Automation & AI Readiness Gap: Which UK sectors are falling behind?

New research by Esendex reveals which industries are leading the way in automation and AI readiness and which ones are falling short. The research highlights a growing gap not just in the adoption of technology, but the skills required to implement and sustain it.

The current state of automation and AI adoption in the UK

As innovation accelerates, artificial intelligence (AI), automation technologies, and agent-based systems are reshaping the way businesses operate across every sector. AI-driven tools and automated systems are transforming workflows, increasing productivity and redefining job roles.

As of mid-2025, AI adoption among UK organisations has seen strong adoption, with around 39% of businesses already using AI in some capacity, and a further 31% considering implementation. 

However, while enthusiasm for AI is prevalent, full-scale automation, especially end-to-end, remains limited, with just 14% of UK businesses reportedly achieving fully automated, AI-driven workflows across their organisations. Yet, with over half of enterprises (57%) reportedly experimenting with AI in automation, a broader rollout could be underway.

This trend comes as the UK process automation market reached approximately $6.72 billion last year, with its value projected to grow by more than 80% over the next decade to reach $12.15 billion by 2034. 

Elsewhere, an estimated seven million people in the UK use generative AI in their day-to-day roles, signalling a major shift in how AI is being integrated into business operations. In 2022, only 15% of businesses used an AI tool, but by 2025, this figure had surged to 78% globally, reflecting rapid acceleration in adoption. 

The UK AI market alone is currently valued at over £21 billion, and is projected to expand dramatically to £1 trillion by 2035. However, technological developments are outpacing workforce readiness, as research shows half of all employees will require significant reskilling in response to automation. 

The UK government’s recent £187 million national skills drive highlights the urgency of this issue. The initiative aims to bring digital skills into schools and upskill 7.5 million workers with essential AI skills, demonstrating that the government is acknowledging that long-term growth depends on equipping people with the skills needed to thrive in a digitally transformed landscape.

Therefore, this report aims to highlight which industries are best prepared for digital transformation and which require further investment.

The Automation & AI Readiness Index

To assess automation and AI readiness, our team analysed over 10,600 automation and AI job listings and 11,400 training courses across 17 industries using data from Reed. Each sector was scored on two core areas: job demand (out of 1,200), and training availability (out of 400), separately for automation and AI-related search terms. 

These scores were then combined to produce a single readiness index score out of 1,600, to determine how well each industry is equipped for the future of work and where the biggest opportunities for growth and investment lie. We further examined employment data Office for National Statistics (ONS) to identify trends in the workforce and vacancies for relevant sectors between 2022-2025, where available. 

Automation and AI Readiness Index, overall rankings by sector

Sector	Overall index score
IT & Telecoms	777.9
Engineering	368.7
Financial Services	58.3
Marketing & PR	50.3
Banking	47.6
Manufacturing	46.2
Education	45.3
Accountancy (Combined)	44.9
Sales	41.2
Transport & Logistics	29.2
Legal	24.7
Health & Medicine	14.3
Energy	13.8
Insurance (General)	10.7
Human Resources	10.5
Retail	10.4
Construction & Property	6

 IT and Telecoms lead in automation readiness 

The IT and telecoms sector emerged as the leader in automation readiness, achieving an overall index score of 777.9 out of 1,600 – more than double that of the next highest industry. This strong performance is somewhat unsurprising due to the sector’s central role in shaping the UK’s digital economy, and signals that many businesses are actively preparing for the broader implementation of AI and automation. 

Nearly 90% of telecom companies already use AI, and the industry’s AI Index score (498 out of 800), comprising job demand and training availability, reflects this adoption due to strong demand for AI talent from over 6,000 available roles. 

Roles such as ‘data engineer’ and ‘python engineer’ were among the most in demand, accounting for 52% of the sector’s AI job listings. However, training provision notably fell short, with limited availability from a score of just 54.3 out of 200, indicating a potential skills gap that could slow down hiring and growth. 

In contrast, the sector’s automation score trailed behind at 279.9, with a lower job demand of 251.8 and a limited training availability score of 28.1. Automation roles accounted for just 17% of the 6,816 current vacancies in the sector overall, compared to 88% for AI, revealing a clear imbalance in readiness. 

While there is a strong appetite for both AI and automation, without immediate investment in education, training programmes, and reskilling initiatives, the sector could face bottlenecks in growth, innovation, and productivity.

This comes as job vacancies within the industry plummeted by 55.1% between 2022 and 2025, reflecting a potential slowdown in tech hiring likely driven by a combination of factors, including economic uncertainty and AI-driven efficiencies.

Automation and AI Readiness Index, top 5 industries

Engineering sees high automation demand, but training gaps persist

Engineering ranked second overall, with an index score of 368.7 out of 1,600, demonstrating strong readiness for automation and AI. 

However, there is a notable disparity in investment focus, with a significantly higher automation index score of 245.8, more than double the AI index score of 121.9. This is driven by greater job demand for automation-skilled workers, with a score of 215 out of 600, in contrast to 89.2 for AI-skilled roles. 

This suggests that automation technologies are being prioritised within the sector’s investments, likely due to their applicability in engineering processes. Encouragingly, a reported 97% of engineering firms now use AI and machine learning, indicating widespread adoption. However, as our data’s lower AI index score suggests, while it is being utilised, the focus on dedicated talent is lagging. 

Interestingly, despite the demand, only 30% of training provisions were for automation skills, with a greater number of AI courses, highlighting a gap between industry needs and current training availability, which may limit the sector’s ability to reach its full automation potential.

