Artificial intelligence cannot deliver concrete business benefits or a genuine competitive advantage without a vision and strategy. These, in turn, require systematic management, investments, and, above all, the ability to measure successes. Digia's experts explain how to succeed in change management and measurement.
The AI revolution is progressing rapidly, but the Finnish business sector is sharply divided into two different camps. Pioneers are taking bold steps and striving to build a competitive advantage, while cautious organizations are stuck in the assessment and preparation phase for one reason or another.
This is revealed in the AI maturity survey conducted by Digia in spring 2026, which was published as part of AI Finland's How Finland utilizes AI report (in Finnish).
"The result shows the intensity of the change. AI is no longer just a technological experiment, but a strategic choice that requires leadership, investments, and, above all, the ability to measure success," says Minna Häkämies, Head of Data Insight at Digia.
The role of leadership is emphasized when the direction of change is sought and must be carried forward. Without clear goals and measurements, organizations risk falling behind in development.
"What is worrying about this polarization is that the total productivity of the Finnish business sector is weakening. Half of the companies are trying to drive the change forward but have not yet achieved the desired results, and some are not even trying. To reap the benefits of AI, more investment in change management is needed. The focus is on experiments that are too small and on individual tools," adds Henna Ahtola, Director, Business Consulting at Digia.
According to the survey, more than 85 percent of management in Finnish organizations are committed to using AI to some extent. However, only about three percent said that the vision and implementation of AI are well advanced or that they have a comprehensive AI roadmap in place. In other words, 97 percent of companies lack a vision or roadmap for using AI.
"If the vision is missing, it is clear that implementation is problematic. Even though technologies and use cases are changing rapidly, they cannot be an excuse for a lack of vision. Organizations must be able to clarify the role of AI in the development of operations," Ahtola says.
The vision serves as the basis for a strategy and a concrete AI roadmap, which can be dynamic and evolving. After this, there is a need for systematic management, processes, monitoring, and indicators.
AI can have a major impact only if organizations are prepared to renew their operating methods and integrate AI into their processes, products, and services.
"The pace of development has been so fast that organizations have not been able to take care of the AI strategy, its management, ownership, or measurement in the necessary way. This slows down the utilization of AI and the realization of business benefits," Häkämies says.
"Ensuring the right direction requires measurement that goes beyond just technological KPIs. With the right kind of metrics, we can ensure that AI projects do not remain just hype, but bring concrete benefits," she adds.
When using AI, it is worth setting both short-term and long-term goals, along with the indicators that support them. The indicators must be both qualitative and quantitative.
"Organizations should create both predictive indicators (leading) and performance indicators (lagging). In change, it is not worth focusing only on measuring short-term productivity," Ahtola points out.
Predictive metrics indicate whether AI adoption is progressing towards the desired impacts. For example, utilization rate, level of expertise, number of automated processes, and customer satisfaction help guide operations, while performance metrics, such as cost savings, productivity, and business growth, ultimately demonstrate the business value achieved.
"The benefits of AI are not always immediately visible directly under the line, but they can first manifest themselves as more efficient processes, increased staff motivation, and the creation of new kinds of services," Häkämies adds.
From a goal-achievement perspective, it is important that the measurement motivates the entire organization.
"When clear goals are set, and progress is monitored transparently, a can-do attitude is created. Well planned is half done, as the saying goes. The successes and lessons learned from AI projects must be shared openly so that the organization can learn, and cautious companies dare to take steps towards utilizing AI," Häkämies points out.
"Change and change management require courage, a clear strategy, and measurement. Indicators help guide the implementation of the strategy and identify areas for development. If you don't measure, you can't guide or succeed," Ahtola adds.
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