Leadership in Motion - Issue 2
Leadership systems are unable to absorb AI effectively.
In Issue 1 of this brief, the central observation was that structural transformation is accelerating at a pace that leadership behaviour hasn’t yet matched. The gap between ambition and behavioural readiness is where execution risk increasingly sits.
That gap is now becoming more visible in a specific and very topical domain.
The rapid introduction of AI into organisations is not primarily revealing limitations in technology. It is revealing the extent to which leadership systems, operating rhythms, and decision processes have not yet adapted to a very different set of conditions.
Leadership Signals
Recent research published over the past six months points to a consistent pattern. Organisations are progressing in their adoption of AI, yet leadership systems and operating models are not evolving at the same pace.
Deloitte’s State of AI in the Enterprise 2026 highlights that while many organisations feel strategically prepared for AI, far fewer report readiness in governance, talent, and operational integration.
McKinsey’s State of AI 2025 indicates that adoption is now widespread, but only a limited number of organisations have successfully scaled AI across the enterprise. The differentiator is not access to technology, but how effectively leadership integrates it into decision making and operating rhythms.
Research from the Oxford Internet Institute in collaboration with Snowflake points to organisational and leadership factors as the primary barriers to AI value realisation, rather than technical limitations. Questions of accountability, ownership, and clarity of use are emerging as central challenges.
Studies examining the impact of AI on work suggest that roles are not disappearing as quickly as anticipated. Instead, tasks are being reshaped, placing greater emphasis on human judgement, oversight, and decision quality.
Emerging data on governance indicates that many boards and executive teams have not yet established clear oversight for AI, reinforcing the idea that leadership capability is becoming a critical constraint.
The Systemic Leadership Tension
Leaders are now being asked to operate at a pace that their organisations aren’t yet structured to support. This isn’t simply a question of speed. It’s a question of how decisions are made, how accountability is defined, and how insight is translated into action.
AI is increasing the volume, immediacy, and visibility of information available to leaders. At the same time, many organisations continue to rely on decision processes, governance structures, and management layers that were designed for a slower and more stable environment.
This creates a tension that builds directly on the theme identified in Issue 1. The gap between transformation ambition and leadership behaviour is not only widening. It is being placed under greater pressure.
Leaders experience this in practical terms. There is more data available than ever before, yet less confidence in how to interpret and act on it. There is greater urgency to respond, yet uncertainty about which signals can be trusted. There is an expectation of speed, yet the underlying system has not been redesigned to support it.
Leadership Implication
The leadership challenge is no longer whether to adopt AI, it’s how to redesign leadership practice around it.
This requires a shift in three areas:
leaders need to move beyond introducing new tools and instead reconsider the operating rhythm of the organisation. AI changes how frequently decisions need to be made and how quickly insight becomes relevant.
the focus must shift from generating insight to integrating it into real leadership moments. The value of AI is not realised in dashboards, but in how it feeds into deal reviews, strategic trade offs, and resource allocation decisions.
leadership discipline becomes more important than ever. As AI increases visibility, it exposes inconsistencies in thinking, gaps in process, and weaknesses in execution more quickly.
AI is increasing the volume and speed of insight in organisations, but leadership systems are not yet structured to absorb and act on it effectively.
Reflection Question
Where is AI increasing the speed of insight in your organisation, while leadership processes continue to operate at a pace designed for a different environment?
Source Log
Deloitte, State of AI in the Enterprise 2026
McKinsey, State of AI 2025
Oxford Internet Institute and Snowflake, AI adoption research
MIT research on AI and task transformation
Recent governance and board oversight studies on AI
Erlend Asker
Executive coach and leadership advisor. Former commercial executive. Works with senior leaders navigating organisational transformation.
