The speed at which AI is establishing itself in business and society is unprecedented. While its potential has long been recognised – from increased productivity and automated processes to completely new business models – practical experience shows that simply developing an AI strate-gy is not enough. Studies show that AI initiatives fail less because of technological hurdles and more because of a lack of structures and inadequate change management (source: The Impact of Artificial Intelligence Adoption on Organizational Decision-Making, Systems Journal, 2025).

The following challenges in particular can be identified for the successful introduction of AI:

  • Lack of organisational foundation: Without defined roles, responsibilities and committees, there is no basis for making decisions, prioritising projects and effectively managing risks.
  • Unclear procedures and processes: Without established decision-making and implementation processes, the integration of AI into existing value chains remains sluggish. Pilot projects remain in test mode and do not deliver any lasting benefits.
  • Inadequate organisational preparation of the IT infrastructure: A lack of coordination between business processes and the technical basis prevents scaling and leads to friction losses.

This raises a key question for companies: How can companies not only plan AI strategically, but also integrate it successfully, sustainably and securely into their everyday business? The decisive factor is to bring together organisation, processes and people in such a way that obstacles are overcome, acceptance is fostered and the conditions for broad anchoring are created.

This is where the AI Adoption Framework comes in. It offers a clear five-step roadmap that helps companies successfully implement AI, from initial orientation to defining goals and structures to scaling:Adoption Framework

  • Components: Companies analyse what AI can achieve in their specific environment. This involves identifying potential, risks and limitations.
  • Added value: A sound knowledge base creates transparency and decision-making certainty. This allows opportunities to be explored in a targeted manner and risks to be assessed realistically.
  • Components: A clear AI vision is developed and linked to the organisation’s values and strategic goals. This results in a roadmap that prioritises the relevant areas of application.
  • Added value: A common vision, including prioritized use cases, provides clarity and strategic alignment. Resources can be deployed in a targeted manner, decisions can be accelerated and the added value of AI for the company can be made visible at an early stage.
  • Components: Establishment of a governance program and a scalable IT and data infrastructure.
  • Added value: A stable organisational and technological basis ensures scalability and minimises risks. This leverages productivity potential and creates a resilient foundation for long-term growth.
  • Components: Targeted communication, training and role clarification prepare the organisation for the introduction of AI.
  • Added value: Employees gain confidence in the new technology and develop the necessary skills. This promotes acceptance, reduces resistance and increases the success rate of AI initiatives.
  • Components: Initial projects are implemented, results are reviewed and continuously optimised. Successful initiatives are then scaled up.
  • Added value: Initial quick wins make the benefits tangible, create momentum and increase credibility within the company. By scaling up successful projects, AI gradually becomes an integral part of value creation.

By consciously structuring the introduction of AI – from initial orientation to scaling – companies create the conditions for sustainable business success. In this way, AI becomes not a short-term experiment, but a key driver of efficiency, innovation and growth.

This article was written by

Philipp Tiedt
Philipp Tiedt
Partner, Advisory, Management Advisory, Head of AI Strategy & Implementation Service
Max Lembke
Max Lembke
Manager, Management Advisory, AI Strategy & Implementation Services & Customer Experience