Article Dealing with the Impact of AI intesity

Evolution of AI

Dealing with the Intensity of AI means evolving how we work with it.

Navigating uncertainty and the unknown

AI is changing not only how work is done but also what roles require. As responsibilities expand and traditional boundaries between functions blur, individuals and organisations need to become more adaptable in how they learn, work, and grow. 

It starts with recognising that the way work was done six months ago may not be the way in the future. Navigating this uncertainty requires curiosity, humility, and the willingness to ask for help. It also requires honest conversations about workload, learning curves, and capacity.

Some industries are already further ahead of AI transformation. Media, entertainment and technology are often early movers, exploring new ways of working and building capabilities that sectors such as critical infrastructure, public sector, fintech, and health can learn from as they navigate their own AI transformation journeys. 

Building mindsets needed for AI-driven shifts

As AI reshapes work, success will not be achieved by staying within role boundaries but by being able to adapt as they change. A client centric mindset will be needed and the ability to apply transferable skills.

Work is increasingly being redesigned around the boundaries of roles. It raises questions for both individuals and organisations: what roles will look like in the future, how will people succeed in unfamiliar territory, and how can transferable skills be applied to expanding responsibilities? It also challenges traditional assumptions about growth, particularly the idea that increasing revenue must always mean increasing headcount. As AI expands what existing teams can deliver, leaders need to rethink how growth is supported. The focus shifts to maintaining a client-centric mindset, applying judgement effectively, and understanding the role of internal teams in driving business growth.

Leading and managing AI agents

As AI becomes more capable of acting independently, the human role shifts again. Human interaction with AI extends beyond task completion to directing, supervising, and refining the work of AI agents. Managing AI will require leadership skills in setting clear goals, providing context, defining boundaries, and ensuring work stays aligned to the intended outcome. 

This is where situational leadership becomes relevant. Not every AI agent requires the same level of oversight. Some tasks may need close guidance and frequent review, while others can be delegated more autonomously once expectations, guardrails, and quality standards are clear. The ability to judge when to step in, when to guide, and when to let the system continue independently will become an important leadership capability.

Managing AI effectively begins with goal alignment. The objective is not just to get a task done faster, but to ensure the work supports the organisation’s broader goals. This requires a clear brief that defines the objective, broader context, decision-making boundaries, quality standards, and escalation points. It’s important to develop the skills to intervene and provide feedback similar to managing less experienced team members. The effectiveness of an AI agent depends on the quality of the delegation. If it has not worked on a particular project before, it needs the right context, guidance, and training before it can perform effectively.

Accountability does not disappear when work is delegated to AI. People are still responsible for what is produced, whether they create it directly or manage AI agents to deliver it. This means reviewing outputs, fact-checking information, applying judgement, and providing feedback to improve future performance. As AI makes execution faster and more scalable, the risk is that teams may produce more under time pressure, leaving less time to properly check the work.  Our value becomes less about execution alone and more about our judgment, capabilities, wisdom, and application.

As AI proficiency grows, roles will continue to expand and traditional boundaries between functions will keep blurring. The challenge is not learning how to use AI but learning how to lead with it. This means staying curious and adaptable, while building the confidence to operate in unfamiliar territory. As more work is delegated to AI agents, human value will increasingly come from judgement, accountability and situational leadership: knowing when to guide, when to intervene, and when to apply oversight to ensure quality, accuracy and alignment with organisational goals.

AI is already happening. Move past the pilot and see how leading organisations are winning with AI.