Background to the study “Artificial Intelligence & Decisions”

  • In this study, we analyze the support of decisions in the company through Artificial Intelligence.
  • To this end, we look at current activities in companies to introduce AI and differentiate them according to the support provided for operational execution and complex decision-making tasks. We examine the importance of AI in supporting decisions in six specific decision-making areas in marketing and sales, as well as the actual application of AI and the adequacy of investments in these areas. Finally, we evaluate the obstacles and success factors in initiatives to introduce AI for decision support.
  • In collaboration with a renowned market research institute, more than 200 executives from German-speaking retail, wholesale and e-commerce were surveyed in September 2025 (DACH region).

Overview of the results of the study “AI & Decisions”

Status quo on AI implementation projects

  • 73% of companies have already started initiatives to introduce Artificial Intelligence.
  • The majority of these initiatives focus on supporting execution tasks rather than decision-making tasks.

Strategic importance of AI-supported decisions

  • The majority (59%) of the executives surveyed see a strategic competitive advantage in supporting decisions through artificial intelligence.
  • Accordingly, 53% expect a competitive disadvantage if decisions are not supported by Artificial Intelligence.
  • However, most companies (57%) currently see a
    higher risk in supporting decision-making tasks through Artificial Intelligence than in execution tasks.
“The use of Artificial Intelligence in decision-making will become a strategic competitive advantage. Companies currently lack the competence to use and understand AI, the associated trust in AI outputs, and the necessary data infrastructure to make AI work for decisions.” Dr. Markus Husemann-Kopetzky, Managing Director, Price Management Institute

Application and investment in AI-supported decisions

  • The application gap is -55% and the investment gap is -59%.
    The application gap describes the ratio between the proportion of respondents who consider AI to be important for decision-making and the proportion of respondents who use AI for the respective decision category. The investment gap, in turn, relates the proportion of respondents who perceive AI as important for decision-making to the proportion who consider their own company’s investments in AI to be sufficient for the respective decision category.
  • The investment gap in Artificial Intelligence is largest for pricing decisions.

Success factors and obstacles to introducing AI-supported decisions

  • More than a third see the greatest obstacles in the necessary investments (41%) and the still low level of trust in AI-based recommendations (34%).
  • Most executives see the greatest success factors in building AI competence among employees (55%) and in access to data sources (51%).