Bridging the Gap

Workforces in the “Information and Communication” and “Financial and Insurance” industries in the UK have not exhibited precipitous swings over the past thirty years. Information and Communication jobs have grown at a fairly uniform pace from 800,000 in 1996 to some 1.6 million today, with some modest downturns along the way, while Financial and Insurance employment has held steady at 1.1-1.2 million. Even through major economic shocks, these sectors have avoided the swings seen in manufacturing or retail.

However, many observers are highlighting the risk of AI-driven job losses across the spectrum of employment, with specific concerns naturally attached to industries where it is easiest to imagine AI supplanting human workers. These two sectors are now the twin poles of the AI displacement debate:

Information and Communication is exposed due to the collapse in cost for natural language and code generation.

Finance and Insurance is vulnerable to the rise of agentic AI capable of automating the “reasoning loops” involved in compliance, auditing, and administrative analysis.

Recent research from the UK’s AI and the Future of Work Unit (published in early 2026) has begun to quantify this. Their pilot studies suggest that while mass unemployment hasn’t hit the aggregate stats yet, we are already seeing a silent hollowing out of entry-level roles. Their data indicates that AI-exposed occupations saw a 13% drop in early-career hiring in late 2025, a potential leading indicator that the total headcount may finally be ready to break its 30-year trend.

This question postulates that by the end of next year, one or the other of these workforces will undergo a sharper contraction than any that has been recorded over the past thirty years. While the Financial and Insurance workforce contracted by 10% at least once in this period, it did not happen as rapidly as this question envisages, and the Information and Communication workforce has not experienced a contraction of more than 6.7%. Importantly, because organisations are not required to cite specific causes/reasons when reporting redundancies, the question does not stipulate that the contractions must be only due to AI adoption. Nevertheless, given the historic trends in these industries, a drop of 10% in such a short space of time would point to a significant shift in workforce practices – the sort of structural shift which AI advancement and adoption is currently the leading predictor for.

The Swift Centre forecasters estimated the likelihood of this scenario materializing in the specified time frame at 23%. The bulk of the forecasters landed between 10% and 30%, with two outliers at 35% and 55%.

The forecasters saw the persistent uncertainties about the uptake, use-cases, and effects of generative AI in these industries as high enough that an essentially unprecedented employment disruption was more unlikely than likely in this relatively short time window. That said, the very same uncertainties about the near-term shape of AI uptake ensure that the chance is non-trivial, and no forecaster assigned a likelihood below 10%. Probabilistically, also, the fact that the question requires only a qualifying shift in either of these two AI-vulnerable sectors supports the odds of it resolving positively.