In November 2024 BCS asked its professional members to give their views about on which sectors they felt AI would have the greatest impact in 2025. Brian Runciman MBCS reports.
Last year saw a big change in the concerns of IT leaders and IT professionals from BCS’ annual research on tech priorities, with AI making big gains and cloud concerns receding. BCS has reported on future IT needs in various guises over recent years — and again, for 2025, we asked questions of two key groups: IT leaders and digital/IT professionals.
We asked participants to tell us on which sector they feel AI will have the greatest impact in 2025. Responders could choose only one option. This is what they chose, in order:
Information technology (17%), customer services (14%), health and social care (14%), publishing/creative industries (9%), marketing (7%), education (7%), defence (6%), finance (4%), retail (3%), law (2%), manufacturing (2%), other (3%) and those who chose ‘don’t know’ (11%).
We asked an LLM to provide an overview of the reasons members gave as to why the respective area would be most affected. Two of these overviews follow, with some specific verbatim comments, to give a flavour of the feelings behind the thoughts.
Results for information technology
The survey suggested that AI is having a significant impact, particularly by causing job reductions for mid-level programmers, with automation affecting both high- and low-level roles. While AI is still seen mostly as a tool, it is transforming IT services by improving tasks and productivity. As AI adoption grows, it is driving research and development budgets, particularly in sectors focused on IT advancements. Roles like software engineers and IT support are being automated, and early AI adopters are already using it to enhance efficiency, with further integration expected across industries.
AI's potential to manage complex infrastructures, improve service provision and enhance software development, such as code generation and documentation, is becoming more apparent. Useful in threat detection and cybersecurity to safeguard systems and prevent attacks, it plays a key role in improving security. Many IT companies are already seeing a positive ROI from AI, especially in tools that enhance development processes and productivity. As AI continues to mature, IT professionals with the right skills will be well-positioned to leverage these tools, with AI taking on more tasks in coding and documentation, improving overall productivity. Additionally, AI will play a critical role in automating data analysis, managing large data volumes and supporting infrastructure and system design.
Human response analysis
So what of actual human comments? Several commenters noted that as IT underpins AI, it will be the first, and most, affected. One IT professional comments: ‘While it may be that the current generation of LLMs and "traditional" ML models would be easier to implement and far more disruptive in other industries, IT and software development are unfortunately for them the only industries generally capable of understanding and implementing meaningful AI solutions. I expect other industries to remain undisrupted in the short term while the barrier for entry to "AI" drops or they improve their technical competency.’
‘The rate of new discoveries in AI is phenomenal. The impact is felt in every sector. The world must realise that AI has come to revolutionise it. The earlier we embrace it, the better.’
The demands of the end user can drive big changes, as one member notes: the ‘move to increased personalisation is a big agenda item. Consumers want to spend more of their own time on things that are important to them. Tech alone does not make a person function, however, tech and AI can be fabulous life-enablers.’
There are still reservations for some. As one member comments: ‘Solid business use cases remain infrequent. In the majority of cases, true AI is a "tool to play with" rather than having a solid set of requirements and a meaningful financial business case.’
And the ever-present human-in-the-loop concern came up, with some helpful caveats. One member says: ‘A lot of the grunt work can be done by AI in requirements and coding. People can add value by refining the results’, with another simply writing ‘AI is perfect for creating suitable interfaces into IT.’
Results for health and social care
The LLM overview for health and social care highlighted the growing challenges of an ageing population. Elsewhere, workforce shortages are driving the demand for innovative tools in healthcare, with AI emerging as a solution to bridge the gap. AI is particularly effective in processing vast amounts of healthcare data, offering significant advantages in areas like medical imaging, diagnostics and predictive analytics. AI’s proven capabilities, including its success in reading medical scans and detecting anomalies, have led to strong investment and adoption, particularly in automating time-consuming tasks to improve diagnosis speed and decision making.
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In the context of rising healthcare costs, AI can help reduce financial strain by automating administrative functions. Its ability to deliver faster diagnoses and treatments is especially beneficial in high pressure environments like emergency care and oncology, where quick intervention is critical. AI also alleviates the pressure on overburdened healthcare professionals by automating repetitive tasks and providing decision support, helping reduce burnout and workload.
The advancements in AI tools tailored to healthcare are offering new ways to enhance patient care through early intervention, personalised treatment plans, and predictive models. However, ethical and regulatory considerations must be addressed to ensure AI’s integration aligns with privacy standards and provides tangible benefits to all stakeholders. Additionally, AI’s capabilities in machine learning enable it to predict disease outbreaks, identify health risks and offer preventive care, making it crucial for genomics, drug discovery, and early disease detection.
Human response analysis
The verbatims for this area were plentiful.
One member points out that there are also societal issues at play: ‘due to the fractious nature of healthcare in the UK there are many opportunities for small, incremental, and immediate benefits to using GenAI for support. LLMs to enhance a level of trusted collaboration must be built for this to happen, and it is happening.’
And the end user (the patient) is paramount: ‘the increasing amount of data available that could be used to help train AI to assist healthcare professionals with decisions and management of patients could lead to better outcomes for patients. Patients need to be empowered and encouraged to be actively managing their interactions with healthcare providers.’
‘An aging society needs new tools and we cannot train enough people here. AI will become commonplace for certain activities.’
One member drew attention to the shortage of healthcare professionals across the world and their relative expensiveness to employ: ‘Both of these factors place a strain on the public and private sectors. Many aspects of healthcare involve the analysis of data, which is an ideal use case for AI. There is also a very large amount of training data available to aid in the creation of AI models for healthcare. All of these factors would make AI a very attractive prospect for healthcare organisations.’
Other comments covered the importance of the underpinning Google accessible information standard (AIS), and one posited that ‘health analytics is ahead of other sectors, with traditional blockers around identity/access and privacy/data protection being addressed at pace.’
