How to maximize returns on AI investments — the 5-point plan for successful AI transformation

AI is considered a savior for improving efficiency and overall performance, unlocking new sales potential, and evolving business models. Top management, in particular, have high expectations for the use of generative AI within their own organization. Budgets for AI projects have been generously increased, as our study shows, and an entire catalog of measures and initiatives for 2024 has been enthusiastically approved.

However, the expected benefits associated with adopting these new technologies will not materialize in many companies. The reason: there is a lack of strategic prioritization, budgets are not allocated reasonably. The measures are not managed holistically, and implementation often does not follow a tried-and-tested approach. The effort and challenges of implementation are often overlooked. 

Scattergun approach burns budgets and resources

Currently, the majority of companies are following the scattergun approach, as revealed by our study. Following the motto “a lot helps a lot”, they initiate AI measures in every department and conceivable category. All measures are approached with (almost) the same priority—the budget is distributed accordingly in a granular manner. The same applies to internal resources. Operational challenges and risks are significantly underestimated. Departments are already groaning and criticize the lack of strategic positioning, complain about insufficient internal expertise and the shortage of specialized team members. 

To illustrate: If I have only limited building materials and craftsmen, yet I open ten construction sites, at most two will be completed within the planned timeframe. Instead of a sustainable, self-sustaining property on a solid foundation with expansion potential that appreciates in value, the result is a run-of-the-mill building with planning errors, conventionally operated—and now we’re already talking about developing the next new residential area.  

In short, many companies will run out of financial steam before they can even embark on the next level of AI transformation. By then, the competition will have long surpassed them.