Almost every organisation sees the potential of AI, yet only a few succeed in making it work in practice. Significant investments are made in pilots, policies and tools, but the expected return often fails to materialise and reality disappoints. Research by MIT shows that an estimated 95 per cent of AI projects fail to scale successfully. Where does it go wrong? We often see what is known as Shiny Object Syndrome. A tool is purchased because competitors are doing the same, and only then does the search for a problem begin. The result is a polished AI pilot that automates a task nobody actually cares about. Or a tool that nobody dares to use because its outputs are not trusted.
Why does AI rarely move beyond the pilot stage?
The cause does not necessarily lie in the technology itself, but in how AI is implemented. Organisations often underestimate what is required to deploy AI properly. Many AI applications are easy and quick to roll out, and that speed can lead organisations to overlook the human, technical and organisational aspects.
In many organisations, there is a strong focus on compliance. With the AI Act, the GDPR and increasing European regulation, the responsible use of AI has become an essential condition. But compliance alone does not make AI a success. Most AI initiatives stall at the same point. There is enthusiasm, there are ideas and sometimes even pilots, but the step towards structural deployment is never taken. Use cases are poorly defined, the value for the organisation is unclear, stakeholders are not involved and the organisation is not ready for change. As a result, AI remains an experiment rather than becoming an integral part of day-to-day operations.
Responsible implementation
The Certified AI Lead Implementer (CAILI®) programme was developed to address exactly this challenge. CAILI® is aimed at professionals responsible for embedding AI sustainably and responsibly within their organisations. The focus is on making the right choices. Which problems are suitable for AI, how do you ensure that AI contributes to organisational objectives, and how do you take the organisation with you?
The emphasis is not on blindly applying technology, but on answering the crucial how questions. One of the biggest misconceptions is that AI replaces jobs. In reality, AI replaces tasks, not people. That is why it is important to look beyond what is technically possible and focus on where processes get stuck. Effective AI applications target tasks with high frequency and low variation. Think of summarising files, categorising customer enquiries or carrying out an initial review of contracts. The success formula is not automation as such, but balanced collaboration between people and technology. AI does the repetitive groundwork, the expert completes the job.
Chicken or egg?
In practice, it is not uncommon for organisations to purchase a licence first and only then consider what problem they want to solve. They may have a Copilot or ChatGPT licence, but are still searching for a concrete use case.
Successful organisations reverse this logic. They start with a clear and measurable business objective and then assess whether AI is the right tool. If the business case cannot be substantiated in advance through time savings, quality improvements or cost reductions, there is a strong chance it will never progress beyond the pilot phase.
Then there are the employees. A solution may be technically excellent, but if employees are unconvinced or feel threatened, failure is inevitable. Implementation therefore goes hand in hand with change management. This means being transparent about what the tool can and cannot do, demystifying AI, and training employees to work effectively with it. Once employees experience that AI does not replace them, but takes over tedious tasks so they can focus on their expertise, resistance turns into enthusiasm.
What successful organisations do differently
Organisations that successfully use AI today do not stand out because they have better models. On the contrary, access to fast and high-quality models has never been easier, even with modest investment. What sets these organisations apart is their implementation process. Clear problem definition, starting small, controlled testing and responsible scaling. Taking compliance into account during selection is not an obstacle, but a framework that provides clarity. CAILI® professionals play a key role in this process.
This does not mean that compliance is secondary or less important. Quite the opposite. Without proper governance and oversight, AI cannot be deployed sustainably. Our CAICO® and CAILI® programs complement each other, but serve different purposes. CAICO® ensures that AI can be used responsibly, while CAILI® ensures that AI is actually implemented and continues to deliver value.
The fact that many AI projects fail is not a reason to hold back, but a reason to think more carefully about responsible implementation. AI requires not only vision and rules, but above all people who know how to implement it responsibly, effectively and across the organisation. The question is not whether you use AI, but whether you implement it properly.
Would you like to help organisations successfully implement and scale AI projects? Then follow our Certified AI Lead Implementer (CAILI®) programme.
CAILI® programme
