The costly AI transformation mistake organisations are making

BOARDROOMS across South-east Asia are noting a frustrating paradox: artificial intelligence (AI) is a top technological priority – Egon Zehnder’s 2025 CIO survey found that chief information officers ranked it second only to cyber risk – yet the return on these substantial investments remain negligible. Despite numerous proof-of-concept initiatives, few are scaling to create real business value.

Why does this occur? Many organisations misdiagnose the failures of AI transformation. They often attribute these shortcomings to technological issues or to the performance of an individual leading AI initiatives. The real challenge, however, lies in a leadership blind spot.

To become AI-driven, organisations frequently delegate AI transformation to a senior technical leader, typically the CIO, chief technology officer, or a data/AI leader. When hiring or appointing leaders for AI initiatives, they tend to prioritise technical expertise over business acumen.

This misalignment leads to strategic discord, projects that fail to deliver value, and friction between technical and business units. Consequently, organisations incur significant investments that do not scale, resulting in a transformation agenda that stalls before achieving tangible business impact.

To avoid this costly oversight, organisations must rethink the talent they deploy. They need to identify and empower the right leader to lead the charge, and ensure that all leaders share accountability for this critical initiative.

Rethinking leadership

Our research has identified three distinct archetypes of AI leadership:

The Shaper: This visionary focuses on the broader implications and future potential of AI. They challenge conventional wisdom and guide organisations through the complexities of AI evolution. They are suited for board positions, where they can pose critical questions, help fellow members recognise opportunities and risks, and articulate a compelling vision.

The Builder: This expert develops disruptive AI products and possesses deep technical knowledge, driven by a passion for creating innovative solutions. They are essential for organisations developing proprietary AI models, providing the expertise needed for large-scale innovation. Typically holding a PhD in engineering, mathematics, statistics or AI/machine learning, they often have extensive research backgrounds and commonly hold titles such as chief scientist.

The Transformer: This business integrator drives value by bridging the gap between technical AI knowledge and business execution. They manage cross-functional teams to deliver AI-driven results and seamlessly integrate the technology into core business functions.

While all three archetypes are important, the Transformer is the most critical leader in an organisation’s AI transformation journey, connecting technological potential with business outcomes. Without this profile, organisations risk developing impressive technical solutions that fail to yield business value, or creating proof-of-concept projects that lack scalability.

Assessing the Transformer in South-east Asia

The business environment in South-east Asia is defined by family-owned enterprises, government-linked companies (GLCs) and large conglomerates, all of which require leaders who can navigate complexity, dismantle internal silos and effectively implement AI initiatives. The nature of the role, however, must adapt to each unique context.

In a family owned enterprise, they build trust and influence stakeholders, balancing tradition with transformation. To succeed, they demonstrate the value of AI while respecting the company’s legacy.

In a GLC, they navigate public-sector accountability and complex regulations, framing AI’s value beyond commercial return to also highlight their contribution to national mandates.

In conglomerates, they act as a portfolio strategist, creating tailored AI road maps for diverse business units while orchestrating collaboration and shared learning across the entire group.

Recognising the need for a Transformer is the first step, but the real challenge lies in assessing their competencies. In addition to appointing a leader for AI transformation, can some of the present leaders also serve as Transformers within their respective functions?

Transformers can be evaluated based on how they utilise their core leadership skills to drive AI transformation. Some of the most critical competencies include:

Leading change: Transformers encourage holistic change in how things get done with AI, inspiring and mobilising others. They model AI integration, demystify its application, and empower their teams to experiment and learn.

Cross-functional collaboration: Transformers dismantle silos and embed AI into business processes. They have demonstrable examples of how they have driven collaboration between technical and non-technical teams to achieve measurable outcomes.

Understanding customers through AI: Transformers leverage AI-enhanced insights to comprehend customer needs and drive innovation. They prioritise AI use cases that deliver genuine value to customers, rather than technical novelty.

Talent and organisation development: Transformers think ahead about the organisation’s future talent needs. They recruit future AI Transformers, cultivate a culture of continuous learning, and position their organisations as talent magnets.

From the CIO global survey, 70 per cent of Asian respondents reported that piloting and rolling out AI/generative AI tools have become increasingly important in the past 18 months. Furthermore, 80 per cent expressed a need for greater support in upskilling and training their organisations for AI adoption.

The demand for Transformers – leaders who can drive business transformation, rather than merely technical implementation – is more urgent than ever.

To avoid the costly mistake of AI transformation, boards and senior executives must ask themselves:

• Are we leveraging our talent to drive business transformation?
• Do we possess enough AI Transformers within the organisation to remain competitive over the next 36 months?
• How are we assessing and developing the right capabilities within our existing team?

Ultimately, AI transformation is not just about the tools; it is about the people. By prioritising the assessment and development of effective leaders, organisations can cultivate a pipeline of AI-ready leaders, build a culture of innovation, and reap the potential returns of enterprise-wide AI adoption.

The writer is a partner at Egon Zehnder