AI Introduction in SMEs – The Biggest Risk Is Not Making a Decision

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How well do you understand the potential of artificial intelligence?

In interviews with managing directors, the most frequent complaint is:

"There are so many possibilities and everything is so confusing that we don't know where to start."

As long as the boss is not fully convinced, the AI project will get stuck at the slightest difficulty (and believe me, there will be difficulties).

No matter how undecided you are: You have to make a decision about introducing AI! Waiting is the biggest risk, because competition is developing at breakneck speed.

Understanding the potential of AI

The technology is so new that most companies still lack experience with it.

I regularly see how managers of small and medium-sized companies approach artificial intelligence with a mixture of fascination and caution.

Expectations are high: AI is set to fundamentally change the way value is created and competitive advantages are achieved.

But what exactly does that mean?

Be honest, you are still unsure, at least you still lack a clear target image. You still need to learn the technology. Get started, try it out, gain experience. Many large companies are already launching internal initiatives and seeking advice from experts.

At the same time, there is a great deal of uncertainty in SMEs about how AI can be effectively introduced into the company and which processes will benefit most from it. Answering the question of where in the company artificial intelligence actually generates added value, reduces costs and increases added value requires careful analysis and a pilot project.

AI expertise is necessary

Given the current pace of AI development, I am certain that if you do not have any internal AI expertise in your company, you should seek advice from an external expert.

And the market for AI experts is confusing. Numerous self-proclaimed "ChatGPT experts" and "prompt engineers" offer their services, often without in-depth knowledge of how AI can be successfully integrated into existing company structures.

In this scenario, small and medium-sized enterprises find themselves in a dilemma: high pressure to act on the one hand and an unclear target image on the other. As a result, many companies are hesitant to make the necessary decisions regarding the implementation of AI.

However, this reluctance harbors a considerable risk. In today's fast-paced and technology-driven business world, hesitation to make decisions regarding the use of AI poses the greatest threat to the competitiveness of companies.

I would therefore like to show a way in which decision-makers can develop an effective AI strategy and implement it in the company despite uncertainties. With 3 steps, small and medium-sized companies can master this challenge and secure a future-proof position in the market.

How quickly can AI be integrated?

The fact that artificial intelligence is technically possible does not mean that it can be integrated into the company immediately. The new technology must first go through the organizational friction process.

Organizations have well-established structures and usually a certain degree of inertia. Many employees are worried that artificial intelligence could replace them. They are unsure whether they will be able to deal with this new technology and whether their work will change as a result.

This factor must be considered and taken into account. It therefore takes a certain amount of time to integrate an existing AI solution into a company so that the company becomes stronger and benefits sustainably.

For this very reason, I recommend that you decide quickly and gain initial experience with a pilot project.

Introducing AI in 3 steps

So how do small and medium-sized companies come to an AI decision? In the following, I will guide you through the 3 steps that successful companies go through when introducing AI. You will first test artificial intelligence and only then integrate it into your processes on a large scale:

1. AI workshop
2. AI strategy and pilot project
3. AI implementation and scaling

Step 1: AI workshop

This first step involves working with management and employees to find suitable AI use cases for your company. The format of the AI workshop creates an understanding of the added value of AI and promotes acceptance among employees. It is important to communicate transparently what AI means for the company, how it works and what impact it can have on individual areas of work. At the same time, fears and concerns should be taken seriously and addressed.

This phase is crucial for the successful use of AI in the company. It lays the foundation for acceptance and sustainable anchoring of the technology in the work process.

The following procedure has proven itself in practice:

Clear objectives from the company management: Management must clearly define which goals are to be achieved with the introduction and how the goals contribute to the corporate strategy. This makes it easier for everyone involved to understand and categorize the purpose of introducing AI.

My recommendation: Organize a workshop session with all relevant decision-makers in the company and set your goals for the introduction of AI together. Have the workshop session conducted by an experienced AI consultant so that a broad spectrum of use cases can be considered in the objectives.

Involvement of employees: A crucial step is the early involvement of employees. AI projects can only be successful if a critical part of the workforce adopts the new technology in their work processes. This is why "early adopters" are selected from each relevant team. By this I mean AI-savvy Participants who help to identify implementation ideas and later act as multipliers.

Implementation of an AI workshop: An AI workshop is held with the selected early adopters. In this workshop, successful AI use cases from other companies are presented and the potential of AI for your own company is discussed. Together with the employees, the workshop moderator analyzes existing processes. Under the guidance of an experienced AI consultant, initial ideas for optimizing these processes using AI are designed, discussed and evaluated.

