AI solutions are appearing on the agendas of more and more organisations, but implementing them is not always straightforward. Many encounter the same challenges – often unnecessarily. Introducing AI is not merely a technical project; it represents a shift in organisational culture and requires determined leadership. When these challenges are addressed systematically, AI can genuinely drive business growth, efficiency, and renewal.
We have identified four common challenges organisations face in adopting AI. Fortunately, there are clear and accessible solutions to all of them.
Challenge 1: Rebuilding environments repeatedly and losing control of costs
When AI solutions are developed without a shared technical foundation or governance model, it often results in each team or project building its own environment. This leads to duplicated services, fragmented technologies, and unnecessary costs.
With a centralised approach to AI development, individual experiments become part of a broader strategic framework. This enables efficient use of resources, clear oversight, and faster progress. A shared technical foundation and governance model support scalability, reduce redundancies, and ensure that AI solutions deliver tangible value to the business.
Challenge 2: Neglecting cyber security and increasing risk
Leveraging AI requires responsible and secure data management. When cybersecurity is neglected, risks grow: confidential information may be mishandled, trade secrets exposed, and access management left incomplete.
Clear data governance, defined access rights, and a secure infrastructure ensure that AI operates responsibly and ethically. This not only protects the company’s assets but also enables wider and safer adoption of AI across the business.
Challenge 3: Fragmented practices make maintenance impossible
If every AI project follows its own rules, the result is technological chaos. Maintenance becomes difficult, learning slows down, and best practices fail to spread across the organisation. This prevents AI from scaling and stifles innovation.
Unified ways of working and clear governance enable efficient development, continuous improvement, and long-term business support. This foundation fosters innovation and ensures that AI does not remain a series of isolated experiments but evolves into an integral part of the organisation’s daily operations and strategy.
Challenge 4: No one owns the big picture, and rules are missing
Without shared principles and a governance framework, the AI landscape can easily become fragmented. Responsibilities blur, decision-making slows, and progress stalls. AI is not just a technical issue, it is also strategic and ethical. Without a holistic view, it is nearly impossible to measure the success of AI initiatives or the impact of AI adoption.
When AI development is guided by shared principles and a clear governance model, roles and responsibilities are well defined. This supports strategic decision-making, fosters collaboration, and ensures that AI solutions align with the organisation’s values and objectives.
Four challenges, one solution
Harnessing AI is not only about technological choices, it’s about the organisation’s ability to act cohesively and purposefully. When environments are built on a shared foundation, data security is taken seriously, ways of working are harmonised, and the overall effort is clearly led, AI becomes a strategic asset. Read more about our AI Landing Zone service!
