How artificial intelligence will transform Nordic businesses

Artificial intelligence (AI) is set to radically reshape the way companies do business. From retail to healthcare and finance, machines are likely to play a growing role in making companies more efficient, responsive, and relevant to customers’ lives.

Already, AI is the driver behind some of the world’s most profitable businesses, helping technology firms distribute an array of products and services across digital platforms. Companies such as Amazon, Netflix, and Tencent are leading the development, creating personalized offerings that evolve in line with people’s choices and preferences. In the age of AI, industry boundaries become ever fuzzier, with companies forming alliances, even with competitors, and moving into new industries by innovatively leveraging their vast amounts of data and technology.

The reason artificial intelligence is so compelling is its ability to not only process vast quantities of data but also to extract patterns and learn from experience. By being able to accomplish cognitive tasks commonly associated with humans, it creates the building blocks from which companies can build an array of “intelligent” services. AI is an industry-agnostic, general-purpose technology, which in recent years has moved from concept to reality.

We estimate that some 40 percent of the total working hours in the Nordics could be automated by adapting existing technology alone.1A future that works: The impact of automation in Denmark, a joint report from McKinsey and the Tuborg Research Centre for Globalisation and Firms, April 2017. Since AI is driving a substantial part of this automation potential, it will therefore have a major impact on the Nordic workforce in its entirety. However, AI is not only an automation play; it is also an augmentation and enhancement play. It can provide predictions at a scale and depth of detail impossible for individuals and has the power to transform human behavior—the prospect of self-driving cars and computer-based healthcare are not far on the horizon. In the future, we are likely to see many more organizations shaping their activities and business models around AI and data, which will, in many cases, become a key strategic asset. As a result, the onus will be on companies to ramp up their systems and capabilities.

In the Nordics, AI represents a significant commercial opportunity. Kone, for instance, is creating a competitive advantage by monitoring the performance of more than one million elevators and escalators. The company uses AI for predictive maintenance, leading to reduced customer reports of problems by 60 percent. Similar success stories can be found around the world. US-based John Deere is using AI to disrupt the entire agricultural value chain: robots for harvesting, for monitoring crop and soil health, and for tracking and predicting the impact on crop yield. Amazon has opened cashierless stores and is experimenting with autonomous drones for warehouse logistics and last-mile delivery. runs a fully automated warehouse where robots carry out all functions, including product entry, storage, packaging, and sorting, handling up to 16,000 order packages per hour with an accuracy of 99.99 percent.

McKinsey research for this report suggests that exclusively applying the AI techniques we know today can unlock $80 billion in value in the Nordics, equivalent to approximately two to three percentage points in profit-margin uplift (exhibit). These numbers are based on 400 use cases across 19 industries, yet only constitutes the direct impact from currently proven deep-learning techniques and applications. AI should not only be assessed on the basis of its current potential; it also represents a trajectory that creates winners and losers. For instance, a recent McKinsey study simulated that front-runners2 could potentially double their cash flow compared with nonadopters3 by 2030. This is because establishing endowments of data, computing power, and organizational capabilities is needed for harvesting AI’s full potential in the future.

Companies are often investing not only because they can see a definite impact on the bottom line but also because they do not want to miss out on a potential advantage against their peers. Across sectors, companies’ prioritization of business domains indicates that they invest in AI with an aim to capture productivity gains but equally so to drive new business.

To unlock the potential, companies require a strategic step change. Most are currently in the early stages of AI adoption. By investing more, they can capture more first-mover and fast-follower advantage. Indeed, our findings show that first movers and fast followers in AI are already more profitable than the industry average.

Commercialization of AI remains indeed in its infancy. However, laggards should be cautious. Usually, once an industry reaches a tipping point, slow adopters will see significant pressure on margins.

In aiming to become AI leaders, Nordic businesses have structural disadvantages relative to companies in China and the United States. This is largely due to the two countries’ scale and tech clusters, including investment inflow, a superstar talent base, and world-leading hubs. What the Nordics do have is a good starting point for establishing globally leading capabilities to apply AI throughout the businesses. This is manifested in a number of key enablers, such as digital-transformation maturity, an open and agile workplace culture with a flat hierarchy, and an AI-positive, innovative, and adaptable workforce.

The objective of this report is twofold: to provide a fact base for discussion of AI in Nordic C-suites, including how AI is changing businesses, the value at stake, and Nordic businesses’ starting point; and to inspire Nordic companies to succeed, with reference to the characteristics of leading adopters, and put forward concrete actions to take.

Our research on the implications of AI on Nordic businesses leads to a number of key insights:

AI can unlock significant value potential, and early adopters excel:

  • Existing AI domains can unlock $80 billion in value for Nordic businesses, corresponding to a two to three percentage-point uplift in profit margins.
  • On average, early adopters have a profit margin that is seven percentage points higher than the industry average.

AI has not yet reached a tipping point:

  • Front-runners in AI, including advanced industries, automotive, financial services, and telecom, are also generally front-runners in digital.
  • AI diffusion, however, has not reached a tipping point, suggesting that first-mover and fast-follower advantages can still be achieved in most industries.
  • The main trigger for AI investment is competition; rivals’ progress increases the propensity to invest three times more than the perceived value of AI.

Nordic businesses are well-positioned to scale AI and drive innovation within business domains, especially in their stronghold niches:

  • Nordic businesses already have key enablers in place for scaling, including an agile, low-hierarchy workplace culture and flexible employees.
  • Still, Nordic AI investment remains relatively meager and talent is scarce. In addition, the region comprises much smaller “home” markets and does not have vibrant tech hubs like China and the United States do.

Our survey of Nordic CXOs’ views on AI in 2019 suggests that Nordic C-suites may underestimate AI’s impact and overestimate the talent challenge:

  • AI is not a priority on Nordic C-suites’ agendas. While more than three-quarters of businesses are piloting or embedding AI into at least one function or business unit, only approximately 30 percent have rolled it out at scale, and few discuss it on their boards.
  • Nordic C-suites do not expect AI to dramatically reshape the competitive landscape over the next three to five years.
  • The most significant barriers to adoption are a lack of talent, strategy, and technological infrastructure.

Download How artificial intelligence will transform Nordic businesses, the full report on which this article is based (PDF–12.5MB).

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