AI Can Accelerate Work, But Can Leaders Build the Judgement Behind It?
Updated: 2 minutes ago
The report took 12 minutes to prepare. The decision could affect the company for the next 12 months.
Sophie Bennett, the chief operating officer of a growing retail company, had asked her strategy team to assess whether the business should expand into two new markets.
By the following morning, the team had an AI-generated report. It included competitor comparisons, projected demand, pricing analysis and a recommendation to move ahead. Work that might previously have taken several days was ready before the first morning meeting.
Sophie reviewed the presentation. The arguments sounded convincing, the figures were organised and the recommendation appeared straightforward.
Then she asked one question:
"Which important factor might this analysis have missed?"
The team looked back at the report. It had considered market data and competitors, but nobody had checked whether the company's distribution network could support the expansion or whether local customer expectations had been properly understood.
Yes, AI has accelerated the analysis. But it had not completed the thinking.
Would you trust a 12-minute report with a 12-month business decision?
This is the challenge facing executive leaders today. As AI reshapes the workplace, leadership must evolve from simply driving efficiency to building better judgement and decision-making capabilities.
AI Can Speed Up the Work, But Can It Improve the Decision?
AI can summarise lengthy reports, identify patterns, organise information and generate recommendations in minutes. These capabilities can free employees from repetitive work and give them more time to focus on complex responsibilities.
But faster output does not automatically mean better decisions.
An IBM Institute for Business Value study published in September 2026 surveyed 1,500 CHROs and 8,800 employees globally. It found that 60% of employees worried about skills erosion, with critical thinking cited most often as a declining skill. Interestingly, 71% of CHROs identified the ability to supervise, validate and override AI outputs as essential, compared with only 29% of employees who ranked judgement as important.
This difference deserves attention.
AI-assisted decision-making still requires people who can question information, understand its limitations and recognise when a recommendation does not fit the situation.
One important part of this balance is understanding where data ends and human judgement begins. As explored in our earlier article on balancing AI insights with emotional intelligence, effective leadership requires more than interpreting what technology reveals. Leaders must also understand the people, emotions and circumstances behind those insights.
The Hidden Human Tension Behind AI Adoption:
If AI makes everyday work easier, why might it also create new challenges for employees?
The answer often lies in how people respond to uncertainty, responsibility and the fear of making mistakes.
1. Fear of making the wrong decision:
What if I challenge AI and my judgement is wrong?
AI-generated answers often sound confident and well-researched. Employees who doubt their own judgement may hesitate to question the output, even when something doesn't seem right.
2. Fear of accountability:
If the decision goes wrong, who takes responsibility?
Employees may worry about being held accountable for decisions based on AI recommendations. This can make them reluctant to challenge the technology or question its conclusions.
3. Loss of autonomy:
Does AI make my experience and expertise less valuable?
Experienced professionals may feel that their knowledge is being overlooked when AI is expected to provide answers. Over time, they may rely on technology instead of sharing their own insights.
4. Overdependence on technology:
Are we becoming too dependent on AI for answers?
When speed becomes the priority, employees may accept AI-generated recommendations without examining the reasoning, checking the facts or considering alternative solutions.
Leaders also need to confront a deeper question: How does AI change their professional identity?
As intelligent systems take on more analytical responsibilities, leaders may need to rethink where their real value lies. We explore this shift further in Leadership Identity in the Age of Intelligent Systems, which examines why human judgement, emotional intelligence and the ability to connect with people remain central to leadership.
What Happens When Organisations Introduce AI Without Developing Their People?
Let’s understand this with two organisational examples that show why employee involvement and decision-making structures matter when introducing AI.
IBM: Giving Employees a Voice in AI Adoption
IBM offers an interesting example of involving employees in shaping how AI is used at work.
In a June 2026 case study published by Partnership on AI, IBM's responsible technology team described how it gathered employee feedback through individual interviews and structured discussions.
The purpose was to understand how employees wanted AI to support their jobs, what concerns they had and where the technology could add value.
