Graduate roles are intended to be necessary training for the industry professionals of tomorrow. Replacing graduates entirely with AI tools may be a short-term fix and efficiency burst, but ultimately damaging to the industry long-term, as talent is no longer gaining experience.”
With the UK’s Big Four accountancy firms – Deloitte, EY, KPMG and PwC – significantly increasing adoption of generative AI to automate the entry-level administrative tasks, graduate job intake is seeing the chop with cuts as high as 29% in some firms. The drop in graduate hires also follows a challenging period for the consulting sector and the need for cost-cutting measures.
This strategic shift may align with UK government goals of becoming a global AI hub, with projections suggesting AI could add £200 billion to the economy. However, firms face the challenge of low public trust in AI, and the battle of whether AI tools are mature enough to fully replace talent in any capacity.
Resource augmentation with AI is a key part of an innovative consultancy approach, but AI tools should not be wholly used to replace talent, even for entry-level tasks.
While the UK is leading the charge when it comes to the goal of becoming a global AI hub, this AI-focused approach cannot ignore the fact that we are also a global leading exporter of quality management and technology consultancy. It is in our best national interests to ensure that we don’t sabotage our talent, not just today’s talent, but also the talent of the future, by choosing to replace them with AI bots for cost-cutting, ease or laziness.
As AI continues to drastically reshape the landscape, headlines often focus on job displacement and the automation of teams. The reality is far more nuanced, with AI redefining how people work, accelerating existing teams, rather than replacing them. When it comes to the makeup of delivery teams, for example, especially in software engineering and development, AI can help generate clean, functional code faster than ever.
This is especially impactful in more repetitive or templated development tasks, yet still critically requires human oversight, strategic thinking and wider contextual understanding. Much like the automation wave of the last decade, AI is taking on repeatable, rules-based tasks. This frees up skilled professionals to focus on higher-value work such as design, strategy, stakeholder engagement, and innovation.