AI Implementation

    AI implementation: introducing AI your team uses every day

    At datadice, AI implementation means selecting suitable AI tools, connecting them to your data and systems and bringing them into your workflow with clear rules. The starting point is your tasks and the licences you already have. Since February 2025, Art. 4 of the AI Act has required companies to ensure sufficient AI literacy among their staff; practical training through the datadice Academy is part of the introduction.

    Goal:Introduce AI sensibly

    Book an initial consultationView strategy workshop

    Last reviewed: · reviewed by Thomas Knorr, Managing Director datadice

    Your AI system landscapeBeing assembled
    ApplicationsChatAssistant
    ModelsModel AModel B
    DataSharePointERP
    RulesData traffic lightRights

    Your team uses AI with clear rules

    At a glance

    What
    datadice selects AI applications and models, connects them to your data and systems and defines rights, rules of use and responsibilities.
    For whom
    Companies with their first AI licences and departments that have specific applications in mind.
    Outcome
    A coordinated selection of applications, models, data connections and operation, with a permissions concept, rules of use and training.
    Getting started
    Initial consultation, then a strategy workshop with current-state analysis

    Funding:Small companies in Bavaria receive a grant of up to 50% from the Digitalbonus for the introduction. We prepare the application with you free of charge.

    Go to the Digitalbonus

    Typical starting point

    You want to use AI in your company in a targeted way. The first licences are in place, and your departments have specific applications in mind. But which AI systems suit your tasks? Which can be connected to your data and existing applications? And what costs and dependencies arise in ongoing operation? Individual tools do not yet answer these questions.

    Our answer

    Implement and enable

    You receive an AI system landscape tailored to your company that your employees use in their daily work, because selection, set-up and enablement are planned together.

    What we stand for
    We are convinced: mid-sized companies select AI according to their own business goals. A loose collection of individual tools achieves little. Value only comes when AI applications, models, data and existing systems work together in everyday operations. To shape their AI system landscape deliberately, companies must assess quality, costs and dependencies.

    Approach

    How does a mid-sized company introduce AI?

    With one specific task. datadice starts with the question of which workflow costs time today. Only then does datadice choose the application and model.

    First, we clarify the task, the metric and the systems and licences already in place, for example an office suite with AI features and an ERP. Then we assess possible solutions by performance on your task, connection to your systems, data protection and total cost.

    In the third step, we set up the selection, connect it to your data and test it with the department on real examples. Finally come rights, rules of use, training and the question of who operates the solution.

    For your IT

    Who looks after the AI once the project team has left?

    We settle that before the start. datadice agrees an operating model with you: which tasks your IT takes on, which datadice takes on and how changes are reviewed.

    Documentation and training are part of the delivery. Your technical staff learn the tasks they take on themselves in the datadice Academy.

    We state the internal effort for your IT before you decide. If you later want to take over operation entirely or hand it to another partner, we plan that transition too.

    For your IT management

    Where is our data stored and can we switch models later?

    That depends on your use case. For every solution, datadice discloses where data is processed, which dependencies arise and what a switch costs.

    Options include AI models in EU data centres without data retention at the provider, as with IHK zu Coburg, hybrid operation or a local model in your own data centre.

    For sensitive documents, we define a data traffic light in the strategy workshop: green is free, yellow only in the approved environment, red only with explicit approval. These rules apply regardless of the provider. For every solution, your IT receives a sheet listing data sources, processing locations, models, access and exit options.

    Architecture

    How datadice brings AI into your workflow

    Together with you, we put together a tech stack (the interplay of AI applications, models, data connections and operating infrastructure). The starting point is your business goals, use cases and existing systems.

    Step 1 of 4

    01

    Use case

    We clarify your business goals, use cases and existing systems and check which applications and licences can already be used.

    Example: AI for checking incoming invoicesStep 1 of 4

    Use case

    Task: Check incoming invoices

    Metric: Processing time per incoming invoice

    In place: ERP, AI licences in the office suite

    Outcome

    What you receive

    You receive an AI system landscape tailored to your company, made up of selected AI applications, models, data connections and operating infrastructure. This includes the agreed set-up and integration, a coordinated permissions concept, rules of use, clear responsibilities and practical training. We support operation, ongoing quality checks and further development to the agreed extent.

    • Set-up and integration to the agreed extent
    • Permissions concept, rules of use and clear responsibilities
    • Options and limits regarding choice of provider, place of operation and later changes, set out openly
    • Practical training through the datadice Academy

    Building blocks

    We start with your data

    Data basis

    Every AI application works with your data and your knowledge, so the introduction starts with the data foundation.

    Sources, meaning and quality of the data your use case needs.

    Application

    AI tools, integrated into your workflows and existing systems.

    Your existing systems and licences form the starting point, so we only add what the use case additionally needs.

    Enablement

    Your team uses the solution confidently and develops it further.

    Effective AI needs reliable data, clear business rules and people who use it confidently.

    Example result

    Five rules for using AI in your company

    datadice defines these five rules with you in the strategy workshop; they fit on one page.

    1. 1

      One tool for everyone

      Approved, with a business contract, data processing agreement and sign-in via the company account.

    2. 2

      The data traffic light applies

      Green is free, yellow only in the approved environment, red only with explicit approval.

    3. 3

      One person decides

      On new tools and new cases; data protection and information security advise them.

    4. 4

      Switching without consequences

      Anyone who has used AI privately so far switches by a set date.

    5. 5

      Proof of training

      Everyone who uses AI receives a short training session and documents their participation (Art. 4 AI Act).

    View strategy workshop

    Application

    Pilot with a metric, then operation

    We plan operation and further development from the outset, so the solution remains manageable after launch. You receive an operating model with defined responsibilities, support services and reporting lines. Beforehand, we agree which tasks your team takes over after handover and where datadice provides support.

    datadice starts every AI introduction with a pilot on one task and one metric, for example the processing time per incoming invoice. Baseline and target value are set before the start. After the pilot, you decide based on the measurement whether the solution goes into operation, is adjusted or stays smaller.

    Knowledge

    Articles on this topic

    ChatGPT Enterprise or Custom AI: What Fits When?When is ChatGPT enough? When do you need your own solution? We compare both paths.13 min read(opens in a new tab)Claude for Business: The Guide 2026Chat, Cowork or Code? The guide explains context windows, licences and GDPR. Plus: Claude only in the EU, Design and Motion. As of October 2026.15 min read(opens in a new tab)Google Cloud for AI Projects: Vertex AI, BigQuery & Co.Which Google Cloud service fits which AI use case? A guide from practice.16 min read(opens in a new tab)

    Frequently asked questions

    An objection we often hear

    „We already have AI licences and an IT partner.“
    Good, datadice builds on that. Together with your responsible staff and your IT partner, we check what is already covered. Then we only add what the task additionally needs.
    What does getting started cost?

    The strategy workshop is one day on site at a fixed price of €3,900 net, including preparation, travel and follow-up. The initial consultation before it is free.

    Do we have to implement with datadice afterwards?

    No. The results are available to you for further implementation, including with a partner of your choice.

    Who operates the solution?

    Operation and further development are agreed services with clear responsibilities. You decide which tasks your team takes on.

    Do we have to replace existing systems?

    No. Your systems and licences are the starting point; datadice only adds what the use case additionally needs.

    Getting started

    Which task should AI take on first in your company?

    In the free initial consultation, we talk about your goals, the planned applications and how you use AI so far. Afterwards, you receive a short playbook.

    Starting point:Strategy workshop with current-state analysis

    Book an initial consultationSee the strategy workshop