Europe's Advantage Lies Not in Lower Costs, but in Greater Capabilities

Digital transformation, artificial intelligence, decarbonization, and talent: these are words that company leadership hears every day. But where are the concrete results, the numbers, and the pitfalls? We discussed this at the Manager Association Congress with Swedish digital transformation and artificial intelligence expert Claudia Olsson, founder and CEO of Stellar Capacity.

These days, many are worried that artificial intelligence will take away their jobs and livelihood. But let's flip the script: where do digital solutions truly help people and companies? Where does technology already bring concrete results, higher sales, faster service, or better products?

Digital transformation yields the best results when it empowers people rather than replaces them. The most effective outcomes come from “augmented intelligence,” where technology acts as a co-pilot to human expertise.

A clear example is software development. When engineers use AI tools like GitHub Copilot, their productivity increases by about 20–26 percent. A study involving over 4,000 programmers shows that projects are completed faster, quality remains stable, and developers report greater engagement at work. This is a concrete, measurable result: fewer delays and greater satisfaction among highly skilled professionals. The broader message is that when people and artificial intelligence work together, performance improves across all sectors.

Trust: “The foundation of any digital transformation. Without it, the adoption of technology fails, no matter how advanced it is. The key principle is clarity. People must always know when they are communicating with an algorithm and how their data is being used.” PHOTO: Shutterstock

A similar effect is seen in services and sales. Companies using generative artificial intelligence to support customer interactions report about a 15 percent increase in agent productivity and a 15 to 20 percent increase in customer satisfaction. The improvement is not just in greater efficiency; people get faster and more relevant answers, and employees use their time to solve more complex tasks with higher added value.

At the same time, increasing automation will inevitably reshape many professions and industries. New professions will emerge, some will disappear, as has always happened with technological advancement. The key is how individuals and organizations prepare. Instead of fearing new developments as disruptions, we should invest in future knowledge, learn to work with new technologies, and seek practical ways to harness their potential.

Ethical boundaries and questions are also very relevant. Which ethical boundaries would you never cross? Which principles should we never abandon?

Trust is the foundation of any digital transformation. Without it, the adoption of technology fails, no matter how advanced it is. The key principle is clarity. People must always know when they are communicating with an algorithm and how their data is being used. Hidden automation undermines trust. Open systems build it.

For me, human oversight, fairness, and explainability are not choices but necessities. These are the reasons technology continues to work for us, not the other way around.

Which measurable indicators most clearly show that digital upskilling is worth it?

Investing in knowledge yields faster results than most leadership teams imagine. Evidence from various sectors is consistent: the return comes within the first year.

First, there is productivity. The World Economic Forum reports that two-thirds of employers see a positive return on investment in upskilling within less than twelve months.

Second, this helps retain staff. Gallup data shows that organizations prioritizing development are twice as likely to retain employees. People who learn are engaged and motivated; learning signals that leadership is investing in their future. The cost of replacing skilled talent is significantly higher than the cost of training them.

Learning: “Learning and creativity will be the most important skills in 2030.” PHOTO: Shutterstock

Third, there is the speed of innovation. Studies we have reviewed show that teams dedicating just a few hours a week to learning new tools report shorter project cycles and find solutions faster. They are better at using AI assistants, automating routine tasks, and freeing up time for creative work.

What should be Europe's priority by 2030, and where are we losing compared to the USA and China?

Europe stands at a crossroads. Our advantage is innovation based on values, connecting technology with trust, ethics, and sustainability. The European Union's human-centered approach to digital transformation, grounded in transparency, data protection, and responsible artificial intelligence, can be our competitive advantage. It has the potential to create systems that people trust and widely adopt.

We also lead in the green transition. The EU has set a goal to become the first climate-neutral continent by 2050, with an interim goal of at least a 55 percent reduction in emissions by 2030. Already, 92 percent of European companies are investing in reducing emissions and energy consumption, faster than in the USA. Strong cross-border data centers are emerging for collaboration in energy, mobility, and production, forming the digital core of Europe for sustainable growth.

We lag in speed and scale, facing competition from two very different directions. Last year, the USA attracted approximately $109 billion in private investments in artificial intelligence, nearly twelve times more than China. Their advantage is the concentration of capital and venture capital ecosystems investing in such projects.

Meanwhile, China excels in scale and speed. Today, it files about six times more patents in generative AI than the USA and has built a national innovation system with 156 institutions producing significant AI research, while in Europe, it is still concentrated in a few leading centers.

The USA leads in capital, China leads in research efficiency and the ability to scale ideas into applications. If Europe wants to lead by 2030, it must close this execution gap while leveraging its unique strengths and advantages.

You come from Sweden, which has strong digital foundations. Which part of the vision has been realized faster than expected in Sweden, and where are you lagging?

Yes, we almost have a universal digital identity in reality. Its key pillar is BankID, the national digital identity system that allows individuals to securely verify their identity online. Today, more than 8.6 million people use BankID, and thousands of services in the public and private sectors rely on it. This trusted digital identification layer has made public services simple and secure while accelerating innovation in sectors such as fintech and digital health.

