Artificial Intelligence has become one of the most discussed topics in boardrooms, management teams, and leadership forums worldwide. Every leader seems to be talking about AI. Some are excited about its possibilities. Others are curious but unsure where to begin. And many feel overwhelmed by the AI hype – the speed of change, the constant stream of new tools, and the pressure to act quickly.
The challenge today is no longer determining whether AI has potential. That question has largely been answered. The real challenge is understanding how to turn that potential into meaningful business outcomes.
This is where many leaders get stuck. With questions such as:
- Where do we start?
- Which use cases should we prioritize?
- How do we move beyond isolated experiments?
- How can we ensure AI investments create real business value?
These are not technology questions. They are business questions.
And that is exactly why successful AI transformation rarely starts with technology.
Start with the Business Need
When organizations begin exploring AI, there is often a temptation to focus on tools, platforms, and technical capabilities. New solutions emerge almost daily, each promising to transform the business.
However, technology should never be the starting point.
Instead, leaders should begin by asking:
- What are our strategic priorities?
- Where do we need to create the most value?
- Which challenges consistently limit our performance?
- What opportunities could strengthen our competitive position?
- Which processes, decisions, or customer interactions could be improved?
AI is not a strategy in itself. It is an enabler.
Organizations that achieve the greatest impact from AI are those that use it to support clearly defined business goals. They focus on solving real problems rather than implementing technology for its own sake.
The most successful AI transformations are business-led, not technology-led.
A Practical Framework for AI Value Creation beyond aI Hype
Once business priorities are clear, it becomes much easier to identify where AI can create meaningful value.
According to José Parra Moyano from IMD Business School, there are three dimensions to be adressed in AI transformation:
- Value
- Data
- People.
For this article, lets focus on the first: Value. He proposes a simple and practical framework that I find particularly useful when helping leaders structure their thinking and define their next steps.
The framework describes three levels of value creation:
1. AI for Me: Becoming a More Effective Leader
The first and often most overlooked step is personal adoption.
Before leading AI transformation across an organization, leaders should gain firsthand experience using AI in their own work. This builds confidence, understanding, and credibility.
Examples include using AI to:
- Prepare presentations and reports
- Summarize large volumes of information
- Draft communications and meeting notes
- Analyze data and identify insights
- Support planning and decision-making
- Generate ideas and explore alternatives
The goal is not to become an AI expert overnight.
The goal is to learn through practical experience. By integrating AI into daily work, leaders develop a more realistic understanding of both the opportunities and limitations of the technology.
Perhaps most importantly, you as a leader begin to role-model the behaviors you hope to see across the organization.
2. AI for My Team: Improving Productivity and Collaboration
Once you as a leader become comfortable using AI themselves, the next step is exploring how AI can create value across teams.
This is where organizations often start seeing measurable productivity gains.
Questions to explore include:
- Which repetitive tasks consume valuable time?
- Where do quality issues occur?
- How can information be accessed and shared more effectively?
- Which processes could be accelerated without sacrificing quality?
Potential applications might include:
- Automated meeting summaries and action tracking
- Knowledge management and information retrieval
- Content creation and communication support
- Data analysis and reporting
- Customer service support
- Project and process optimization
At this stage, teams can begin identifying specific use cases, testing solutions, and measuring business impact.
The focus shifts from curiosity to tangible results.
3. AI for My Organization: Driving Business Transformation
The third level involves scaling AI across the organization and integrating it into broader business transformation efforts.
This is often where leaders instinctively want to start. However, it is also where complexity increases significantly.
At this level, AI influences areas such as:
- Customer experience
- Product and service innovation
- Operational excellence
- Stakeholder management
- Business processes
- Operating models
- Technology architecture
- Data governance
- Organizational culture
- Talent and capability development
Successfully implementing AI at this level requires alignment across multiple functions and a clear connection to strategic objectives.
It is no longer about individual tools or isolated use cases. It becomes an organizational transformation journey. This journey MUST be carefully orchestrated across strategy, processes, technology, data, governance, and last but not least – culture, and people. Taking a thoughtful and structured approach is critical to realizing sustainable value from AI. We will explore this topic in more detail in a future article.
Why Starting Small Leads to Bigger Success
Throughout my career—starting with my early work in Operational Excellence—I have observed an interesting phenomenon: people are naturally drawn to complex, sophisticated tools and solutions. The simple first steps often seem less exciting, and sometimes even too obvious to matter.
Yet, sustainable performance improvement rarely works that way. No one goes from novice to expert overnight. First, you learn to crawl. Then you learn to walk. Only after building experience, capability, and confidence can you start thinking about running a marathon.
I have seen countless organizations invest significant time and resources in ambitious, high-level initiatives because they were attracted by the promise of transformational results. The challenge was not the solution itself—it was that the organization’s capabilities, ways of working, and level of readiness had not yet matured enough to support it.
The same principle applies to AI. While large-scale transformation opportunities are exciting, lasting success starts with small, practical steps. Leaders and teams need the opportunity to experiment, learn, adapt, and sometimes fail. Through that process, they build the experience, confidence, and capabilities required to unlock greater value over time.
AI transformation is not a sprint to the most advanced use case. It is a journey of continuous learning and capability building that ultimately enables organizations to successfully tackle more complex opportunities.
And this journey includes you as a leader. Without practical own experience, it is difficult to identify realistic opportunities, address concerns, and guide your teams effectively.
Starting with “AI for Me” creates a strong foundation. It allows leaders to experiment, learn, and build confidence before scaling adoption across teams and the broader organization.
In my experience, leaders who actively use AI themselves are better equipped to ask the right questions, identify meaningful use cases, and lead change more credibly.
Final Thoughts
The AI conversation is often dominated by technology, algorithms, and tools. But successful AI transformation is ultimately about aligning technology with business value, trusted data, and empowered people.
If you are wondering where to start, resist the urge to focus on platforms and features.
Instead, start with your business needs. And with yourself.
Clarify your priorities. Identify where value can be created. Then begin your AI journey at the personal level, expand to your team, and gradually scale across the organization.
The organizations that succeed with AI will not necessarily be those with the most advanced technology. They will be the ones that most effectively align technology with business value, trusted data, and empowered people.
And that journey often begins with a simple question:
How can AI help me become a better leader today?
Author note: This article is inspired by the work of José Parra Moyano at IMD Business School and his perspective on the three dimensions of AI transformation and value creation.