Services - Introducing AI tooling in the enterprise

You bought the AI tools — and adoption still isn't happening

Procurement stalled for months while legal, security and data protection each asked their own questions and nobody owned the answer. When the licences finally arrived, developers and business units pulled in different directions: the engineers wanted deep IDE integration, the product owners wanted something they could use without touching a repository, and no single rollout served both. Now the seats are paid for, the invoice recurs every month, and the productivity you were promised has not materialised.

Shelfware is the most expensive kind of software: you carry the cost with none of the return, and every quarter the "AI initiative" looks more like a sunk cost than an advantage. The failure is almost never the model quality — it is the introduction. Without a clear procurement recommendation, role-based access, enablement and governance, even excellent tools sit unused or, worse, get used in ways that create data-protection and cost risks nobody is watching.

Imagine both your developers and your business units actually productive

Picture one coherent product family with the right entry point for each role, clear guardrails around cost and data, and two groups — a developer team and a product-owner circle — shipping real work with it rather than experimenting in the margins. The engineers build faster and more safely; the business units run their own research, analyses and drafts without waiting on IT.

Instead of a zoo of individually-approved tools that no one governs, you have an adopted system with measured value behind every rollout decision. When you scale to the next department, you do it on evidence — documented time savings, real adoption numbers, a procurement and governance model that already works — not on a hopeful business case.

We run the introduction end to end — this is the "tools" step

We get both audiences productive and give your organisation the guardrails around them. This engagement answers the "tools" questions: which products you buy, who gets which access, and how you procure, secure and govern them across the organisation. It is deliberately the first of two steps — AI-DLC answers how your teams build software once the tools are in place. Tools first, then method: consecutive, not competing.

Two audiences, one system

• Developers work in their usual environment — IDE or command line. They want agent mode, not just autocomplete. Goal: build faster and more safely, spec-driven rather than "prompt in, fingers crossed".
• Product owners and business units do not want to see a development environment. For them the chat-centric access is the entry point: they describe what they need and work with an agent instead of operating an IDE. Goal: run their own research, analyses, concepts, and requirements.

Both address the same system — one product family with different entry points, not a zoo of individual tools.

What you have afterwards

• A clear procurement and approval recommendation: approve the product, not individual clients
• A mapping of which access fits which role (developers and business units)
• Two enabled pilot groups working productively, spec-driven
• Cost and data-protection guardrails as a solid basis
• Measured value from the pilot as the basis for the rollout decision

Why Taimos

• AWS DevTools Hero — recognised expertise in cloud, automation, and developer tooling
• In consulting since 2013, using the tools ourselves day to day
• Independent — an honest assessment rather than a tool sale
• Both worlds — developer enablement and business-unit enablement from one source

Led by Thorsten Hoeger, who uses these tools himself every day.

Three stages

1. Assessment

• Baseline: who should use AI tooling, what expectations and reservations exist
• Audience-to-access matrix (developers and product owners / business units)
• Procurement and approval recommendation, including clarification of product names
• Cost and data-protection basis as a decision template

2. Pilot

• Guided pilot with one developer team and one product-owner circle — deliberately both
• Enablement for the spec-driven way of working, in each audience's language
• Concrete real-world use cases from both groups, implemented together
• Measure value and consumption: time saved, adoption, cost

3. Rollout

• Scaled introduction across further teams and business units, in waves
• Training for both audiences
• Governance in production: approval, cost, and data-protection guardrails finalised
• Adoption support with multipliers per area

Price

All prices are net. Fixed stage prices, no day rates.