The competitive advantage: Why ‘slow and steady’ matters in the age of AI

The use of AI is typically associated with speed. Speed of work, speed of outcome, speed of process. This has led to a powerful narrative that faster is better. But as organisations look towards AI as a way to improve efficiencies, this is having an impact on entry-level roles which are being replaced by automated systems. Figures from the World Economic Forum’s Future of Jobs Report 2025 found that 40% of employers expect to reduce their workforce where AI can automate tasks.

But in the race to remain competitive, are we losing the much valued ‘slow and steady’ aspect of roles where knowledge is built and critical thinking skills acquired? In fact, the very capabilities that AI accelerates may make slow, reflective, human‑centred work more valuable than ever. AI learns from the information it is fed, but people still need to be able to assess and evaluate the outcomes for accuracy, anomalies and also opportunities.

Why the future needs slower thinkers

Worker expectations are growing and diversifying. Flexible working is no longer the preserve of younger generations. Older workers facing rising retirement age, increasingly value reduced working time and the chance to enjoy life while still healthy. This shared desire for balance creates unexpected bridges across generations and brings a different kind of productivity.

Rather than equating speed with efficiency or AI with the loss of roles, slow and steady work can actually lead to working better. AI can produce outputs at the click of a button, but the real value lies in how humans interpret and apply it.

Jobs of the future will rely heavily on the ability to analyse AI‑generated information. The technology might be able to generate answers instantly, but what it can’t do is judge whether those answers are appropriate, fair, or aligned with organisational values. That responsibility still falls to humans and it demands time and the kind of deep thinking that cannot be automated.

This is where intergenerational and interdisciplinary teams become essential. Knowledge transfer between experienced workers and new entrants helps build the judgement required to work effectively with AI. Instead of removing entry‑level roles, organisations may need to redesign them to cultivate the reflective skills that AI cannot replicate. Pairing junior roles with structured mentoring may be the key to preserving mastery in an AI‑driven workplace.

Supporting a new kind of career path

The modern workforce is also increasingly fluid. People move between roles, build portfolio careers, and expect flexibility in both time and place. The four‑day week has emerged as a powerful tool for improving work‑life balance with trials across the world demonstrating that reduced working time is especially valuable for workers who commute or must work on‑site. In sectors like healthcare or hospitality, where physical presence is non‑negotiable, work time reduction becomes the most meaningful form of flexibility.

But of course, not every job can or should adopt the same model. The goal is not uniformity but equity. This means ensuring that all workers have access to meaningful, purposeful work and the time to live well. Having the opportunity to think slower brings more equality. If everyone works less, it frees more time to do tasks that should be done. For example, if we look at gender equity, men who work a four-day week tend to participate much more in childcare and domestic tasks. When we lower the amount of work for everyone, then it becomes more egalitarian. Having free time to think and also engage in different projects for society is ultimately better.

AI has an integral role to play in supporting equity and a work time reduction rather than removing a role altogether.

A future of support not sacrifice

Over the next few years, we will see a proliferation of AI‑assisted roles – from researchers and clinicians to accountants and engineers. But whatever the application, ethics, integrity and mental health will grow in importance as society navigates the boundaries between human and machine.

Rather than a world where AI replaces human judgement, I see one where humans work with AI, supported by the flexibility and creativity that reduced working time enables. Slow and steady isn’t disappearing but becoming indispensable.

In a world where AI accelerates everything, the competitive advantage may lie in taking a step back and cultivating the human capacity to pause, reflect, and act wisely. Slow thinking is not a relic of the past but a skill that will allow organisations to harness AI responsibly and workers to build meaningful, sustainable careers.