AI pioneers dare to experiment, innovate – and fail

Finland’s progress with AI isn’t limited by technical capability but by cultural barriers like risk aversion and perfectionism. Many Finnish industrial organizations might fear failure and wait for perfect solutions before taking action, missing opportunities to explore AI’s potential. Small-scale trials are the key to progress, helping businesses identify what works and enabling them to iterate quickly. Kostiainen argues that bold experimentation is critical for uncovering scalable solutions that drive competitiveness and growth.

Adopting AI successfully requires more than technical tools; it needs a solid foundation. Kostiainen emphasizes the importance of investing in dedicated AI teams that are fully integrated into business operations, supported by high-quality data, robust data management practices, and a strong organizational data culture.

Kostiainen continues by highlighting that setting clear goals is equally vital. Businesses must define how AI will contribute to their operations, whether by automating routine tasks or enabling smarter, faster decision-making. By aligning AI with daily workflows, companies can ensure it becomes a natural part of operations, not a disruptive experiment.

Even the most advanced AI tools can fail if employees aren’t on board, and the role of culture and change management should not be underestimated. Cultural resistance and uncertainty about new technologies often slow adoption. To overcome these barriers, organizations need strong leadership and change management practices to foster collaboration between employees and AI systems. Building trust and understanding around AI’s role in supporting, rather than replacing, human work is essential.

The industrial sector has access to cutting-edge technology, and competitive advantages often stem from small differences in the smoothness and efficiency of processes. These differences will grow between two groups, and those that integrate AI into their workflows to perform fast analyses and make data-driven decisions will outpace those sticking to traditional methods. It is easy to guess which group everyone would want to belong to.

The value of AI investments must also be demonstrated. Companies measuring the impact of AI projects — for example, tracking how much faster issues are resolved with AI compared to manual approaches — helps secure further investment and ensures resources are directed toward what works.

Kostiainen notes that AI tools are no longer exclusive to elite companies; they’re accessible to nearly everyone. While this democratization reduces reliance on traditional data scientists, it increases demand for professionals skilled in data modeling, generation, and deep business expertise. Success now depends on asking the right questions and applying AI to solve practical challenges effectively.

Kostiainen concludes that the companies that succeed in the AI-driven future will be those unafraid to experiment and innovate. AI doesn’t innovate independently — it provides suggestions based on data and instructions. True innovation still relies on the courage and creativity of people and organizations willing to take risks, learn from failures, and push boundaries.

Read the full opinion piece in Finnish in Tivi to learn more about Kostiainen’s insights on how AI can shape the future of industrial competitiveness and the importance of human commitment to technological change.