A survey by Survation, on behalf of BusinessLDN, found that only 50% of London businesses believe their workforce currently has the skills and capabilities they need, down from 63% a year earlier. Meanwhile, 15% report significant skills and capacity gaps, up from 4% in 2025.
The gap is becoming more noticeable as adoption accelerates. Three-quarters of businesses surveyed are already using AI in some form, while only 5% have no plans to use it. Among firms already using AI, 85% say the technology has changed the skills required from employees, including greater demand for critical thinking, ethical reasoning and decision-making.
Understanding the Scale of the Problem
London sits at the centre of European business, finance, and technology, yet the scale of its digital skills gap is becoming difficult to ignore. The Survation survey of 2,043 business leaders found that 35% of firms reported some skills and capacity gaps, while 15% reported significant gaps.
Digital capability is a particular concern. Among businesses experiencing skills gaps, 60% said they lacked advanced digital skills, while 23% reported shortages in basic digital skills. The pressure is also expected to increase: 78% of businesses anticipate a significant need for advanced digital skills over the next two to five years, compared with 66% last year and 56% in 2023.
These figures suggest that AI literacy is part of a wider workforce challenge. As AI becomes embedded in analytics, automation and everyday business processes, employees increasingly need the digital knowledge to understand these systems, assess their outputs and use them appropriately.
How AI Is Changing Digital Operations Across Industries
The shift towards AI is becoming visible across almost every industry. Businesses are using the technology to process larger volumes of data, automate routine tasks, identify unusual activity and respond more quickly to changing customer behaviour. As adoption grows, the question is increasingly not whether AI can be used, but where it can improve existing operations without removing the human input that customers still value.
Gaming provides a clear example of where that balance could develop further. AI can already support areas such as fraud detection, customer service, data analysis and personalised recommendations. Similar possibilities are emerging for casino gaming, where the technology could eventually help monitor digital platforms, identify technical problems, and adapt services based on real-time activity.
That could also influence live casino games in the future, with AI supporting more of the technology and operational processes behind each session while live dealers continue to provide the human interaction at the centre of the format.
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Why Traditional Training Models Are Falling Short
Most firms respond to skill gaps with training programmes. The instinct is logical, but the execution often misses the mark when it comes to AI.
Generic online courses, one-day workshops, and vendor-led product demos rarely produce lasting behavioural change. Employees complete the training, return to their desks, and revert to familiar habits within weeks. The knowledge doesn’t stick because it was never connected to the work employees actually do.
Another failure point is that many AI training programmes are built for a technical audience. They focus on how models work under the hood (concepts like machine learning architectures, training data, and parameter tuning), which is genuinely irrelevant for the majority of business users.
A marketing manager or financial analyst does not need to understand neural network design. They need to frame a problem clearly, evaluate AI-generated output critically, and integrate AI assistance into their existing workflow without compromising quality or accuracy.
The firms making real progress on AI literacy have moved away from event-based training toward embedded learning. They integrate skill development into daily work processes, assign internal AI champions who support colleagues in real time, and create environments that encourage experimentation and treat mistakes as learning opportunities rather than failures. That cultural shift is harder to manufacture than a training module, but it delivers far more durable results.
What London Firms Should Prioritise Right Now
For firms still in the early stages of addressing AI literacy, waiting for the technology to stabilise could leave existing skills gaps unresolved as requirements continue to change.
Training is an obvious place to start, but investment is not necessarily keeping pace with expected demand. While 78% of businesses expect a significant need for advanced digital skills over the next two to five years, 13% expect their training investment to remain unchanged, and 5% expect it to fall. That makes it increasingly important to direct available resources towards areas where skills shortages are already affecting work.
The immediate priority should therefore be an honest internal audit. Firms need to identify where AI is already being used, which roles are changing as a result, and where employees lack the knowledge needed to work effectively with these tools.
This matters beyond training alone. Twenty percent of businesses plan to reduce staff numbers, and among firms planning cuts, 24% cited reduced demand for entry-level staff due to AI. Building AI literacy therefore needs to be considered alongside recruitment, workforce planning, and the changing responsibilities of existing employees.
Disclaimer: Reference to casino activity is for information only. Gambling involves financial risk and is for adults aged 18+. Please gamble responsibly.