AI is a cap­ab­il­ity – not a busi­ness strategy

A text that once took an hour to write can now be produced in a matter of minutes. Large volumes of data that employees previously spent days analysing can now be processed in a fraction of the time. Like a powerful high-speed train, AI has arrived in Denmark and rapidly made its way into the business landscape.

Yet while many companies have boarded the AI train, only a few have cracked the code on how to turn the technology into genuine business value. This is one of the key findings of a study conducted by Professor Torsten Ringberg and External Lecturer Per Østergaard Jacobsen from the Department of Marketing at Copenhagen Business School.

There are several reasons for this. One of the most significant is that many organisations mistakenly begin by developing an AI strategy and then attempt to impose it on their existing organisation and way of working.

“The reality is that it is very difficult to create value simply by layering new technology on top of existing practices. Organisations typically need to start by examining their business processes and asking: ‘Can we do something differently that enables us to use AI in a way that changes how we go to market and interact with customers? Where can AI support these ambitions, and where can it not?’ AI should be regarded as a capability that supports a company’s broader business strategy,” says Per Østergaard Jacobsen.

Bring the employees along

Another challenge associated with AI is the significant gap in adoption across organisational levels. While 70 per cent of managers use AI in their work, the figure drops to just 32 per cent among employees. At the same time, only 11 per cent of the workforce has received formal AI training.

If AI primarily becomes a tool for senior management and a handful of early adopters, organisations will struggle to realise its broader business benefits. Without training and a shared understanding of what AI is meant to achieve, companies risk creating an organisation in which some employees move quickly with the technology while a large proportion are left behind. This may help explain why 47 per cent of employees in Torsten Ringberg and Per Østergaard Jacobsen’s study do not believe AI should be used in their organisation.

“It is not necessarily a sign of technology resistance. Rather, it is likely a reflection of the fact that many employees are neither trained in AI nor involved in discussions about how the technology is being used and for what purpose,” says Torsten Ringberg.

When AI becomes an actor

With the rise of AI, Danish businesses have effectively gained a new colleague: the AI agent. Unlike a chatbot, an AI agent is an autonomous software programme powered by artificial intelligence that can operate independently over extended periods and carry out entire workflows without continuous human intervention.

It may sound almost too good to be true. And organisations that fail to understand the limitations of AI agents risk running into problems.

“With AI, factors such as machine readability on a company’s website become critical. If a landing page is not structured in a way that allows AI agents to interpret it, a company may not even be considered when customers search for products,” says Per Østergaard Jacobsen.

It is also important to recognise that AI agents are not like trusted colleagues who can always be relied upon to approach a task in the same way. When it comes to the strategic mindset they bring to a market, AI agents can be unpredictable.

“Agents have a mindset, but only until they switch to a different one. Organisations need to understand this and remain aware of it when prompting AI from one interaction to the next,” says Torsten Ringberg.

According to him, this illustrates the respective strengths and limitations of humans and technology, and, perhaps more importantly, what they can achieve together.

“This is what we refer to as hybrid intelligence: humans and AI complementing one another to create outcomes that neither could achieve alone. Humans provide direction, evaluate quality, and decide what can and cannot be delegated, while AI agents execute tasks, deliver real-time analysis, and scale the decisions made by humans,” says Torsten Ringberg.

From investment to real value

Tobias Laursen, Project Leader at Boston Consulting Group (BCG), who advises major companies on topics including digitalisation and artificial intelligence, recently shared his perspectives at the CBS event Leadership in the Age of AI: Strategy and Business Potential on the biggest challenges Danish companies face when it comes to turning AI investments into tangible business value.

“There are fundamentally two factors that challenge companies’ ability to make investments that genuinely create value. The first is the need to increase both the focus on and the effectiveness of those investments that can generate value at scale. The second is the need to ensure a strong focus on value realisation, so that organisations have confidence that increased IT investment will ultimately pay off,” says Tobias Laursen.

The biggest challenge is about people

The greater business potential does not lie solely in giving every employee access to a new tool. It lies in examining which parts of the business can be reimagined. And the path to getting there is far from being only about technology. BCG uses the so-called 10-20-70 model to illustrate where the real work takes place.

“We often say that 10 per cent is about data and algorithms, 20 per cent is about technology and 70 per cent is about people, processes and the organisation. As this clearly shows, it is very much about change management,” says Tobias Laursen.

This means that leaders in Danish companies have some clear tasks ahead of them if they do not want to be left standing on the platform as the AI train continues to gather speed. BCG has recently examined what leaders in the companies that are most successful at converting AI into business value are doing differently. 

Five factors stand out in particular:

- Set an ambitious AI direction from the top that is closely linked to concrete business outcomes.
- Allocate investments across adopting AI tools, rethinking processes and creating new business opportunities, with the greatest emphasis on the latter two.
- Establish an AI-enabled organisational and collaboration model with close interaction between the business, IT and external partners.
- Rethink workflows and processes, and equip employees with the skills needed to work in new ways.
- Make the organisation AI-ready, ensuring that employees embrace the technology and that culture and strategy support one another.