The shortage of AI skills is now a crucial bottleneck for business success. Companies must rapidly develop their internal capabilities to avoid falling behind. Business leaders have a great responsibility to learn more while encouraging employees to explore AI. How should the management approach AI skills?
AI has the potential to become a key success factor for most companies. Everyone wants to implement it, at least to stay relevant. However, to achieve real success, it is essential to boost AI awareness among management and ensure that the workforce is upskilled on AI.
“Both business and technical leaders must possess a degree of data literacy. Data literacy helps in understanding how AI can bring value to customers and the company and how to upskill the workforce to be better equipped with AI. Additionally, leaders need to understand how we use data and AI in a transparent and ethical way,” says Telenor's Jawad Saleemi, Director of AI & Cloud.
AI requires a human in the loop
Saleemi emphasises that AI alone will not solve all our problems. Instead, it is just another tool in the toolbox. What counts is how companies use AI, combine it with business strategy and domain expertise, that determines how they can leverage it to realise business value.
“With AI, we can make better decisions, but it is not making them for us. We still need a human in the loop who has complete oversight. The human factor is extremely important, and it is also required by the EU AI Act.”
The EU AI Act, coming into effect in August 2026, requires human control, especially in high-risk AI applications such as biometric data, real-time facial recognition through surveillance cameras, and profiling individuals and making lending decisions.
A human-centric approach to AI is also necessary for tackling any risks.
“Uncertainty and a lack of trust persist, as AI systems have been known to hallucinate. It is important to raise awareness of ethical restrictions and to be very careful about the use cases we start with. We must implement guardrails and conduct proper risk analysis,” Saleemi says.
In their position, leaders are responsible for bringing together groups that may have polarised and unrealistic opinions about AI. Some individuals may still view AI as merely a buzzword, while others believe it has the potential to solve every problem.
“We have to bring the expectations and hype to a realistic level.”
AI requires a mindset change
Companies must invest in technical and cultural training on AI and ensure that employees are familiar with its potential and limitations.
“You need to foster a culture that encourages AI innovation while maintaining safe boundaries. People must feel they can freely explore AI technologies within ethical and legal guardrails. That requires a mindset change,” Saleemi emphasises.
A different mindset is also necessary due to the differences between traditional IT systems and AI. While conventional IT tends to follow strong roadmaps, AI tends to be much less predictable and requires a more exploratory mindset.
Human skills – such as critical thinking, creativity, communication, and ethical reasoning – remain vital in the era of AI and should not be neglected. AI adoption must go hand in hand with developing these soft skills across the organisation.
Need to know when and how AI is the right solution
Management must develop their ability to assess when and where AI can truly deliver value. Often, a key obstacle to doing anything with AI is the quality and availability of data. Therefore, Saleemi recommends focusing on data governance to properly structure and manage information.
“Without good quality data, decisions made with AI assistance will not be optimal. However, you cannot wait until everything is perfect before getting started. It's crucial to simultaneously apply both bottom-up and top-down approaches. By doing so, you can find the optimal balance and uncover opportunities with AI,” Saleemi explains.
Beyond understanding key enablers and blockers and developing core architectures, AI must ultimately support the business.
“It is easy to become caught up in AI buzz, but we must look beyond it. We need to keep a clear ambition of what we want to achieve. At the end of the day, AI and data will not change the overall business strategy but will instead play enabling roles in more effectively achieving existing objectives and in defining new ones.”
Telenor's own AI approach highlights customers
Telenor's AI strategy targets three core areas: enhancing customer experience, optimising networks, and empowering employees.
“AI helps us automatically resolve recurring customer issues and deliver the best possible customer service. The next domain with strong potential for AI is networks, our bread and butter, so to speak, and how to optimise them further and eliminate downtime. Equally important is how AI supports employees in their work,” says Jawad Saleemi.
To confirm the business value of AI, Telenor is going to define such KPIs. For instance, when AI is implemented to reduce recurring customer calls on similar issues, it is possible to measure the results. In the networks, downtime and automatic incident resolution KPIs can reveal AI's impact.
Key tips for management to drive AI:
- Educate yourself on the possibilities and challenges of AI.
- Invest in workforce training and provide easy access to AI tools.
- Encourage a culture of experimentation and safe exploration.
- Emphasise the human-in-the-loop principle.
- Focus on data governance – AI quality is tied to data quality.
- Measure success using clear KPIs tied to business value.
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DNA is part of Telenor Group, the leading telecommunications company in the Nordic countries.
