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Artificial intelligence: from pilot to profit

Data and artificial intelligence (AI) have evolved from being a technological opportunity to becoming a strategic necessity. Today, AI is as important a strategic resource as capital, talent, and technology. Nevertheless, many companies face the challenge of scaling the value of their investments in platforms, technology, and tools.

What is required to succeed in making the leap from experimentation to real value creation across the organization?

Despite most companies having high ambitions regarding AI, only one in four succeeds in broadly scaling the value of AI within their organisation. By 2026, 75% of companies are expected to rely on data and AI to improve operational efficiency and growth. However, on average, it takes 14 months before a company begins to see returns from AI investments. (Source: IDC and Microsoft)

A good example of successful implementation is a Norwegian retail platform that achieved 2 million NOK in annual savings through Power BI management tools. The solution enabled better visualisation and faster decision-making based on data.

Stages of scaling data and AI

To ensure value creation at scale, companies must take a holistic perspective. Technology alone is not enough — success requires a combination of organisational and technical capabilities.

After assisting over 100 companies with various projects involving data and AI across industries, we have identified six critical areas that must work together for success:

  1. Business value – AI must be clearly linked to business strategy and integrated into existing decision-making processes.
  2. Skills and culture – The success of AI depends on the organisation's ability to adapt and adopt the technology.
  3. Technical infrastructure and tools – A scalable technology platform that supports AI development.
  4. Operational model and governance – Clear roles, responsibilities, and processes that ensure effective implementation.
  5. Access to quality data – Necessary data for AI must be accessible and of high quality.
  6. Ethical and responsible use – Guidelines for developing and applying AI to ensure ethical use in accordance with regulations.

People are key

One of the biggest pitfalls in AI implementation is underestimating the importance of people and organisational culture. Research shows that only 10% of challenges lie in AI models and algorithms, while 30% relate to data and technology. A full 60% of success depends on change management, skills development, and governance.

Workshop Jorunn og Frank-321

Itera has helped several companies realise the value of AI through successful projects:

Financial Sector

Machine learning for fraud detection has reduced financial losses and improved risk management.

Retail

Prediction of customer churn provides better customer insights and increased customer loyalty.

Public Sector

Fire statistics reporting with AI-driven analytical tools offers better decision-making support.

Communication

Automation of reporting with Power BI has saved businesses millions in annual costs.

The way forward – from strategy to action

For companies looking to succeed in scaling AI, the following steps are recommended:

  1. Understand the current situation and define ambition levels – Where are we today, and where do we want to be?
  2. Design a comprehensive AI strategy – Link AI to business strategy clearly outlining what capabilities are necessary for success with AI.
  3. Implement targeted development – Identify specific business needs that can be addressed with AI.
  4. Ensure organisational anchoring – Build skills and a culture for AI adoption.
  5. Establish a technical foundation – Ensure scalable and flexible solutions.

Scaling the value of data and AI is not just about technology — it requires a strategic approach, organisational adaptation, and a clear understanding of how AI can create business value.

Companies that succeed in this will achieve efficiencies and secure a solid competitive advantage in the digital economy.

Get in touch

We help you get real value out of your AI investments

Vishal Kaura

Vishal Kaura

Head of Data & AI

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