AI transformation requires leadership – CGI trains all its personnel to use AI
IT and consulting company CGI is investing one billion dollars globally in AI. The company is systematically training its entire workforce and helping customer organisations navigate the AI transformation. “Using AI is not just a technical development project – it is a change process that affects the entire organisation,” says Henna Poutiainen, AI change management consultant at CGI.
Organisations need to build expertise, establish operating models, and cultivate a culture where generative AI becomes a natural part of everyday work and decision-making. The transformation touches all levels – individuals, teams, management and organisational structures – and requires consistent and responsible guidance.
Change management consultant Henna Poutiainen from CGI explains how organisations can implement generative AI transformation and why the role of management is now more important than ever.
Key considerations in the AI transformation
“It is crucial that an organisation has a clear change strategy and vision: why we want to use AI, where we are heading and what our goals are. These messages need to reach everyone through role-specific training and communication, for example. It is also essential to measure progress from both technological and human perspectives.
“AI on its own does not deliver benefits – implementation alone is not enough if it is not used effectively. People need to build confidence in using AI and a clear understanding of when it can support work – and when human expertise is required.”
Should technology or people come first in the AI transformation?
“We need both. The technological foundation must be in place, but it is equally important to consider people and how the organisation operates. Technology evolves quickly, while people adopt new practices more slowly. Change management ensures that AI is truly integrated into everyday work – only then will benefits emerge.
“It is also important that people understand what is expected of them. This speeds up projects and streamlines deployment. As readiness for change grows, new applications can be rolled out without starting from scratch with everyone. Training should start with an assessment of AI readiness: what people know now and what skills or knowledge will be needed in the future.”
Tackling real business problems with AI
Common pitfalls in AI transformation, and how can they be avoided?
“One pitfall is related to attitudes and uncertainty about where AI can genuinely be useful. The best results are achieved when AI is used to solve actual business problems, not issues imposed from outside. The business must own the problem and start solving it. IT’s role is to support the process with the right tools and platforms, but it is up to the business to define and take responsibility for the problem.
“Another key aspect is role-specificity. AI is applied in different ways across functions, so training and tools must be targeted accordingly. Clear principles and ethical guidelines are also needed. Without them, people are left to figure out on their own what is acceptable. Expectations can sometimes be unrealistic – AI is not a solution for everything and using it effectively requires effort and ongoing discussion.”
Ensuring responsible AI use
“The quality of data is very important, because AI is only as good as its background data. Organisations must know who is responsible for the data and who is in charge of keeping it up-to-date. This is particularly important when AI has been trained with internal guidelines – outdated data can lead to incorrect outcomes.
“A strong culture of information security is a vital part of the transformation. The use of closed AI systems has become more common, but they also require discretion. Not all information can or should be fed into them, and people need to understand what can and cannot be done with AI.”
Without understanding, there will be no AI use cases
What kind of AI-related needs do CGI’s customers have?
“Customers need support on how to implement AI in their organisations and make it a natural part of everyday work. They require help in designing training and communication, as well as understanding the key considerations for deployment. Support is also needed with governance models and strategic questions: where is the organisation headed with AI?
“On the product development side, customers often need concrete technical assistance. But when it comes to change management, the focus is on how to actually integrate the technology. Training, communication and AI literacy are critical. Without a solid understanding of AI, no use cases will arise – for example, HR must recognise for itself where AI could be useful. This understanding cannot come solely from the IT department.”
How has CGI implemented the AI transition in its own organisation?
“CGI has invested heavily in AI. All personnel are trained in the basics, and the training then deepens according to each role into different technologies. Training is tailored to the individual and integrated into ongoing skills development.
“Globally, CGI is investing billions of dollars into AI. In addition, we have developed a framework for responsible AI, ensuring that transparent and explainable models are used, delivering reliable and ethically sustainable results. AI is evaluated from the perspectives of fairness, equality and reliability – and it must meet strict data protection and information security requirements.”
Leadership is more important than ever in AI transformation
What is the state of AI development in Finland and globally?
“According to the AI Finland report, Finland performs well in international comparisons, although the trend is downward. Among the Nordic countries, Finland ranks highest. In Stanford’s annual AI survey, Finland came fifth relative to its population, and its overall ranking was around 20. We have strong research and good infrastructure, but private investment remains very limited.”
How does the AI transformation progress at societal, organisational and individual levels?
“At the societal level, regulation is still being developed and refined. At the organisational level, systematic change management is essential: roles, responsibilities, processes and data management must be clearly defined. Using AI effectively requires large-scale, coordinated action.
“Progress at the individual level is slower, as people adopt new technologies at different speeds. There are significant differences between sectors, which is why education and communication are particularly important. You cannot assume that everyone will understand the potential of artificial intelligence on their own.”
Critical role of management in AI transformation
“It is crucial for organisations to appoint someone to coordinate the AI transformation. AI alone will not drive change – active management is required. Management must understand what AI is, what projects are being carried out in the organisation and what impacts these projects have. This is the only way AI can be effectively managed.
“A systematic approach brings the greatest benefits – which is why leadership is more important than ever in the AI transformation.”
Text: Mikko Viljanen / Photos: Liisa Takala