AI introduction in companies: Guide for successful implementation

AI can be used to automate numerous processes or make them much more efficient. The AI Regulation sets out requirements for the use of AI systems. In addition to legal issues, technical decisions also need to be made. A checklist helps with a structured approach. Furthermore, there will soon be numerous training courses, workshops and lectures by Dr. GDPR on AI.

Why a structured AI introduction is essential

The integration of AI systems requires a well-thought-out strategy that goes far beyond the mere acquisition of software. Companies must not only consider technical aspects, but also meet legal requirements, train employees accordingly, and adapt processes. The AI Regulation in particular demands proof of AI competence for employees, classification of AI systems by risk classes, and avoidance of prohibited practices.

Those who use generic systems such as ChatGPT or Copilot cannot really fulfill the requirements of the AI regulation very well. Generic systems have the property that they can be used for almost anything and often deliver incorrect results. This danger can be averted.

Regardless of the AI regulation: who wants bad results? Better results are delivered by optimized AI systems that support preconceived processes. Depending on the risk appetite in terms of data protection and data security, such systems can either be run with cloud applications such as ChatGPT or on a company's own server.

The following diagram illustrates the most important steps at a glance.

The important steps for the structured introduction of AI are listed in detail in the following sections.

Preliminary considerations: The basis for successful AI implementation

Before a company invests in AI technologies, fundamental questions should be clarified:

• Identify use cases: For which specific tasks and processes should AI be used? Whether customer service, data analysis or product development – the areas of application should be clearly defined.
• Process automation evaluate: Which recurring workflows can be made more efficient through AI? Here it is a matter of identifying processes that particularly benefit from automation.
• Ensuring Result Quality: How can the quality of AI results be continuously checked and improved? Are universal AI solutions sufficient or are specialized systems needed?
• Data sensitivity evaluation: What types of data are processed in the AI system? Business secrets, confidential information, personal data or internal company data require special security measures.

Documentation: The foundation of AI compliance

Good documentation not only makes sense from a regulatory perspective, but also supports the systematic use of AI in the company:

• Inventory: Document all existing AI applications and their purposes of use.
• Employee Guidelines: Develop clear guidelines for handling AI systems that take into account both technical aspects as well as ethical principles.
• Organizational Guidelines: Define responsibilities and processes for AI deployment within your organization.
• AI guideline: Establish a comprehensive guideline that includes ethical principles, data protection regulations, and defined application areas.
• AI-Strategy: Develop a long-term strategy with clear goals, implementation phases, and measurable success indicators.

Training concept: empowering employees

The success of AI implementations depends largely on the acceptance and competence of employees:

• Target Group-Specific Trainings: Different employee groups require different training approaches – from basic introductions to in-depth technical trainings. A basic training for all as well as focused trainings for specific AI applications are sensible.
• Leadership Development: Special attention should be given to training leaders, as they act as multipliers and drive cultural change forward.

In this context, we would like to draw your attention to the following training courses and events, which are organized together with partners:

• Developer workshop, 06.05.2025 in Wiesbaden: AI IT development workshop for development departments. If you are interested, please contact Dr. GDPR.
• Compliance Training, May 8th, 2025 in Düsseldorf: Artificial Intelligence and Compliance for Executives.
• Webinar for notaries and companies, 14.05.2024, 2 to 3:30 p.m., online: Artificial intelligence basics. If you are interested, please contact Dr. GDPR.
• Erfa circle of the construction industry: 15.05.2025 in Düsseldorf. If you are interested, please contact Dr. GDPR.
• CoCon25, 03.06.2025 in Mainz: Workshop AI and Transformation. Free tickets available from Dr. GDPR.
• Webinar for notaries, 04.06.2024, 2 to 3:30 p.m., online: Artificial intelligence – in-depth study for professional secrecy holders. If you are interested, please contact Dr. GDPR.
• Webinar for companies, 11.06.2024, 2 to 3:30 p.m., online: Artificial intelligence – in-depth study for companies. If you are interested, please contact Dr. GDPR.
• MADKON25 (Mainz Digital Congress), 13.06.2025, Mainz. Workshop "Using AI to avoid mistakes". Free event, registration required.

Technical implementation: making the right decisions

Various factors need to be taken into account when selecting and introducing AI systems:

• Provider selection: Carefully check which AI provider is best suited for your requirements, and consider legal aspects such as the applicable law system in the provider's country.
• Evaluate operational model: Decide whether a self-operated AI solution or a cloud-based service better fits your needs, taking into account aspects such as data sovereignty and compliance.
• Weighing infrastructure options: From own hardware through rented hardware from US providers all the way to exclusively European solutions – the choice of infrastructure has far-reaching implications for data protection and compliance.
• Analyze cost structure