Nokia CEO: Companies Must Change Work Approach with AI Adoption
· news
Companies Are Using AI, Now They Must Change How Work Gets Done
The recent trend of rapid AI adoption in the corporate world has reached a tipping point. Companies like Nokia are no longer just experimenting with AI tools; they’re redefining their entire approach to work, leadership, and infrastructure.
Nokia’s “lowering the cost of curiosity” initiative encapsulates this shift perfectly. With AI-powered tools like Cursor, teams can now explore multiple architectural paths in parallel, test them quickly, and achieve stronger outcomes faster. This increases productivity without requiring more resources.
However, this shift requires a fundamental change in how organizations operate. As execution gets faster, leadership must move at a higher pace to define priorities, make trade-offs, and create conditions for teams to operate efficiently. Leaders need to be closer to the work to understand how teams are using these capabilities and where bottlenecks remain.
More than 90% of organizations use AI in some part of their business, yet only about one-third have scaled it across the enterprise. Nokia’s approach serves as a model for others: redesigning execution to harness the full potential of AI involves connecting intent, context, and implementation more directly, allowing teams to iterate faster with greater consistency.
In an AI-enabled environment, technical judgment, customer judgment, and business judgment become key differentiators. The notion of a “star team” must also evolve: built by creating teams comfortable operating with ambiguity, less coordination, and continuous learning.
Redesigning Infrastructure for AI
As AI workloads move beyond the data center, networks need to carry more than just traffic; they must deliver specific AI tokens for tasks. This structural shift in customer expectations requires fundamentally different network architecture.
Companies like Nokia recognize that infrastructure needs to become AI-native by design rather than simply layering intelligence on top of existing systems. This trend is mirrored in the development of AI infrastructure, where companies are redesigning entire systems from scratch rather than just adding intelligence.
The Leadership Imperative
Leaders must adapt to this new reality and redefine their role in the organization. They need to be closer to the work, understanding how teams are using AI capabilities, identifying bottlenecks, and facilitating decision-making across departments. This requires a higher pace of innovation to keep up with accelerating technology advancements.
Nokia’s approach serves as a beacon for companies seeking to scale AI across the enterprise by redesigning execution and infrastructure. By harnessing the full potential of AI, companies can drive productivity gains that benefit customers and employees alike. The question now is: will leaders rise to meet this challenge?
Reader Views
- RJReporter J. Avery · staff reporter
While Nokia's emphasis on connecting intent, context, and implementation is a crucial step in harnessing AI's full potential, companies should also consider the cultural impact of relying more heavily on automation. As work becomes increasingly driven by algorithms, workers who are comfortable operating with ambiguity may not be those with the greatest technical skills, but rather those able to adapt quickly to new processes and technologies.
- EKEditor K. Wells · editor
The shift in work approach with AI adoption is often touted as a silver bullet for productivity gains, but we're glossing over the elephant in the room: talent acquisition and retention. Nokia's emphasis on creating teams comfortable operating with ambiguity is commendable, but companies must also acknowledge that this new paradigm requires new skill sets. How do we ensure existing employees are upskilled or cross-trained to adapt to these changes?
- CSCorrespondent S. Tan · field correspondent
The adoption of AI in companies like Nokia is undoubtedly transformative, but what's striking is how much emphasis is placed on leaders adapting their own roles to keep pace with these changes. It's not just about empowering teams to innovate, but also about creating a culture where leadership can relinquish some control and trust in the expertise of others. Without this shift in mindset, even the most sophisticated AI tools risk being underutilized or worse, leading to unintended consequences.