How to move from an AI pilot project to genuine value creation
Most organisations have started using AI. The challenge is no longer to start using the technology, but to ensure it creates real value. The problem is that AI often remains confined to pilot projects and technology initiatives, rather than transforming working methods and processes, which is where costs, revenues and the business itself actually lie.
AI is currently used for a variety of purposes, including customer service, analytics, product development and automation. However, international surveys show that over half of companies struggle to identify a clear financial return on their AI investments.
We need to progress beyond the initial phase, which involves smaller innovation groups.
This is not particularly surprising, according to Martin Körling, head of the data analysis unit at RISE.
‘Setting up a pilot project alongside the main business isn’t difficult. However, it won't generate any new revenue or result in any change in costs for the main business,” he says.
Many organisations begin by establishing small AI teams or innovation groups to explore the technology. This is a natural first step.
‘But you have to get past that.' In order to move forward, you have to integrate this expertise into your operations,' says Martin Körling.
He also believes that this is where many AI initiatives get stuck. Value is only created when AI influences an organisation's working methods and core processes.
‘It is the managers in the core business who need to start thinking about how AI can be used in their processes,’ says Martin Körling. That’s when things will start to happen,” says Martin Körling.
Integrating AI into core business operations requires more than just new tools.
However, transitioning AI from pilot projects to core operations is a complex process that requires more than just purchasing licences for new tools.
According to Martin Körling, organisations need to understand how developments in AI are changing their operations. They must also have the courage to challenge existing processes, identify which parts can be automated and grasp how their products and services create added value.
At the same time, the standard of data, security and infrastructure must be high enough. To scale up the use of AI, organisations also need to understand the risks and regulatory framework, and learn how to use the technology responsibly.
The ease with which AI can be implemented does not necessarily depend on the size of a company. The difference is often greater between organisations where data is already available and those that first need to digitise their processes.
‘If you run a sawmill and haven’t started collecting data, you might need to begin by taking photographs of your logs. Based on those pictures, you can then do lots of interesting things,” says Martin Körling.
In order to move forward, you have to integrate this expertise into your business.
Value and return are not the same thing.
The discussion about AI often centres on return on investment (ROI). However, value and return do not always align in the short term.
‘You can improve the product by doing things in a new way, but you still can’t charge more for it. Even if it isn’t possible to quantify it initially, it can still be incredibly important,' says Martin Körling.
Nowadays, AI is often considered separately – as a project, a pilot scheme or a specific function.
Martin Körling believes that, in the long run, this division will disappear.
He compares this development to how the internet has transformed businesses and organisations.
‘When the internet first came along, it was seen as something separate. Now, however, it’s built into everything, he says.
Spotify is a prime example of what the future might look like. Although recommendations, playlists and other features rely heavily on AI, most users don’t give the technology behind them a second thought.
‘There is no “AI” button in Spotify. It’s deeply integrated into the product, which you simply experience as being better: more precise and in line with your tastes and expectations,” says Martin Körling.
Assessing the maturity of AI can help to identify the next steps.
For many organisations, carrying out an AI maturity assessment can be the first step towards understanding their current situation and identifying their next steps.
According to Martin Körling, understanding the business is as important as understanding the technology.
Among other things, RISE helps organisations understand the impact of AI on their operations, identify new working methods and develop prototypes to facilitate the testing of ideas in practice.
At the same time, RISE's expertise covers everything from industry and energy to forestry. This enables AI issues to be linked to the specific operations in which the technology is to be used.
“We can talk about AI technology itself. But we can also discuss how it affects businesses,” says Martin Körling.