Leadership style is a critical factor in the success of AI transformation across different industry sectors, according to research by Paavo Ritala and his colleague Mika Ruokonen. They have identified three distinct approaches – Generalist, Expert, and Disruptive – and recommend that CEOs should be responsive to change.
Rapid adoption of AI and its potential to automate and augment knowledge have profound implications for companies’ business models and strategies. So, senior leaders need to quickly assimilate new information to maintain and create a competitive advantage.
Paavo explains: “AI transformation can be defined as a strategic process in which businesses adopt and integrate AI into their operations, products, and services to drive innovation, efficiency, and growth.”
“AI adoption presents a novel challenge that strategic leaders and organisations are just beginning to navigate.
“Our research reveals that the approach taken by the organisation is being determined by the knowledge and personal style of the leader. With organisations in the same industry taking very different paths.
“The rapidly evolving competitive landscape means that the appropriateness of approaches should be continuously evaluated.”
Interviews with 31 CEOs across a spectrum of industries
Paavo’s insights are based on 31 interviews with CEO’s and managing directors from large organisations and ambitious growth firms in Finland. Representatives from a diverse range of industries were interviewed, spanning advertising and fashion through healthcare and pharmaceuticals to manufacturing, energy, and finance.
The leaders all had extensive business experience but varied in their backgrounds, leadership styles, and experience with digital technologies. Each faced the challenge of leveraging value from AI, most notably Generative AI and large language models, but also in some situations, machine learning and other advanced technologies.
Additionally, the researchers collected secondary data to gain context about the pace of the firm’s AI transformation.
Findings: three distinct leadership positions
1. Generalist – although important, AI is not the main priority for the CEO. The CEO focusses on strategic direction and trusts their AI and domain experts, providing resources and removing obstacles. They are curious about AI but prefer to delegate.
“I trust that people in these roles are far ahead of me in AI thinking…. if I forced ideas top-down, I wouldn’t get great results.”
Research found generalist CEO in regulated industries such as construction, healthcare, legal services, and public sector.
2. Expert approach – many CEOs from technology-oriented sectors are themselves deep domain experts in AI. They lead by example and invest personal time and attention to AI over other priorities. Their role is to define the scope and pace of the AI transformation to capture business potential, while ensuring the business is aligned. Many said that AI was used to enable data-driven management practices.
“I have enough tech expertise to engage with our deep tech experts and assess the alternatives …but ultimately they are the true experts, and their view matters most.”
“We need to maintain a balance so that not everything turns into AI. It should remain a tool.”
3. Disruptive approach – for some CEO’s, AI is a make-or-break technology that enables reinvention. AI is not about incremental gains but about creating new markets and business models. The challenge is to define risk tolerance levels that allow an ambitious agenda without jeopardizing the company’s stability.
The value of disruptive and future-oriented AI projects was found to be difficult to measure with traditional business KPIs. They were considered closer to early-stage exploration.
“Our market is pushing us to change, but we also have a great opportunity to lead that change”.
What determines selection of leadership style?
The researchers examined the factors determining the approach taken.
Some association:
Market volatility, when combined with the CEO’s personal knowledge of IT and AI, was a factor. In relatively stable markets, CEOs with lower levels of knowledge adopted a generalist approach. In highly volatile markets, CEOs with strong skills are more likely to pursue disruptive strategies. However, there were exceptions to this, and the choice appears complex and non-linear.
Level of experience, adequate digital/AI skills appear to be a prerequisite for identifying and capitalizing on radical AI-enabled opportunities.
Company size – smaller companies were more likely to adopt a disruptive strategy, reflecting appetite for risk and agility. However, all approaches were found across the range of company sizes.
Little association:
Sector and length of CEO tenure – all three approaches were identified across multiple industry segments, indicating that the sector does not dictate a leadership style.
Key findings for successful AI transformation
Regardless of leadership style, the following were factors in success.
- Personal commitment – The enthusiasm and expertise of the CEO have a major impact on their leadership style and, by extension, the company’s approach to AI transformation.
- Investment of time – Developing a deep, actionable understanding of AI requires dedicated time and investment of effort by the CEO – many described this as an ‘awakening’ which enabled them to see the potential of the technology.
- Lead from the front – AI transformation requires it to be made a priority at all levels across the organisation.
- Empathy for employees – AI will impact all roles within the organisation, so the change journey needs two-way communication.
- Awareness of context – AI transformation is impacted by expectations of internal and external stakeholders. In some cases, the leader’s enthusiasm exceeded the readiness of the industry.
- Recognition of disruptive force – The rapid evolution of AI, cross-industry applicability, and potential to redefine competitive dynamics, allows some leaders to take a bolder, more ambitious stance.
AI transformation – practitioner takeaways
Paavo comments that the findings show that there is not a single ‘correct’ way to approach AI leadership. “Success depends on factors such as industry dynamics, organisational readiness, and the CEO’s strategic intent. However, we do have four recommendations.”
- Continually assess industry and organisational readiness – companies in fast-evolving tech-driven sectors may benefit from an Expert or Disruptive approach. For slower-moving and more regulated sectors, a generalist approach may be more appropriate.
- AI literacy is key CEO competency – AI transformation extends beyond technology adoption and demands an evolution in leadership style to align business strategy and the opportunities created by AI.
- Inaction or over-cautiousness is not an option – the intangible benefits of AI are difficult to measure, but in a rapidly changing landscape, more aggressive competitors will win market share and talent.
- Be prepared to be flexible – AI capabilities and industry dynamics can change in a matter of months. So, leaders need to respond and adjust their leadership style to capture new opportunities and emerging risks.
To read the paper
Leading AI transformation: three approaches for CEOs – M. Ruokonen, Paavo Ritala, LUT University, Finland. Strategy & Leadership. https://doi.org/10.1108/SL-12-2025-0433