The initiative highlighted the importance of listening to employees, providing opportunities to experiment and making AI learning and access more widely available.
The leadership lesson: People should not simply be recipients of technological change. Their experience and practical knowledge should help shape how that change happens.
When employees have a voice in the process, leaders gain a better understanding of where AI can genuinely support work and where human expertise remains essential.
CIPD's InnovationCo: When Decision Ownership Is Unclear:
A different perspective comes from a CIPD case study examining a small public innovation company, referred to as InnovationCo, that introduced an AI tool for maintenance planning in a safety-critical, unionised sector.
The project encountered several organisational barriers. Decision-making was fragmented, information was not consistently shared across regions, and teams lacked clear ownership of important decisions. Employees also felt they did not have sufficient authority to redesign workflows around the technology.
The problem was not simply whether the AI tool worked. The organisation needed better coordination, cross-functional involvement and clearer governance to make its adoption effective.
The leadership lesson: Giving employees access to AI does not automatically give them the authority or organisational support to use it effectively.
These examples highlight two sides of the same challenge. Technology adoption requires employee involvement, but it also needs clear responsibility, shared knowledge and leadership support.
Executive Leadership Means Setting Guardrails, Not Just Introducing AI:
Imagine an employee using AI to assess customer risks. The tool identifies potential issues and recommends an action. But should the employee follow it without checking the findings?
This is where executive leadership matters. Leaders must establish clear boundaries around how AI is used and who remains responsible for the outcome.
Delegation: Decide which tasks AI can support.
Autonomy: Allow employees to explore different approaches.
Decision-making authority: Clarify who can approve or challenge recommendations.
Ownership: Ensure people remain accountable for decisions.
Guardrails: Set clear boundaries for accuracy, privacy and human review.
Delegating a task to AI does not mean delegating accountability to AI.
Leaders must make sure people understand where technology can assist, where their judgement is required and when a decision needs further review.
5 Questions Leaders Should Encourage Their Teams to Ask:
How can leaders make critical thinking a regular part of AI-supported work rather than an occasional exercise?
Start by encouraging employees to question the output before acting on it.
What evidence supports this recommendation?
What context or information might AI have missed?
What alternatives, risks or consequences should we consider?
Who owns the final decision and its outcome?
What needs human judgement or expertise before we act on this recommendation?
These questions can become part of team discussions, project reviews and decision-making processes.
The objective is not to make people question every AI-generated sentence. It is to help them recognise when human judgement must guide the next step.
Beyond the Algorithm: Building the Human Side of Leadership with Next Dimension Story :
AI will continue to change how people work. But the organisations that benefit most will not necessarily be those that adopt the most tools or automate the greatest number of tasks.
They will be the ones that develop people who know how to question information, recognise risks, collaborate and take responsibility.
As a Storytelling & Executive Leadership Coach at Next Dimension Story, I'm George Eapen. My focus is helping leaders understand that AI should support human thinking, not replace it.
I encourage leaders to ask a more important question: Are we simply helping people work faster, or are we developing their ability to make better decisions, take ownership and lead with confidence?
The Executive Leadership Video Course is a relevant starting point. It explores OGSM, micro-decisions and emotional intelligence to help leaders develop stronger judgement and team performance. Our Leadership Reflection Worksheet and Smart Decision-Making programmes offer a structured way to reflect on your leadership approach and evaluate choices, overcome hesitation, and move from overthinking to action.
Complement these with the Power of Storytelling, which helps leaders articulate the deeper WHY, build trust and communicate decisions more effectively.
Because AI can accelerate the work, but developing people who can think, decide and act responsibly is what builds lasting organisational capability.
Ready to Build the Human Judgement Behind AI?
AI might have generated the recommendation. But did your team question it? Did anyone challenge the assumptions? And most importantly, who took responsibility?
These are the questions that separate technology adoption from genuine leadership capability.
If you're ready to explore how 1-to-1 personalised coaching can help you strengthen your decision-making, emotional intelligence and leadership approach, connect with Next Dimension Story.
Let AI expand what your team can do. Let leadership strengthen how they think.
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