AI is not the challenge, our organisations are

Five key challenges facing organisations - and what you can do directly

1. AI is not a project, AI is a process.

Many companies treat AI as an IT project: an isolated endeavour with a technical roadmap, start and end point. However, AI must be understood as an ongoing process that changes organically and must be managed dynamically. It is about continuous experience, success and decisions.

What to do?

• Understand and organise the introduction and use of AI as an iterative learning process
• Introduce an internal ‘AI roadmap’ with milestones and feedback cycles
• Create flexible decision-making channels in order to be able to react quickly to new developments

2. an AI strategy must primarily consist of business goals, not technology decisions.

The mere use of a technology is not a competitive advantage if there is no clear objective behind it. Companies need to ask themselves what problems AI should solve and what the business impact will be.

What to do?

• Clearly define the business areas in which AI should create measurable added value
• Form interdisciplinary teams of experts, technology experts and managers to identify relevant usage scenarios and determine the strategy
• Establish roles such as ‘AI coaches’ to actively support teams in the introduction of AI

3. actively involve employees to create acceptance.

Many technology or tool implementations fail due to a lack of willingness to use them. The reasons for this are complex, but can be mitigated through early involvement and participation - because without trust and clear use cases, even AI remains ineffective.

What to do?

• Communicate the benefits and limitations of AI at an early stage to reduce reservations
• Actively involve employees in the design of AI-supported processes
• Train managers to become ‘AI-competent’ decision-makers who understand and can scrutinise the use of technology

4. The biggest challenge is not the technology - but its productive use.

Many companies are experimenting with AI without rolling out the findings on a broad scale. Individual pilot projects are of little use if they are not systematically developed further.

What to do?

• Identify successful pilot projects and develop a clear scaling strategy
• Define processes for how AI-supported solutions can be rolled out from one department to the entire company and how the application can be trained
• Establish regular performance measurement to understand which AI applications bring real added value

5.Companies need clear rules and defined responsibilities when dealing with AI.

The use of AI entails risks - from faulty products to ethical issues. Companies need to define guidelines to make the use of AI transparent and safe.

What to do?

• Set up an internal AI governance team to assess risks and develop guidelines
• Define binding rules for the ethical use of AI, e.g. to prevent discrimination by algorithms
• Do not run AI as a ‘side project’, but integrate it into the long-term corporate strategy

Whoever starts now, wins

The introduction of AI is not a technological problem - it is a question of organisational development, leadership and strategy. Companies that start structured implementation now instead of continuing to discuss it have the best chance of utilising AI not just as a tool, but as a real competitive advantage.