Companies need evaluation instruments to steer through demanding AI transformation processes. Often, practitioners face a conflict between picking tools with very few items that are easy and fast to answer but which may be of little use – and longer tools that really could help but are difficult to vouch for. We offer an approach to deal with this issue.

The real challenge: organizational change

Do you feel your organization is prepared to handle the disruptions caused by the availability of AI solutions in almost every area of work?

While the big companies in Germany began working with AI technologies years ago, more and more small and medium-sized enterprises (SMEs) are realizing the importance and starting their first projects to introduce AI into their work environments. Once they start their first AI projects, they see that it is not just about getting software with new capabilities; AI means the company is starting a continuous learning journey that brings new roles and responsibilities, as well as new perspectives on individual and organizational development. In most cases, the hardest part about the AI disruption is not implementing the new technology itself, but preparing the company to embrace the changes it brings at both the organizational and individual level. How can companies create favorable conditions for the use of AI to not only benefit from a single application, but also fully exploit the potential of AI?

Assessment tools are essential

Appropriate change management should, of course, be based on a thorough analysis of the status quo. Various measurement methods are available to companies, some free of charge, and others require paying a fee. There are short quick tests with a low level of resolution, and instruments with large item sets that provide a more differentiated picture but are more complex and take more time to fill in. Practitioners usually tell us they prefer short and concise tools that can be implemented with few personnel in a very short time. They fear they may be unable to justify the additional effort of more comprehensive instruments to their superiors, or that they will not be able to present complex results in a sufficiently condensed or simplified form to all stakeholders. Nevertheless, they also assume that such short tools will barely scratch the surface of actual transformation needs and are thus of little relevance to the actual change management.

The KI-ULTRA Evaluation Toolkit (E.T.)

Obviously, this conflict cannot be resolved fully. However, there is a way to limit the efforts and maximize the usefulness of the output in a reasonable manner. In the KI-ULTRA project (funded by the Ministry of Labor and Social Affairs, BMAS), we have developed such a measurement. It is available free of charge. Here, companies can start a survey that their employees and managers can fill out, and the results are instantly visualized once the survey is completed. For each construct or aspect measured, the visualization of results refers to the relevant section in the KI-ULTRA guides so that users easily find advice on how to make improvements.

How we made the E.T. comprehensive and efficient at the same time

  • Modular structure: the questions for measuring the need for transformation and the questions for evaluating the success of an AI implementation project are available in two separate modules that can be carried out individually.
  • Adaptation to company size: we offer two different versions of the E.T.:

    1. (1) one for medium and large enterprises
    2. (2) one for small companies
  • Role-based question sets: employees receive a tailored selection of questions depending on their role. Since especially managers often have limited time, they receive a particularly short set of items.
  • Presentation of results: each construct is presented in two frames of reference:

    1. (1) a comparison to the range of the scale
    2. (2) an anonymized benchmark with all other participating companies
  • Individualization: On request, we can provide a survey with a selective set of items, based on the current needs of the organization.

Of course, measuring only makes sense if one is committed to taking action based on the results. AI has come to stay, and if we want to remain competitive, we need to get moving. Every journey starts with a first step, and assessment tools can help us determine the right direction.

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Jan-Paul Leuteritz

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Kategorien: Künstliche Intelligenz
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