Article by Nadine Soyez.

Why a Clear Plan Matters More Than Just Tools.
Across various sectors, many organisations are starting to explore how AI can support their operations. But in my experience, I often see the same patterns repeating, and not all of them lead to success.

Here are two common starting points I observe:

• Some organisations begin by trying out AI tools without a clear plan or goal.
• Others are unsure how AI fits into their current ways of working, so they hold back.
• Only a few think more strategically and set up clear use cases 
• Many are overwhelmed by the AI noise and don’t know how to find structure or decide what is best for them.

The first two approaches are understandable, but on the other hand, they can lead to confusion, wasted time, and poor results.

 

What I’m seeing in organisations today

Based on my ongoing work and conversations with companies and people across Europe, a few clear trends are emerging:

• 66% of the people believe AI will change 30% or more of their work within the next two years
• Employees are already using AI tools informally, often without the knowledge or support of IT teams or senior leadership.
• More than 70% of those who use AI honestly say that they aren’t seeing a real impact on the bottom line.
• Around 80% of AI projects fail when organisations don’t prepare properly or assess how ready they are.
• In many cases, more than 40% of AI spending is wasted due to overlapping projects and a lack of coordination.
• 56% of people say training is key for AI adoption, but nearly half feel they’re receiving moderate or no support.

These challenges highlight one key point: adopting AI successfully isn’t just about using new technology. It is about the people who integrate AI in their tasks, not replace them. It’s about getting the whole organisation ready and having a clear strategy in place. 

 

Why strategy comes first to get an AI-savvy workforce

The most successful companies view AI as an integral part of their broader business strategy. It is not just a side project for the IT department. There are two main approaches we see:

• Some organisations set clear goals, assign responsibilities, and build governance structures from the start.
• Others begin with small test projects (or “pilots”) to learn what works.

Both approaches can be useful. But lasting success depends on combining hands-on experience with a clear plan that supports long-term growth.

 

What a Good AI Roadmap Looks Like

A strong AI roadmap gives organisations a step-by-step plan. It helps guide decisions, avoid duplication, and ensure that teams are working towards the same goals. And most importantly, it involves the people. 

Here are five key parts of a successful AI roadmap:

1. Vision and Goals: What role will AI play in your organisation?
This step is about being clear on why you’re using AI. Is it to save time, cut costs, improve customer service, reduce risk, or something else? Set clear goals and use KPIs to measure progress.

2. Readiness Assessment: Where are you now?
Assess your current strengths and weaknesses. Look at your people, processes, data, and technology. Industry benchmarks can help you understand how you compare to others.

3. Governance and Ethics: How will AI be used responsibly?
Set clear rules for how AI will be managed. This includes things like ethical use, data privacy, security, and who is responsible for wh

4. Choosing the Right Use Cases: Where can AI add value quickly?
Start with a few (usually 3 to 5) projects that are realistic and can make a visible difference. Early wins help build support and confidence across the business.

5. Skills and Training: How will your people learn to use AI effectively?
Invest in training and support. Encourage employees to try out AI in their work, and support “AI champions” who can lead the way. People get more confident and savvy when they experience how AI helps them.

 

Overall: What is a ‘Savvy’ AI User?

A savvy AI user is someone who not only knows how to use AI tools but also understands how to get real value from them. They:

• Use AI tools regularly and with purpose
• Think critically about the results AI gives them
• Come up with their own ways to use AI in their role
• Share what they’ve learned with colleagues
• Build AI into their day-to-day work

These skills don’t appear overnight. They need the right support, time to practise, and a work culture that encourages experimentation and learning. Learning to Think, Not Just Use Tools. Many people find themselves lost on learning the latest AI tools or copying prompts they find online. But this approach has limits.

I often see two types of professionals:

• AI-late users follow tutorials, copy prompts, and wait for someone else to find the best use cases.
• AI-first professionals design their own workflows, think in systems, and see opportunities others miss.

The first group follows a guidebook. The second group understands the map. Tools and platforms will keep changing. The people who succeed with AI in the long term are those who build mental models. This is a way of thinking that applies regardless of the tool being used.

 

In Summary

Adopting AI is not just a technical decision. It is a strategic one. Success depends on more than learning tools. The AI journey requires clear thinking, shared goals, and strong leadership. By building a roadmap, investing in people, and creating space to learn, organisations can go beyond just experimenting with AI, and start making it a core part of how they work.

If you would like to learn more about this topic, feel free to reach out. Perhaps my AI Fit Canvas can be helpful for you: Gain clarity on where AI can add value for you. Use the Canvas to test if the AI use case can be implemented and which questions you have to answer for successful implementation.  You can download the AI Fit Canvas here.