Future Leaders: “The next generation of leadership will be less hierarchical and more inclined to connect, agile, and informed.” PHOTO: Leon Neal Via Reuters

Digital transformation driving sustainability has progressed faster than expected. In Sweden, digitized manufacturing and pilot projects in precision agriculture simultaneously increase efficiency and reduce emissions. Agricultural trials, for example, show up to a 16 percent lower carbon footprint. Productivity and environmental protection progress hand in hand.

However, we lag in closing two key gaps. First, in the adoption of technology by small and medium-sized enterprises. Large companies use artificial intelligence on a large scale. Small businesses are still lagging behind, mainly limited by knowledge and execution. Second, we lag in talent. Although the overall talent pool in AI and engineering has expanded, there is a shortage of top experts with knowledge in areas such as AI integration, data architecture, and cybersecurity. These highly specialized skills remain rare and create bottlenecks in organizations looking to move from pilot projects to scaling.

Where does AI generate revenue the fastest today?

We have surpassed the experimentation phase. Generative artificial intelligence is moving from promises to results, and we now see where it creates real value and where it still needs to mature.

The fastest results are in customer support. AI assistants handle repetitive questions, freeing human agents to solve complex cases. Early adopters achieve up to 30 percent lower support costs and faster claim resolution because AI takes over basic tasks. The real profit is better use of human time.

Next is software development. AI copilots increase programmer output by 25–30 percent and shorten development cycles from months to weeks. This is productivity that directly supports innovation.

Next are sales and marketing teams. Automatically drafting initial emails, proposals, and presentations helps teams focus on relationships and strategy. It’s not about replacing creativity; it’s about enhancing it.

Where progress is slower, people are the missing link, not the obstacle. Open, creative work still requires judgment, taste, and collaboration. Large-scale automation fails without clear ownership or training. Therefore, the next wave of transformation is primarily human and organizational, not technical. The key skill is learning to work with AI – how to ask the right questions, verify results, and turn data into insights. Skills like curiosity, communication, and critical thinking drive success today as much as technical skills.

How would you connect universities, companies, and the state to enable new experts to achieve full productivity in six to nine months?

Learning and creativity are the core skills we will need by 2030. To foster them, universities, companies, and the state must set common goals. Universities teach learning and problem-solving skills, companies introduce new hires to concrete projects with clear outcomes, and the state rewards partnerships that bring faster paths to productivity. Studies and work should be connected from day one, and students' final projects should be linked to real business challenges.

Careers are evolving today, and people will need to constantly adapt to new challenges and transition between roles and industries through reskilling programs. The upcoming workforce will need continuous training and knowledge upgrades. Many people will need to connect diverse life experiences and knowledge with new technologies. We will likely see more intergenerational collaboration with programs that include people of all ages and backgrounds, bringing fresh perspectives to common challenges. Universities and organizations will need to work more closely together to create pathways that allow employees, regardless of age, to remain agile and competitive.

Many large companies are reducing the number of new hires and therefore hiring fewer graduates. Law firms are automating document review and drafting initial drafts. This practice is short-sighted. It brings short-term savings but eliminates the training ground where future leaders are developed. The answer is not fewer beginners but smarter apprenticeships where AI is integrated into the process.

The state should help companies, not hinder them. Which steps in public administration would, in your opinion, most quickly stimulate new private investments?

The state sets the pace of innovation. When public systems are fast, secure, and transparent, private investments follow. The low-hanging fruit is not new technologies but the smart use of what already works.

The first key factor is digital identity. Countries with secure, universal digital identities reduce transaction costs for citizens and businesses. Swedish experiences show what is possible: seamless access, faster approval, and greater trust across various sectors. For companies, this means faster contract signing, quicker onboarding processes, and faster payments, all of which are growth factors.

The second important thing is common data standards, allowing companies to connect once and operate everywhere. Estonia and Finland already seamlessly exchange tax and customs data, saving time and reducing the risk of fraud.

The third is digital proof and compliance. When certified data replaces physical documentation, investments move faster. Converting approval cycles from months to days creates liquidity and trust. Progress should be tracked in ways that are understandable to everyone. Important factors are speed (how long it takes to complete key business transactions), connectivity (how well public systems communicate with each other), and trust (the proportion of private investments conducted through digital public systems).

What would you advise the management of a large exporter regarding the allocation of investments in decarbonization, digitalization, and talent?

The next three years will show how quickly purpose and performance can align. Leading companies will be those that treat people, technology, and sustainability as a unified system, not as three separate priorities.

My basic allocation would be 40 percent in talent, 35 percent in digitalization, and 25 percent in decarbonization. Human capability is a multiplier. Every technology and every sustainability goal depends on people who can connect ideas and lead through uncertainty. These skills – curiosity, communication, and collaboration – will largely determine how far and how fast organizations can move.

The next generation of leadership will be less hierarchical and more inclined to connect, agile, and informed. Knowledge will be transferred both horizontally and vertically. Decision-making will shift from chains of approval to empowered teams. This is how organizations maintain pace in a world of exponential change.

Technology and regulation will continue to evolve, but human adaptability will decide who leads. Europe's real export advantage is not lower costs but greater capabilities. The ability to learn faster, collaborate smarter, and create lasting value will define the future era of leadership.