Swedish companies lag behind in AI maturity

AI has moved from the pilot stage to be a major profit driver. But even though the technology has matured, only 12 percent of companies globally have managed to make AI a natural part of the business. This is according to a new report from Accenture.

If just a few years ago AI was a new technology being tested at the pilot stage, today it has matured significantly.

- Take something like the facial recognition that unlocks an iPhone, it's based on AI. Or when energy companies monitor power lines to detect problems with, for example, fallen trees, it is based on AI. The whole society today is full of AI solutions that we don't think about, it's part of our everyday life, says Per Österman, Nordic responsible for the Applied Intelligence business area at Accenture.


Three requirements for enterprise AI maturity

According to the report "The art of AI maturity - advancing from practice to performance" from Accenture, it is also clear that AI within many companies has reached a stage of being a mature technology, which also has a large impact on both the company's earnings and market value. However, what is also clear from the report is that while virtually all companies today are looking at AI as an opportunity, only about 12 percent of the 2,000 companies, globally, surveyed in the report have succeeded in making AI a natural part of the business. 


- What I think becomes very clear in this report is that successful AI use is only to some extent about technical investments, says Per Österman.

Instead, three factors must be in place if AI is to become the value-creating factor it has the potential to be.

The technical basis for data flow is the foundation

The first of the three is of course the technical base.


- The basis of AI use is about how good you are at finding and using the right data in a meaningful way. Therefore, you must have some kind of technical platform that allows you to both collect and disseminate data in the organization simply and cost-effectively. It is often about cloud solutions. 


Focus on value is crucial

But having the technology in place is not enough. The report shows that while the companies that have invested heavily in technology infrastructure are getting some leverage on that investment, they are still far from the leaders when it comes to getting value from their investment.

- The other part you must have in place is the focus on value. Both management and employees must understand how technology can be used to create value for businesses and customers. And although it may take one or two years to build the technical solution, you can start focusing on value creation right away. For example, build a battery with a case that makes the organization understand the need both now and in the future, so that you are ready the day the technology is in place.


Industry know-how plus AI training are important pieces of the puzzle

For that to happen, however, a major investment is required in the third focus area: the ability to adopt both the technology and the way of thinking, both in the organization as a whole as well as in the individual employee. And for that, education, training, and organizational changes are required.

- Companies need to raise the knowledge level of their staff, both in terms of technical and business awareness of what AI and data can do. Today, unfortunately, many people forget this part, but if companies can train personnel who already have the extensive industry knowledge and get them to understand the opportunities AI provides, it can make a big difference.

But it is not enough that the staff has the right skills, they must also be allowed to work in an organizational structure that enables data to flow through the company. 

- What many people are doing now is trying to push the technology of the future into yesterday's organizational models, but it doesn't work. The organization must adapt, otherwise, the investment in AI becomes just a cost item that does not generate expected values. For every penny you spend on technical investments, you must spend an equal amount on change work. 


Six out of ten companies do not receive any exchange

However, for those who do it and get all three parts to fit together, there are great opportunities to go from using AI in pilot studies to scaling up the use and into regular operations. But the opposite is also true.

- The report shows that six out of ten companies are still unable to move from the pilot stage to full-scale use. They get insights, but no results on the bottom line. 

Unfortunately, Per Österman believes that many Nordic companies are within this group, and during the autumn Accenture will conduct a major study on this. 

- The feeling today is that Nordic companies are unfortunately a bit behind other markets in Europe when it comes to collecting relevant data in cloud solutions and thereby accelerating their AI maturity. They have been satisfied with what they have had and have not shifted to cloud solutions at the same pace.

The good news is that if the company enters a data-driven transformation and focuses on creating value through advanced analytics and AI solutions at an early stage while investing in its journey to the cloud, it can help finance the transformation. 

- It's about connecting data with business, but also about connecting business with data. And it is the second area that is often the most difficult challenge.