how much of the team needs onboarding at once. None of that is knowable before the inspect stage, which is exactly why this page doesn't promise a number.

Questions

How many weeks does this take?+

It depends on scope — genuinely knowable only after the inspect stage. A single-workspace entry-package project and a multi-team rollout move at different paces through the same five stages.

Do we need to decide on an AI platform before starting?+

No — that's part of what gets confirmed during inspect and planning, not a prerequisite for starting the conversation.

Can this run alongside AI Governance & Usage Policy work?+

Yes, and it often does — but they're scoped as related, separate pieces of work, not bundled silently into one timeline.

What happens if the inspect stage finds we don't actually need this?+

We say so. Inspect is genuinely read-only and precedes any recommendation — including the recommendation that a smaller or different scope fits better.

See AI Implementation for Business
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