AI only realizes its full value when it becomes part of the corporate strategy
Many companies today are actively exploring AI, testing tools, launching pilot projects, and gaining initial experience. But there is a crucial difference between individual AI initiatives and true transformation. AI should not be viewed as just another tool; rather, it must become part of the corporate strategy and the operating model.
That was exactly the focus of our webinar “AI & Strategy: From AI Activism to True Transformation” with Balz Zürrer, Group CEO of Online Group, and Marco Denzler, CEO Switzerland. The focus was on how companies can integrate AI in a way that leads not only to individual use cases but also to a lasting impact.
The AI Transformation Gap Is Becoming a Strategic Challenge
The relevance of AI is hardly ever questioned anymore; the real challenge today lies in its implementation. According to the results of the PwC CEO Survey presented in the webinar, 54 percent of Swiss CEOs are concerned about whether their companies are transforming quickly enough to keep pace with technological developments. At the same time, 56 percent of their time continues to be spent on short-term issues.
Our own experiences paint a similar picture. More than 500 companies have now completed our AI Readiness Check. 98 percent consider AI important for their business; at the same time, 81 percent lack a prioritized list of processes with AI potential, and 84 percent rate their employees’ level of training in AI as insufficient.
“The greatest enemy of progress is not error, but inertia.”
Henry Thomas Buckle †
English historian (1821–1862)
The key question is not “if,” but “where”
Anyone looking to approach AI strategically should no longer focus primarily on whether the technology is relevant. What matters is where it creates the greatest economic impact.
Four questions are central to this: How can core processes be redesigned and new offerings developed? How can a scalable technological and organizational foundation be created? How can adoption within the company be achieved? And where does AI make a measurable contribution to productivity, revenue, costs, and EBIT?
The Online Group made this strategic decision as early as 2023. Its ambition was to succeed with AI—as a leading AI-first partner for digital transformation on the Microsoft Cloud, as an attractive employer for talent, and with the goal of outpacing the IT market.
The results from 2025 included, among other things, a record 33 new clients, a very high workplace rating, and the best fiscal year in the company’s history.
Breadth and depth must develop simultaneously
A key lesson from our own transformation is the so-called T-shaped approach. In terms of breadth, the goal is to empower as many employees as possible to work more productively with AI, try new things, and learn continuously.
In terms of depth, selected core processes are systematically transformed with the goal of creating new AI-native offerings or enabling significant cost reductions.
Those who focus solely on breadth generate many ideas but achieve little in the way of scaling. Those who pursue only individual flagship projects risk a lack of acceptance within the organization. Only the interplay of broad empowerment and targeted depth creates the foundation for sustainable transformation.
AI is transforming roles, processes, and value creation
True transformation occurs when not only tools but also ways of working change. This is particularly evident in software development. AI Engineer Michal Cislo sums up this development in a concise statement:
“I haven’t written a single line of code in the last two months.”
Michal Cislo
AI Engineer
This does not mean the developer’s role is disappearing; it is evolving. The Q&A session described how developers are increasingly orchestrating multiple agents, delegating tasks, reviewing results, and designing technical architecture. This shift is also changing role profiles in the online sector; consultants are once again building solutions themselves more often, and teams can achieve significantly more with the same resources.
Agents Need Data, Context, and Clear Responsibilities
For AI agents to truly add value, they need more than just access to individual data sources. A shared context across Microsoft 365, ERP, CRM, and other systems is crucial.
In the presentation, this was illustrated using WorkIQ and FabricIQ as a semantic layer that connects information, relationships, and permissions. Only with accurate data in the right context can agents reliably research, act, and automate.
Humans, too, remain part of this model. The more standardized a process is, the more autonomously an agent can act. In more complex or strategically important situations, the decision-making authority remains intentionally with humans. AI thus does not simply change individual work steps, but rather the way responsibility and tasks are distributed within processes.
Transformation also means allowing for mistakes
Not everything went smoothly on the path to becoming an AI-first organization. Some team members left the company, an in-house ISO 27001 bot saw little use, and technological assumptions had to be adjusted several times due to the rapid pace of change. The original idea of consolidating AI expertise into a separate unit also proved ineffective.
These experiences gave rise to the “AI Spine” concept. Rather than embedding AI in an isolated Center of Excellence or within individual teams, the concept connects business units, end users, technology, data, risk, and compliance. Use cases are selected based on their expected value, resources are pooled, impact is measured, and initiatives are then either scaled up or discontinued as appropriate.
Governance and security lay the foundation for scaling
The more AI is integrated into core processes, the more important governance, security, and resilience become. At Online, this includes, among other things, ISO 27001, Microsoft Partner certifications, clear guidelines for using secure AI platforms, and a strong IT and DevOps team.
At the same time, innovation should deliberately remain fast-paced. New approaches can first be tested pragmatically and then systematically transitioned into a secure and scalable environment.
Governance should not be seen as a hindrance. Rather, it creates the framework within which employees can use AI safely, develop new solutions, and scale successful approaches.
Change management is not a one-time training session
One of the most important lessons from our own transformation concerns people. AI adoption does not result from a single implementation day or a one-time training session.
During the webinar, a comparison was drawn with professional athletes. In their case, performance results from a continuous interplay between training and competition, not from a single training session.
That is precisely why a successful AI transformation requires continuous learning, active support, and a culture in which experimentation becomes the norm. Looking back, Marco Denzler emphasized in the webinar that Online initially underestimated the importance of this area. Change must be consciously shaped and understood as an ongoing process.
Five Steps from AI Activism to an AI Operating Model
Based on the experiences of recent years, five key areas of action can be identified.
First, AI must become a top priority and be managed as a business issue. Second, there needs to be a clear focus on measurable economic benefits. Third, companies should combine broad empowerment with targeted transformation using the T-shape approach. Fourth, an “AI Spine” must be established to hold functional departments, process owners, technology, data, and governance jointly accountable. Fifth, data, platform, security, and governance must be established as a common foundation for scaling.
AI transformation doesn’t start with the tool—it starts with the company
The key takeaway from the webinar is therefore clear: AI transformation is not merely a technology project. It affects strategy, leadership, processes, skills, culture, data, and governance in equal measure.
A clear vision is achievable, but it requires the courage to question existing ways of working and to further develop one’s own operating model. At the same time, the Online Group’s experience shows that an AI-first strategy can create added value for customers, employees, and the company’s success.
Companies that take this step no longer use AI just for isolated experiments. They create an organization in which AI can make a measurable contribution. That’s exactly where AI activism turns into real transformation.
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