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AI IMPLEMENTATION · SME ROADMAP

AI Implementation for SMEs: A Roadmap That Ends With Working Systems

I turn a business need into an AI solution connected to your tools and usable by your team. Scope, timeline and support are defined around your processes, data and internal capabilities.

Book a scoping call See the process

The failure modes I see constantly

  • ✕

    AI pilot ran well in the sandbox. Died at the point of integration with the real system. Nobody owned the handoff.

  • ✕

    Vendor sold a solution before understanding the problem. You're six months in and the use case doesn't fit your actual workflow.

  • ✕

    Implementation finished. Vendor left. Your team doesn't know how to use it, maintain it, or extend it.

  • ✕

    AI budget consumed. Board wants to see results. The slide says productivity up 12% — nobody can explain how that was measured.

From business need to everyday use

  1. 01

    Understand and scope

    Select the processes worth improving. Agree priorities, owners and acceptance criteria before building.

  2. 02

    Choose the technology

    Evaluate models, APIs, and infrastructure against your actual constraints: budget, data residency, security, and team skill level.

  3. 03

    Build and test

    Connect the solution to your systems and test it with representative work. Your team helps review quality, permissions and behaviour before a controlled rollout.

  4. 04

    Validate and measure

    Compare results with the agreed baseline and acceptance criteria. Document issues and resolve them within the agreed scope before release.

  5. 05

    Train and transfer

    Deliver documentation, training and operating procedures. Agree responsibilities and any ongoing support your team needs.

Proof-of-work

  • AI-native B2B SaaS product implemented from zero to production, with AI built into its core processes.

  • AI implementation for a legaltech platform: booking agent, document automation and client portal in production.

  • Online training school: programmes launched with AI-assisted content, payment automation and student management.

Scope and proposal

The proposal depends on your company size, the processes and users involved, data readiness, integrations and support needs. We agree the deliverables, milestones, responsibilities and commercial terms before building. Licences and operating costs are identified separately.

FAQ

What sectors do you work with?
SaaS B2B, legal and consulting firms, fintech, manufacturing, and e-commerce. The common thread is mid-market companies with complex internal processes.
Do we need an internal tech team?
Helpful but not required. I've implemented AI for companies with zero technical staff. The handoff approach adjusts to your team's capability.
How do you define the scope and proposal?
I review the business objective, processes, data, integrations and team capacity with you. The proposal specifies deliverables, acceptance criteria, timeline and commercial terms. Any change of scope is agreed before proceeding.
What if the implementation doesn't work?
We define acceptance criteria before building. If the solution does not meet them, we review the cause and agree the corrections or scope changes needed before release.
Can you implement AI without replacing existing systems?
Almost always. AI layers sit on top of existing infrastructure. Rip-and-replace is rarely the right answer — and never the first one.

Go deeper

Let’s put AI to work in your business.

Tell me what you want to improve and how your team works today. We will identify a useful starting point.

Book a scoping call