Businesses warned not to reduce recruitment for AI

McKinsey, a consulting group, has advised companies to continue investing in entry-level positions for young people following evidence that artificial intelligence was causing a decrease in headcount.

McKinsey admitted in a blog that the number of job ads had dropped for occupations that were most affected by AI. This trend could lead to a “long-term gap” in talent. The blog stated that this meant businesses would need to rethink their integration of AI and the way they invest in future skills.

Recruitment analysts reported at the end of June that the four largest accountancy firms had cut hundreds of jobs, and were reducing their recruitment of graduates, since AI was replacing the junior positions once held by university and school graduates.

Deloitte EY KMPG PwC and PwC, which collectively employs around 100,000 people in the UK, are among the companies that have replaced junior roles with AI.

KPMG has made the biggest cuts, reducing its graduate intake for 2023 from 1,399 graduates to only 942.

Deloitte cut its own scheme 18% while EY, PwC and PwC both followed with 11 % and 6% respectively.

James O’Dowd, executive search firm Patrick Morgan’s response to City AM was: “The Big Four look at AI very serious in order to duplicate junior work more effectively and cost-effectively.”

Adzuna analysis supported this view. It found that entry-level job opportunities have fallen by almost a third in the last three years since AI tools with generative capabilities became widely available at the end 2022.

McKinsey argues in a blog post that, while these trends are concerning for graduates, the “real story is more complicated, as AI acts alongside broader economic factors.” To avoid long-term gaps in talent, businesses must rethink how they integrate AI, and how they invest in future skills.

McKinsey’s latest global study revealed that almost 80% of world’s biggest companies, typically with tens or thousands of employees, reported using AI for at least one function. While smaller businesses are still lagging, a third (or more) of mid-sized firms in the UK have adopted AI.

Productivity gains are elusive

The blog stated that “wide-based” productivity gains remain elusive. Despite 92% of businesses planning to increase investment in generative AI over the next three-year period, only 1% think their efforts are mature. Around 20% of businesses report tangible impacts on their enterprise earnings. McKinsey says that “the tools are there, but changing the way people work and integrating them in workflows is challenging.”

The paradox of “widespread use but unrealised benefits” reflects the gap between surface-level transformation and deep adoption, it argued. The “horizontal” cases are where many companies have implemented tools such as chatbots or employee copilots. They were easy to scale, but delivered only modest and diffuse benefits. 90% of “vertical” cases, where AI automates specific business process, remained in pilot mode.

Blog stated: “If significant gains in productivity from AI will still be in the future, then you can expect companies to continue their normal approach to recruiting – all else being equal.” Other things are not the same, whether at the macroeconomic or the impact of AI.

McKinsey acknowledged that geopolitical tensions and the cautious household saving more money and consuming less were all contributing factors to the slowdown in recruitment. However, there were signs of the arrival of AI and large-language models dampening hiring intention. The slowdown in hiring is not due to a large increase in output, but rather to the lack of enterprise-wide productivity improvements.

Generative AI

Jobs that were predicted to be most affected by generative AI, such as software developers and other IT workers, as well professionals in data, design media research finance HR and business are among those who have seen the greatest declines. This includes software developers, other IT workers and professionals in media, design, research, legal and HR.

McKinsey warned organisations that if they continue to slow down entry-level hiring – for AI-exposed roles or lower-skilled positions that give graduates their first job – they risk leaving gaps in the future workforce. It said that once the pipeline is broken, it can be difficult to rebuild.

The blog’s authors wrote that to avoid this, they needed to invest in change management and rethink job design. They also needed reskilling, training and to build the internal ability for continuous adaptation. It is also important to identify which tasks can be automated and which require human creativity, judgement, and relationships.

The importance of investing in early-career employees was highlighted because they would help shape the AI culture and strategies for tomorrow. The article said that “doing so requires a change in mindset: Treat graduate and junior roles as long-term investments, not short-term costs.”

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