The next AI transformation unfolds in five stages: “Companies must reinvent their entire operating model”

AI agents are only the beginning. The next wave of AI transformation is about rebuilding the entire business operating model around people, AI, data, and automation. According to Digia CEO Timo Levoranta, the biggest challenge is not technology but leadership.

Read the summary (AI-generated, human-reviewed)

• The AI transformation is moving towards autonomous business, where people, AI, data, and automation work together as one integrated operating model.
• The transformation progresses
  through five stages: AI as a tool, AI as a co-worker, AI agents, autonomous processes, and ultimately autonomous business.
• Technology is no longer the main challenge. The key question for companies is whether they are prepared to redesign their entire operating model to fully realize the value of AI.

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The first stage of the AI transformation could be anticipated years in advance. In 2020, Digia began talking about the “symbiosis” of humans and intelligent software, where work is carried out together with AI. Only a few years later, that vision has become reality. Now, an even bigger transformation is emerging.

“The direction is clearly towards autonomous business. The next phase of the AI transformation is to build a company whose entire operating model is designed around people, AI, systems, and automation. It requires rebuilding the business in a completely new way,” says Digia CEO Timo Levoranta.

Agents are only the beginning: Five stages towards autonomous business

Levoranta explains that the transformation progresses through five stages.

1. AI as a tool. In the first stage, people do the work while AI tools assist them.

2. AI as a co-worker. In the second stage, people and AI form a new kind of production unit in which work is performed largely in collaboration with AI tools. This stage has already become widespread in areas such as software development. Organizations are no longer measuring only personnel costs but are also factoring in the cost of using AI.

3. AI agents perform tasks. AI agents make the use of AI more efficient because they can independently carry out specific work tasks. Humans direct and supervise their activities.

4. Autonomous processes. AI agents, automation solutions, and other systems begin working together across entire processes. This enables a much higher level of automation.

5. Autonomous business. Ultimately, the entire operating model can be built around collaboration between people, AI, and data. In an autonomous business, systems do not simply report what has happened. They detect changes, learn from operations, make decisions, and initiate actions almost in real time within defined goals and boundaries.

“Humans define the direction, objectives, and rules of the game. AI brings scalable intelligence, speed, and the ability to operate continuously,” Levoranta explains.

It is important to understand that autonomous business is not simply about deploying AI agents. While an individual agent automates a task, autonomous business means transforming the company's entire operating model.

Autonomous business means transforming the company's entire operating model. It is built on collaboration between people and AI.

According to Levoranta, most organizations around the world are currently somewhere between stages two and four. AI agents are being tested and deployed into production, but expanding their use and embedding them into the core of business operations is still a work in progress.

“The pace of change is rapid, but only a few organizations have transformed their operations systematically.”

The biggest challenge is leadership: the entire operating model must change

The building blocks required for autonomous business, such as AI tools, data platforms, integrations, and automation systems, are already highly advanced from a technology perspective. According to Levoranta, the challenge is how to combine them into a coherent business whole. That is why this is not only a technology challenge but, above all, a leadership challenge.

“Leaders must, of course, consider how AI can be utilized. But alongside that, a much bigger question is needed: Do we understand this transformation well enough, and do we have the courage to redesign the organization's entire operating model? Are we ready to build our business as a shared production engine powered by people and AI?”

Leaders need to ask whether they understand the transformation well enough and whether they are willing to redesign the organization's entire operating model.
Simply improving the old operating model is not enough. When the new production unit consists of people and AI working together, organizations must redefine how work is performed, how decisions are made, and how responsibilities are divided.

“The greatest risk is not uncertainty or the pace of change in our business environment. The greatest risk is trying to succeed in a new world with an old operating model,” says Levoranta.

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