Why some companies embrace AI and others don't

Many companies look at their competitors with wonder, asking why some are much further ahead with AI than others. What makes some organisations adopt AI faster? Although AI is often seen as a technological decision, the main driver for this adoption is surprisingly simple: economic necessity.

Companies under pressure: why AI is sometimes a pure necessity

For companies operating in markets with low margins and high price elasticity, such as payment providers and insurers, AI is often a lifeline. Take Klarna, for example, which has replaced a large number of jobs with AI applications. Without this step, they would no longer be viable. In sectors where price and demand can change rapidly, and where staff costs are high, the pressure to increase efficiency is enormous. Companies operating in such environments use AI to automate processes, reduce costs, and maintain their productivity.

Insurers are another good example. These organisations are in a 'commodity market,' where products are often seen as interchangeable and price is the deciding factor. By using AI, for instance in customer service or when summarising customer conversations, insurers can improve their service and reduce costs. In such sectors, the difference between success and failure often depends on the ability to control costs while simultaneously offering an efficient customer experience.

Companies with high margins: less urgency to innovate

On the other hand, there are companies with unique products and high profit margins. They have less need to worry about cost savings and are less sensitive to price elasticity. For these companies, the urgency to implement AI seems less pressing. They have a comfortable market share, and their margins protect them from the immediate necessity of far-reaching digitisation or automation.

Yet, a great risk lurks here: once AI offers a proven competitive advantage, it can be dangerous to fall behind. Large companies that currently feel no urgency might one day find themselves in the same position Kodak was in when digital photography emerged. When the market changed, Kodak was too slow to adapt to the new technology, and the company was ultimately overtaken by more innovative competitors.

Innovation as a long-term strategy

The adage "You have to innovate when you can, not when you need to" applies here. Companies that wait to implement AI until it becomes truly necessary risk being too late. Generative AI and language models, for example, can bring enormous efficiency improvements to processes dependent on information and knowledge. The opportunities to save costs and serve customers faster and better are within reach, but require a proactive approach.

Even companies that don't feel the pressure today would do well to start integrating AI now. By weaving AI into their processes, they build resilience for the future. AI can help optimise customer interactions, accelerate internal processes, and increase overall agility.

Lessons from the past

History has taught us that the wave of digitisation and the rise of the internet had similar effects. Companies that thought their unique position would protect them were disillusioned when faster and more flexible companies overtook them. AI is now in a similar phase: companies that look ahead and embrace AI are building a competitive advantage that is difficult to catch up with.

In short, the difference between companies that lead with AI and those that lag behind lies in economic necessity and the willingness to innovate. Those who think ahead are already implementing AI now, not just when the need arises. Only then will organisations remain relevant and competitive in a future where AI will play an increasingly important role.

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