Why we must overcome fragmentation to optimize AI for the benefit of all

A topic that has come up many times at the World Economic Forum Annual Meeting in Davos over recent years is the increasing fragmentation of our world – within societies and between nations. But, amidst this division and disagreement, there is one hope that many still share: the belief that artificial intelligence (AI) will lead to significant progress across the globe.

From my work at a company that pioneers AI in business processes, I hold this hope too: AI has the potential to stimulate growth and make companies more productive. It can make economies more resilient by helping businesses navigate disruptions – whether through global trade crises, natural disasters or regional conflicts.

AI can also play a critical role in our ability to achieve our sustainability goals, tackle climate change and mitigate its impact. While many recognize AI’s positive potential, the growing fragmentation of our world greatly reduces our ability to take full advantage of the opportunities AI presents.

AI can only be as good as the data it can access and work with. The more restrictions, limitations and political borders we impose on it, the less positive impact AI can have in our countries and companies. AI can’t thrive in a fragmented world. This is what I call the AI progress challenge.

Finding solutions to something as vast and as complex as global fragmentation requires us to divide the problem into smaller, individual challenges that are easier to overcome. How can we make AI a stronger tool for progress? How can we navigate the AI progress challenge step by step?

It starts on our doorsteps – at the level of the individual company. Cloud migration is an integral first step. The cloud makes data accessible for AI, systematically and comprehensively – and cloud solutions can easily (even automatically) be kept up to date with the latest AI innovations. What is more, integrated cloud software offers a standardized environment for data and processes. It makes it easier for companies to keep their data structured, clean and coherent across the company – and consequently easier for AI applications to use.

The second step towards maximizing the potential of AI is to bring individual companies together in an industrial ecosystem. To become more productive, resilient and sustainable, companies need to exchange information with suppliers – sometimes thousands of them – as well as with their clients and innovation partners. In the age of business AI, the need to build intelligent business networks is more important than ever. The more broadly and widely data can be shared between companies, the better and more impactful AI outcomes can be. The whole ecosystem profits in terms of added competitiveness and innovation power.

The third step is to build international frameworks that allow AI innovation to thrive in a responsible way. Governments and regulators can reduce unnecessary barriers to the exchange of data within countries and between countries. In cooperation with industry, public actors can also work towards aligning and harmonizing technological regulations wherever possible, especially between the key economic powers of North America, China and Europe.

At the same time, we must build trust. Lack of trust is perhaps the greatest driver of global fragmentation – and the biggest obstacle to collaboration. By joining forces, international companies can agree on common rules for data usage, data privacy and responsible, ethical AI. Such 'confederations of trust' encourage more frequent data sharing.

The cloud, business networks and a more harmonized global environment based on trust – each of these steps reduces fragmentation and increases federation. And, each of these steps can help the organizations involved reap much greater benefits from AI.

It’s like putting together a 10,000-piece puzzle. It’s not easy to start with and it’s not something that can be accomplished in one go, but if we begin by putting a handful of pieces into place, the big picture gradually emerges. As the degree of federation increases, progress accelerates.

It’s on us to put the AI puzzle together and reduce fragmentation, one step at a time. This is how we maximize the potential of AI – not just for some, but for many.