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Opinion

From human-in-the-loop to human-on-the-loop: The new leadership skill gap

Orla Daly discusses why leaders must develop stronger oversight and governance skills as AI takes on a greater role in the workplace.

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As artificial intelligence (AI) systems become more autonomous, with 50% of business decisions predicted to be augmented or automated by AI agents next year, human roles are shifting away from execution and toward oversight. Humans are moving from ‘in-the-loop’ to ‘on-the-loop’, where they are no longer involved in every decision, but instead oversee outcomes, define guardrails, and step in when risk or accountability demands it.

This shift creates a new leadership challenge: knowing when to intervene, when to trust the system, and how to ensure accountability remains firmly with humans. Closing this gap requires more than AI adoption; it demands a new leadership capability built around judgment, governance and outcome-based decision-making.

Why technical competence alone is no longer enough

For years, technical expertise defined capability and credibility in the workplace, particularly within technical and specialist teams. While employees knowledge effectively on the job, it was technical proficiency that underpinned confidence, performance and career progression.

That expertise has now been devalued due to the growing accessibility and autonomy of AI tools within organisations. Employees across functions can now leverage AI regardless of their technical background, and develop similar AI solutionsThe result is a workplace where technical competence is no longer enough.

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What matters now is how effectively those capabilities are applied through judgment, oversight and decision-making under uncertainty. Organisations that continue to prioritise technical skills or AI adoption as a technology priority in isolation risk creating AI-driven workflows that reinforce sub optimal processes rather than improve outcomes.

At the same time, trust in AI cannot be built passively. If employees are not encouraged to engage with AI early, through experimentation, interaction and practical applications, confidence in both the technology and leadership’s ability to govern it effectively begins to erode. When responsible decision-making is not built into workflows, with one mistake, adoption slows and scepticism grows.

The rise of on-the-loop leaders

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AI does not reduce the need for leadership. It redefines it. As work becomes increasingly cross-functional and AI-enabled, traditional command-and-control leadership styles are becoming less effective. Leaders are no longer expected to manage every input or approve every output. Instead, their role is to orchestrate: aligning people, technologies, and processes to keep work moving effectively through constant change.

This requires a shift from task-level controls to outcome-level accountability. Leaders must create clarity, enable collaboration, and help teams adapt as priorities and skill requirements evolve. That demands stronger judgment, greater risk literacy, and the ability to oversee outcomes rather than individual actions. As AI investments intensify, leadership skills such as critical thinking, prioritisation and decision-making are more critical than ever.

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Effective “on-the-loop” leadership also depends on continuous development. Leaders must build the skills needed to translate AI-driven potential into measurable business outcomes, balancing

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innovation with accountability and ensuring that autonomy does not come at the expense of control. In this environment, organisations need to build a skillforce, where human and AI capabilities work together to deliver impact at scale.

How organisations can equip leaders to manage AI complexity

To succeed, organisations must move beyond viewing AI through the lens of efficiency alone. The real challenge is governance, ensuring AI is used responsibly, consistently and aligned with business intent.

This begins with culture. Responsible AI stewardship cannot sit within a single function. It must be distributed across an organisation, with employees empowered not only to use AI, but also to question its outputs and assess its recommendations. The significant impact that AI is having on how work is being executed means the human skills required for the workplace must evolve.

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Organisations need a continuous system for understanding, developing and deploying skills in line with business priorities. This enables leaders to identify the capabilities they already have for working effectively with AI, identify the gaps that matter most, and build workforce readiness as the demands of AI driven work continue to evolve. Equally, governance frameworks must evolve. Static policies are no longer sufficient in fast-moving AI environments. Organisations need embedded guardrails that guide responsible decision-making in real time. Without these capabilities, businesses risk either stifling AI’s potential or even outsourcing decisions they don’t fully understand.

Importantly, organisations must recognise that AI is not a one-size-fits-all solution. Different parts of the business will operate with different risk profiles and levels of maturity. Some functions require tighter controls, while others can move more quickly, experimenting and iterating more freely. Leading organisations will reflect this reality in their AI strategies, ensuring that governance, risk, value and business priorities remain closely aligned.

Driving returns from AI investments

The shift to human-on-the loop working marks a turning point in how organisations create value from AI. Leaders are no longer expected to oversee every decision, but to guide outcomes through effective oversight, judgment, and strategic direction.

Those that invest in strong decision-making frameworks, governance and responsible AI use will begin to close the gap between AI spend and business impact. Meanwhile, organisations that fail to build these capabilities will risk continued misalignment, where investment grows faster than realised value.

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As we see AI investments continue to rise, success will depend less on what leaders produce directly and more on how they effectively shape, challenge and direct high-impact AI adoption across the organisation.

Orla Daly is chief information officer at Skillsoft

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