The results of this workshop are multi-layered:

• Building AI know-how: The employees involved gain a basic understanding of AI and its potential.
• Development of specific ideas for improvement: Concrete ideas emerge on how AI can improve the processes in your company.
• Employee commitment: Through active participation, employees develop a commitment to the introduction of AI in their work processes.

These results form the basis for the further development of the AI strategy and the planning of a pilot project. Through this structured and employee-centered approach, you can ensure that the introduction of AI not only makes technical sense, but is also supported by the employees. I think that's an important building block.

Step 2: AI strategy and pilot project

In the first step, a foundation was laid for the introduction of AI; now, in the second step, you are taking care of AI strategy development and the implementation of a pilot project. This phase is characterized by detailed analysis, strategic planning and exploration.

Preparation and analysis of AI ideas: The ideas collected in the first phase are analyzed, evaluated and processed by the AI consultant. The analysis focuses on aspects of potential business impact, feasibility, availability of data and interfaces as well as measuring success with KPIs.

In my opinion, the results of the analysis are extremely relevant for company management and decision-makers in the company, as they show concrete options for action and serve as a basis for the development of a corporate AI strategy.

Development of an AI strategy: An AI strategy is designed based on the results of the analysis. The AI strategy defines fields of action for the introduction of AI and determines their prioritization. It identifies the success factors and takes into account the necessary enablers, such as access to specific data and interfaces. It also defines which teams are involved in implementing the strategy.

Selection and implementation of a pilot project: With the clear direction provided by the AI strategy, it is now possible to decide which topic from the pool of ideas will be implemented as the first pilot project.

It should be possible to implement the pilot project with little effort and within a short time. I recommend that you use low-code tools to develop the pilot. This allows you to create a ready-to-use AI integration for your company quickly and at a manageable cost. This AI integration is then tested by pilot users in real working environments to gather feedback and correct errors at an early stage. This helps to avoid major bad investments.

Performance measurement and evaluation: The success of the pilot project is continuously measured and evaluated using KPIs. This process helps to determine the real benefits of AI integration and make any necessary adjustments.

This systematic approach allows small and medium-sized companies to take a practical, low-risk route to effectively integrating AI into their processes and gaining valuable insights for future projects.

Step 3: AI implementation and scaling

The third phase of AI implementation and scaling is crucial for the long-term integration of AI in your company. This phase builds on the experiences and findings of the pilot project and aims to operationalize AI broadly within the company.

Regular tracking and adjustments: Continuous monitoring of the KPIs as part of the pilot project is essential. It enables you to identify and correct errors promptly. This phase is also a valuable learning time for the company and the employees involved to understand how artificial intelligence can improve existing processes.

Integration of AI into other processes: Now that the positive effects of AI are visible in the pilot project, now is the ideal time to integrate AI into other business processes.

At this point at the latest, you should ask yourself who should develop and operate the systems in the long term. Internal teams or external service providers (make-or-buy decision)? In my view, the company's AI strategy, which has already been developed, should clearly define this.

Review and adjustment of the organizational structure: Many companies use this moment to review and adapt their organizational structure. This is important in order to steer AI initiatives in a targeted manner and anchor them permanently in the organizational structure.

Focus on scalability: An early focus on the scalability of AI solutions pays off. Scalability prevents technical dead ends and accelerates the transition to an AI-centric organization. Scaling should be designed in such a way that AI solutions can be flexibly extended to different areas of the company.

By taking this strategic approach to AI implementation and scaling, you can create a solid foundation within the company for the further expansion of its AI capabilities. It's not just about successfully implementing individual projects, but about leading the organization as a whole on the path to an AI-centric future.

Conclusion: AI paves the way for your future business success

Introducing and integrating AI into your organization is a multi-stage process that requires both strategic planning and human empathy. As I have shown you, it is crucial to take an exploratory approach involving key stakeholders from the workforce.

The key to success lies in carefully testing AI systems through a pilot project, before they are fully rolled out. This allows you to integrate the technology effectively and realize the full benefits.

In my experience, successful organizations are characterized by the fact that they communicate and negotiate with their employees at an early stage, make the company's ambitions and goals regarding AI clear to them and involve employees in the process at an early stage.

Remember: AI is more than just a technological innovation; it is a catalyst for change and growth. Companies that follow this path will open up new horizons in efficiency, innovation and competitiveness. The journey may be challenging, but it is essential to succeed in today's fast-paced, technology-driven business world.