AI Strategy 2026: Why Transformation Comes Before Tools

Which Processes Create Value?

This question sounds simple but is usually difficult to answer.

From an AI perspective, it becomes: Where can AI create the greatest leverage? Which workflows should be mapped or supported with AI?

First, however, one must clarify what these processes actually look like. Here, homework often awaits, as processes are rarely truly documented.

Beyond processes, company-specific context plays a central role: How can this context be prepared for AI so that it can provide optimal support?

And in terms of transformation: How can lessons learned be shared efficiently within individual teams, across departments, and ideally throughout the entire organisation?

The Place of AI in the Organisation

The place of AI is also a budget question that each business must answer individually.

One consideration: Should a dedicated budget be created for AI integration, or should existing budget lines be reallocated?

If the AI budget is funded from existing resources – for example, through savings in other areas – the pressure to justify increases: the AI investment must then not only work on its own terms but also compensate for the gap created elsewhere.

This describes one of the fundamental challenges: all relevant processes must be examined before transformation can begin – and at the same time, budget lines must be planned in advance.

Clear Processes and Measurable Goals

It is important to distinguish clearly between processes and goals. The clearer it is what should be achieved, the easier AI implementation becomes.

The following questions can serve as initial prompts:

• What do our processes currently look like, and how precisely are they documented?
• What information is needed for individual processes, and in what form is it available?
• What additional resources are required for implementation?
• How is the necessary information currently used and processed?
• Are there clearly defined rules or thresholds that must be observed?
• Which parts of the process can AI handle, and which decisions should continue to be made by people?
• What results should be achieved, and what goals should be reached?

This approach pays off: it creates the opportunity to critically examine fundamental business processes. Do they need to be redesigned entirely, or are simple adjustments sufficient? When evaluating processes, inefficiencies are often discovered that had previously been accepted as given.

Bringing Employees Along: Taking AI Concerns Seriously

AI is undoubtedly a disruption and causes uncertainty. Concerns about jobs are legitimate and must be taken seriously.

AI differs from earlier disruptions in that it is invisible – not tangible like a steam engine or a welding robot. Moreover, AI affects all areas of the business, not just a single process.

This makes it all the more important to engage employees and enable them to use AI effectively. The question is not “AI or people” but rather “people with AI.” Used correctly, AI can safeguard jobs: it helps compensate for skills shortages and makes employees more productive and valuable.

Employees need not only one-off training but also sufficient time to develop the necessary competencies in their daily work. Without this time, even the best training will come to nothing.

Three Perspectives for Your AI Strategy

An effective AI strategy considers three levels:

1. Individual Level: How can AI usage be optimised at a personal level? How can employees be brought along? What empowerment is necessary? Put differently: How can you ensure that instead of “shadow AI,” genuine progress toward teamwork is achieved?
2. Workflow Level: How can work processes be supported with AI? Which workflows currently exist, and which can be adapted so that AI support works effectively? Which can be completely redesigned or eliminated? And which workflows are actually worth investing additional resources in?
3. Automation Level: For which core processes can AI automation lead to efficiency gains? This differs from the workflow level in that here, genuine automation occurs, while in workflows, people remain part of the process.

AI will affect all areas of the business. That is why it is important not to focus solely on the “low-hanging fruit” but to examine all areas. This requires time and genuine insight into the organisation – generic advice rarely leads to the desired success.

Strategy and Vision: Combining Two Approaches

In AI implementation, many businesses pursue a dual track:

Incremental Approach: AI is integrated into individual workflows. The learning phase is short, successes become visible quickly, and AI relieves human team members. The disadvantage: processes are simply “rebuilt” with AI, and additional efficiency gains remain unrealised.

Transformative Approach: Processes emerge that were previously unthinkable because they could not be delivered by a human team. Processes are not rebuilt but completely redesigned and optimised with the help of AI.

A good mix of both approaches leads to success: the incremental benefits build trust in the technology and make initial successes visible quickly. This creates the foundation for genuine transformation, where some instances of “we’ve always done it this way” may be cast overboard.