In all industries, artificial intelligence is no longer an experimental tool or a competitive advantage reserved for the few. It has become the backbone of strategic and operational decisions. Nevertheless, many companies struggle to move beyond pilot projects. The challenge is not primarily technological—it is fundamentally organizational. Embedding AI in a company requires a rethinking of workflows, decision-making rights, and responsibility structures. It is a transformation of the entire corporate organization from the inside out.

At our upcoming roundtable in Davos in 2026, "Building the AI-Native Enterprise – A Cultural and Operational Transformation from Within," executives from industry, finance, and the service sector will come together to discuss how organizations can become truly AI-native enterprises by 2030. These are companies where technology, culture, and governance go hand in hand, creating systems that are adaptive, resilient, and capable of continuously learning from new data.

A key challenge is integrating AI into everyday work beyond pilot projects. Many companies have shown initial success with AI, but implementation in daily operations often stalls. Managers must promote a culture in which AI is understood not merely as a tool, but as an integral part of decision-making. Employees must experience AI as something that supports and complements their work, rather than replacing it. Change management, cross-departmental training, and clear incentives are crucial to overcoming resistance and building trust in AI systems.

Governance and operating models are equally critical. Continuous learning requires feedback loops, transparent responsibilities, and decision-making rights that balance autonomy and oversight. Without structures that integrate AI into daily operations, there is a risk that AI will be isolated, underutilized, or misapplied. By designing AI-native workflows, companies can create an environment where algorithms support decisions, but human judgment remains central.

Roles and collaboration are also changing. AI influences not only tasks, but entire decision-making chains. Teams must work more closely across departments and combine expertise with technical insights. Early AI adopters in manufacturing, finance, and services show that there are transferable insights: agile, cross-functional teams, integrated data platforms, and leadership that actively exemplifies AI accelerate transformation and secure long-term value.

By 2030, an AI-native company will be one in which technology, processes, and culture are inextricably linked. Operating models adapt in real time, managers make decisions based on predictive analytics, and employees are empowered to drive innovation through AI-powered insights. Competitive advantages arise less from the algorithms themselves and more from a company's ability to integrate AI into its operational and cultural structure.

Action is urgent. AI-driven productivity expectations are rising, regulatory requirements are becoming stricter, and talent structures are lagging behind new workflows. Shaping the path to becoming an AI-native enterprise is not optional—it is key to remaining competitive in a rapidly changing landscape. Our roundtable in Davos will shed light on these dimensions and help executives understand how companies need to be transformed from the inside out to achieve sustainable, AI-driven growth.