People should be the center of attention

Artificial intelligence inspires imaginations of potential increases in efficiency, but so far little has been reflected in balance sheets. People and machines face completely new requirements. How can the miracle of artificial intelligence efficiency be achieved?

Humans and AI must fit together.

Artificial intelligence (AI) and large language models (LLMs) are already being used in large companies. Initially, productivity growth was expected to reach 40%, but current estimates are closer to 25%. These values ​​are only partially reflected in balance sheets and success reports. Why is this? Is artificial intelligence not delivering what it promises?

Challenge: man and machine

The answer is complex and lies in the interaction between people and technology. While building AI systems is now relatively straightforward and these tools seem capable of almost everything, practice shows that their effectiveness depends heavily on how people use them. The capabilities of technology affect a variety of users.

Diversity of users

Employees in companies are very different and are faced with a tool from a completely new product category. Some, especially younger, tech-savvy employees, may already have experience with AI and motivation. Others, especially older employees, may be more conservative, skeptical of new technologies and perhaps worried about being replaced by them. This difference leads to different usage patterns and outcomes and creates a paradox: almost omnipotent technology caters to diverse users, especially in industries such as banks and savings banks.

Avoid new complexity

AI tools make sense and can provide significant efficiency potential for both employees and the company. However, it is essential to measure whether the expected efficiency gains have been achieved without creating new complexities. Otherwise, the IT department only grows while the balance sheet or quality does not improve.

Solutions for integrating artificial intelligence

There are different approaches to making optimal use of AI technology and increasing potential efficiency in companies, including:

• Training of all employees
• Limiting job diversity

Training of all employees

All employees must be trained to use AI tools effectively. Internal resources on the intranet and multiplier system, where a small group receives extensive training in order to train other colleagues and act as contact persons, are key here.

However, the initial efforts and costs for the training and support needed are significant, especially for savings banks and banks. If training is not tailored to employee needs, it can lead to frustration and not fully exploiting the efficiency potential of AI. This may lead to poor results and not using the tool.

Limiting job diversity

Rather than offering the full range of AI functionality, the scope is limited to a limited number of clearly defined claims. This is intended to reduce training and support efforts and cover the most common use cases.

However, restricting it too much can prevent AI from achieving its full potential. Specific functions must be carefully tailored to meet users' needs. Otherwise, the use of AI will remain limited and the expected productivity gains will not be achieved. Ongoing support is also required here, as its costs must be balanced against efficiency gains.

Innovative approach: multi-format user orientation

The third option, polymorphic user guidance, provides flexible adaptation of the AI ​​to the user in question. the movie “Ha“This is shown impressively. In the initial phase, the system recognizes the user and adapts its functions accordingly. This enables a personalized user experience that meets the individual needs of employees while taking into account the needs of the company. One of the benefits of this approach is that it significantly reduces training and support efforts while increasing efficiency gains.” To the maximum.

In practice, this means that the system is constantly getting feedback from the user and continues to adapt. This technology is already available in large MBAs and can be implemented with relatively little effort. A prototype can be created within a few hours via CustomGPT in ChatGPT.

Greater efficiency with multi-format user directions

Implementing AI in organizations represents a complex challenge that requires careful consideration of diverse user needs and capabilities. Multi-form navigation provides the user with an innovative approach to fully exploit the strengths of AI technology while enabling individual adaptation to users. Not only can this strategy reduce support costs, but it can also fully exploit the efficiency potential of AI, which will ultimately have a positive impact on company balance sheets.