Value of (Generative) AI

Artificial Intelligence is bringing about a total transformation of the organisation, and at the tipping point of that transformation, many traditional conventions are falling overboard. What doesn't change is that organisations still face the question of how to create value – now and in the longer term. That question must remain central to the deployment of AI.

Superlatives fall short when it comes to outlining how significant the transformative power of AI can be. For example, AI delivers insights we cannot generate as humans, from new molecule structures for crops that can deal with climate change to predicting the maintenance needs of machines. AI makes it possible to make decisions at a speed and scale previously unattainable. AI can turbocharge the productivity of human effort tremendously, freeing up humans for other tasks. AI can communicate in ways virtually indistinguishable from a human. We could go on and on in adulating these promises.

However, that is not the most sensible way to get a good idea of the value of AI. For that, it is important not to reason from the temptations of technology but from its relevance to the organisation. 

Every organisation essentially has the same mission: to create value. For customers, for employees and/or for other stakeholders. There is no debate about that, even in an era where AI is increasingly playing a leading role. Anyone who wants to remain successful in the long run must therefore reason not from the technology itself but from the question of how to deliver value to employees, customers and other stakeholders. How you can remain relevant to them. And only then can you consider how technology can help with that – in that order. 

That old wisdom remains in full force. But on the flip side, all sorts of other wisdom will be completely overturned. One such old wisdom is that you have to have data and systems in order to optimally generate value with digital technology and prioritise AI use cases. However, such a sensible approach clashes with the laws of the AI era where you have to be able to react at the speed of light. If a startup gets something done, you can't be left behind.

Another old wisdom is that you need to understand how (AI) models and systems work and can use them to show what trade-offs are involved in a decision. This wisdom also runs into limitations. After all, what if an algorithm does very well but it is unclear why? Can you then afford to be left behind?

Yet another piece of wisdom is that humans are the superior party in the cooperation between humans and machines. Is that wisdom still tenable? And is it perhaps time to say goodbye to the idea that humans are always the distinguishing factor? 

These and numerous other questions make it clear that it is essential to keep reasoning from the question of how to create value as an organisation. This is precisely why AI belongs primarily on the agenda of the business. And that the business must be imaginative and dare to venture off the beaten track. Meeting customer expectations is not enough, because customers often do not know what they want. In a figurative sense, a customer is not buying a drill but a hole in the wall. Indeed, they are buying a solution to hang a painting. With that view, the business has to keep looking.

Those who master that will have an excellent foundation to be – and remain – relevant and successful, even in the era of AI.