Higher ROI on AI in the Nordics

Higher ROI on AI in the Nordics

Erik Larsen

Erik Larsen,

In November 2019, Cognizant published a survey done among managers about technology and digital transformation. Over 2,400 tech and business leaders from all over the world participated. The survey revealed a number of interesting Nordic findings.

According to the survey, the Nordic participants report a higher ROI for AI investments than the global average. Why is this important? It’s essential because almost nine out of ten leaders in growing businesses states that AI is extremely or very important for their company’s success. 

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Yet, four out of ten tech leaders see it as challenging to get their managers to agree on AI investments. This indicates that many leaders still aren’t convinced of the importance of this specific technology. 

For those wanting funds for investments, it could be smart to show practical examples of the value and pay off from such technologies. AI is known for providing the most value when it is utilized to support humans making decisions in a proactive way. That’s why top management should be able to experience how it works. 

Cost Savings Not No. 1
For those who want to profit from artificial intelligence, these eight points might be helpful:

  • Knowledge and strategies: Many companies lack a clearly defined AI strategy and are insecure about how to meet changes. Therefore, it is critical that they develop a basic understanding of AI and set a clear AI strategy. 
  • Business targets are important: This is common sense and might sound logical, but a lot of businesses end up in the “technology trap” with AI. That’s why the question “What challenges or opportunities do our business have where we can utilize AI?” is important – in contradiction to “What will IBM Watson or Amazon machine learning be able to do for us?”
  • Test, learn and get better: Developing solid solutions demands experimenting, the ability to learn from your mistakes and utilize the learning in the next phase of the project. A company should encourage new thinking and balance that with testing the solution regularly and often, in addition to measuring the value the solution creates.
  • Cost savings aren’t the most important goal: Companies often think of AI as a tool for reducing costs, and that is certainly a key benefit – one that tops the list for executives in the survey. But there is a vast range of other potential business benefits to consider as well. If executed correctly, AI can help improve product and service quality, reduce time cycles, create new and better employee experiences and enhance safety, among other things. Our recommendation is therefore to see past “cost reduction” – and to have an open mind when exploring the ocean of possibilities enabled by AI.
  • See opportunities in data: Humans will quickly have trouble understanding and interpreting data because of the massive amount of it. AI technology can help us with just that: to understand, interpret and see connections that in the end lead to valuable business insight. 
  • Understand the big picture: Underlaying algorithms must “understand” the larger context they are operating in. If they are not built to do that, you could for example risk that the technology will give the right suggestions but at the wrong time. Teams across departments that identify opportunities in a systematic and structured way, will contribute to seeing the big picture, uncover faulty sources and find improvements. 
  • Get a second opinion: Good partners is an especially important part of an AI strategy. External knowledge can add skills and experience in a fast and safe way and give the business knowledge about how AI technology creates competitive advantages. 
  • Adopt a human-centric approach: The most important part of an AI strategy is to put the humans at center of it. Not the technology. That is why you should ask questions like “how can AI support and create new opportunities for our customers and employees?”, “How can we make sure the technology interacts with and cooperates with humans in the best way?” and “How can we equip technology with enough ‘emotional intelligence’ to make it adapt its decisions to humans?”.


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