Artificial intelligence (AI) requires breaking silos

More and more organisations are investing in artificial intelligence (AI) to make decisions faster, smarter and in a more scalable way. AI can help recognise patterns, predict behaviour, or even perform routine tasks automatically. And that is exactly what is needed at a time when customer expectations are rising, workloads are increasing and processes are becoming more complex.

But one structural blockage remains stubbornly present: organisations divided into silos. AI offers wonderful opportunities, but it only works in organisations that are also organisationally ready for it. Building yet another dashboard with yet more indicators and dates is rarely the solution. What is needed: breaking through silos, collaborating across departments, and thinking integrally about processes, information and decision-making.

AI as an engine for better decision-making

AI technology offers enormous potential. In healthcare, for example, AI is being used to predict risks of readmission. Government organisations are using it to automatically process permit applications. And commercial companies are applying AI to segment customers in real time and offer personalised services. The promise is clear: better decisions, on a larger scale and in less time.

Yet AI works well only if a number of preconditions are met. Organisations must have access to the right data - and across the board. There must be clarity about decision rules and the goals of the process. And perhaps most importantly: there must be no walls between departments, systems or people. And let the latter be the biggest stumbling block.

The silo problem: Who actually owns the decision?

In many organisations, processes and information provision are compartmentalised. ICT manages the systems, legal affairs defines the frameworks, departments manage their own data, and communication is in yet another bubble of its own.

As a result, AI initiatives often founder in experiments or are limited to one department. Discussion arises about ownership: who has the final say on the algorithm? What data can be used - and by whom? The problem is not in the technology itself. AI is not the problem - organisational structure often is.

Digital transformation requires collaboration, not technology

Digital transformation is not about technology, but about value creation, collaboration, processes and people.

This requires a different way of thinking and organising. No longer reasoning from departments, but from chains. Not just looking at functions and roles, but at responsibilities across the entire process line. And not from systems, but from steering on goals and performance.

The solution: work on your digital maturity

How can you break through this persistent silo problem and successfully deploy AI? The TIMAF Maturity Model provides a concrete and practice-oriented framework.

In this model, an organisation develops along five levels of digital maturity. The focus is on strategy, organisational culture, process-oriented work, information quality and technology.

Organisations that go through these steps have a common language for data and processes. They steer by chain-wide performance indicators (KPIs) rather than departmental results. They know which decisions are suitable for automation - and which are not.

And perhaps even more importantly, they don't leave AI to “the tech department,” but integrate it into their service delivery and organisation-wide decision-making.

Check your Digital Maturity

AI offers wonderful opportunities, but only works in organisations that are also organisationally ready for it. Building yet another dashboard is rarely the solution. What is needed: breaking silos, collaborating across departments, and thinking integrally about processes, information and decision-making.

👉 Want to know where your organisation stands? Check out the TIMAF Maturity Model or contact us for a maturity analysis or workshop.