de
Contact
see all blog posts

5 steps to real AI competence –
How companies can future-proof their teams

Digital Advisory Digital Business Consulting Blog article

Author: Dennis Looks, Director Digital Strategy

Colleagues discussing work in front of a whiteboard

Attending an AI webinar and calling it a day? Not quite – real AI competence requires much more. The EU AI Act makes it clear that companies must properly equip their employees to work with AI. How can they do this? With a strategic and sustainable enablement approach in five steps.

AI competence becomes a must-have

AI is transforming processes, business models, and value creation across all industries. As its adoption grows, so does the responsibility to ensure safe, transparent, and ethical use. To address this, the EU has introduced the EU AI Act. Since February 2025, the regulation requires employees in companies that develop, provide, or use AI within the EU to be properly trained and competent in handling it.

AI literacy requires more than just training

Many companies are already investing in AI training, yet lasting success often remains out of reach. The reason? Training alone isn’t enough to develop true AI competence. It’s not just about understanding the basics of machine learning or data analysis—it’s about using AI strategically, navigating ethical and regulatory frameworks, and accurately assessing the potential of AI applications. For AI knowledge to have a lasting impact, it must be deeply embedded in daily work—one-off training sessions won’t suffice. To systematically build AI competence within a company, five key steps are essential.

  1. AI enablement must align with corporate strategy
    Building AI competence shouldn’t be treated as a standalone IT project—it must be part of a holistic program that includes governance, technical skills, cultural change, and risk and compliance considerations. Therefore, skill development must be closely aligned with the company’s overarching AI strategy. This requires:

    — Defining a clear vision and concrete goals for AI adoption within the company
    — Integrating AI into existing processes and workflows
    — Addressing governance, compliance, and ethical considerations

    Only when employees see AI as a strategic tool will they become active drivers of innovation rather than just passive implementers.
  2. Leaders as drivers of AI transformation
    A successful and lasting AI transformation requires active support from top management. Leaders play a crucial role by:

    — Communicating a clear vision and strategic goals for AI adoption
    — Allocating resources and prioritizing AI education
    — Leading by example and developing their own AI competence

    To effectively guide their teams through this transformation, managers must understand not only AI’s potential but also its challenges.
  3. A two-tier training strategy: foundational knowledge & specialized learning
    Successful companies implement a two-step approach to AI literacy:

    AI literacy for all employees
    — Basic understanding of AI and its applications
    — Awareness of ethical and regulatory considerations
    — Reducing uncertainty and fostering a positive AI culture

    Specialized training for different roles
    — C-Level: Strategic integration of AI into business growth
    — IT & Data Science: Advanced technical expertise
    — Specialist Departments: Practical, role-specific AI applications

    This model ensures a shared foundational knowledge across the organization while equipping specialized roles with targeted expertise for their daily work.
  4. Flexible and practical learning formats
    Traditional training alone isn’t enough to embed AI competence long-term. Companies should combine digital and hands-on learning formats, such as:

    — E-learning modules: Self-paced interactive content
    — Workshops & Hackathons: Real-world application of AI knowledge
    — Blended learning: A mix of online courses and in-person training

    The key to success is practical relevance—employees should not only learn about AI but also experience how it enhances their work efficiency and decision-making.
  5. Establish AI centers of excellence & communities
    To prevent siloed knowledge and foster cross-company collaboration, organizations should set up centralized AI Competence Hubs or Centers of Excellence (CoE) to:

    — Consolidate AI expertise and make it accessible across teams
    — Document and share best practices
    — Train internal AI experts through a “train-the-trainer” model

    Additionally, building AI communities within the company allows employees to network, exchange experiences, and explore new AI use cases together.

Conclusion: AI competence is more than training—it’s future-proofing

The EU AI Act underscores that companies need more than occasional training sessions to stay competitive. AI competence doesn’t develop overnight—it requires a strategic, hands-on approach aligned with corporate goals, driven by leadership, and embedded in everyday workflows.

A two-tier training model ensures broad AI literacy and specialized expertise, while Centers of Excellence and internal communities facilitate continuous learning and long-term knowledge transfer. Companies that invest in real AI expertise today are laying the foundation for sustained competitiveness—and empowering employees to become active drivers of digital transformation.

What is the EU AI Act?

The EU AI Act is a regulation that governs AI use within the European Union. Article 4 mandates that companies developing or deploying high-risk AI systems ensure their employees have the necessary AI competence. This requirement is designed to guarantee the safe, ethical, and responsible use of AI.
More details on the EU AI Act can be found here.

5 steps to true AI literacy

  1. Align AI with corporate strategy:
    AI should support long-term business goals rather than operate in isolation.
  2. Leaders as AI champions:
    Leadership must actively drive AI initiatives and foster a culture of innovation.
  3. Two-tier training model:
    Foundational AI knowledge for all, with specialized training for key roles.
  4. Flexible, practical learning formats:
    AI education should be interactive and tailored to employees’ needs.
  5. AI centers of excellence & communities:
    Internal hubs and networks ensure continuous learning and knowledge sharing.

Learn more about AI literacy Start your AI enablement program now

 

Teilen

IBM iX

The Experience Agency
of IBM Consulting
Subscribe
Initiatives
Global network
Community
IBM iX Spotlight Newsletter

Digital trends & insights, right in your inbox.

© 2025 IBM iX