Sector	Overall index score	Overall automation index score	Overall AI index score
IT & Telecoms	777.9	279.9	498
Engineering	368.7	246.8	121.9
Financial Services	58.3	36.2	22
Marketing & PR	50.3	22	28.4
Banking	47.6	14.7	32.8

Financial services shows strong digital ambition despite training gap

The financial services sector ranked third for automation and AI readiness overall, with an index score of 58.3 out of 1,600. However, despite its relatively strong ranking, the sector’s score remains significantly lower than the top performers, reflecting an urgent need for investment. 

The sector is currently focused on automation, with an overall index score of 36.2, compared to a lower AI index score of 22.0. This was in part driven by a significantly higher job demand (20.8) compared to AI-related roles (4.0). 

However, training opportunities for automation skills within the sector remain limited, representing just 29% of courses, compared to 70% focused on AI training, indicating the need for investment to support rising demand for skilled workers. 

Despite a strong intent to digitalise, with 82% of CFOs increasing investments in digital technology in 2024, this is not yet matched by actual implementation, as at the start of 2025, 49% of finance departments still operate with zero automation and only 13% are fully automated. Investing in automation within financial services can streamline processes and increase customer engagement.

However, financial services also emerged as the top-performing industry for customer service, offering a higher-than-average number of communication channels, including web chat, SMS, and WhatsApp. This highlights that, while automation adoption is still catching up, the sector is already prioritising fast, multi-channel customer communication to maintain and scale its customer service standards.

From a workforce perspective, financial services have seen a 7.6% increase in jobs from 1,119,000 to 1,204,000, with stable vacancy levels in 2024-2025 (0% change YoY). However, overall vacancies fell by 32.7% between 2022 and 2025, which could reflect a more targeted hiring approach for new roles. 

Deloitte states that financial organisations that fail to accelerate their automation initiatives risk falling behind competitors that are more digitally mature. While the industry’s efforts to adopt automation and AI are clear, the data reveals significant opportunities for investment in upskilling. 

AI Readiness Index, top 5 industries

Sector	Overall AI score	AI job demand	AI training availability
IT & Telecoms	498	443.7	54.3
Engineering	121.9	89.2	32.7
Banking	32.8	30.5	2.3
Marketing & PR	28.4	13.4	15
Education	25.3	1.5	23.8

Banking focuses on AI, but investment in training is trailing

The banking sector ranked fifth with a moderate Automation & AI Readiness Index score of 47.6, suggesting a sector still scaling its digital capabilities. The industry is heavily focused on AI, with an index score of 32.8 compared to 14.7 for automation. 

Demand for AI-related roles far outpaces those in automation, with positions such as ‘python engineer’ and ‘AI developer’ making up 80% of skilled job openings, compared to just 19% for automation. This imbalance extended to training as well, with four in five (80%) available courses centred on AI rather than automation.

However, the sector’s overall training availability score was just 3.6, signalling a need for proactive efforts to prepare the workforce and keep pace with other sectors. 

According to 2024 research, 75% of banking firms are already using AI, with a further 10% planning on using it over the next three years. Investment in AI technologies, such as chatbots and automated SMS for conversational banking, is already proving to significantly enhance customer engagement, improving response times while streamlining operations.

As the data shows, the banking sector is preparing for an AI-driven future, but must prioritise investment in training to ensure its workforce is ready in the long term. 

The industries lagging behind in automation and AI adoption

Automation skills gap, overall ranking by sector

Sector	Overall automation score	Automation job demand	Automation training availability
IT & Telecoms	279.9	251.8	28.1
Engineering	246.8	215	31.8
Manufacturing	46.1	37.9	8.2
Financial Services	36.2	20.8	15.4
Accountancy (Combined)	30.4	20.3	10.1
Sales	29	19.5	9.5
Transport & Logistics	28.8	2.5	26.3
Marketing & PR	22	6.7	15.3
Education	20	0.1	19.9
Banking	14.7	13.4	1.3
Energy	10.6	1.8	8.8
Legal	9.9	3.6	6.3
Retail	5.9	0.3	5.6
Insurance (General)	5.4	4.3	1.1
Health & Medicine	5.3	0.1	5.2
Human Resources	4.7	1	3.7
Construction & Property	4.2	0.8	3.4

Construction and property is the least prepared for automation

With an overall index score of just 6 out of a possible 1,600, the construction and property sector ranks lowest in preparedness for AI and automation. Job demand in this sector is particularly low, scoring just 1.5 out of 1,200, while training availability is 4.9 out of 400, highlighting limited investment in digital development. 

The demand for automation-related roles (0.8) was slightly higher than AI-specific roles (0.3), however, both were considerably low on average. 

Training availability reflects a similar pattern with 77 courses for automation and just 66 for AI, underscoring an untapped potential for digital skills development. Despite these challenges, construction and property outperformed some other sectors in training availability, suggesting a baseline recognition of the need to upskill. 

However, the overall low scores in both job demand and training provision indicate limited investment into the hiring of skilled workers and perhaps the adoption of advanced technologies, signalling a gap in current capabilities and future needs that may be leaving some businesses operating with outdated systems. 

This is especially low, considering the global market for AI in construction was estimated at $1.8 billion in 2023 and is projected to reach $12.1 billion by 2030. The largely hands-on nature of construction work may reduce the urgency to digitalise; however, as the market value reflects, there is a growing opportunity in both construction and property to use AI and automation, such as mobile messaging, to keep customers informed. 

Between 2022 and 2025, job vacancies also dropped by 40%, reflecting a broad slowdown in hiring. Coupled with limited investment into upskilling and reskilling initiatives, this decline leaves the industry with the most work to do to improve digital competitiveness.

Manufacturing prioritises automation but faces a critical skills gap

The manufacturing sector scored 46.2 out of 1,600 in the Automation & AI Readiness Index, ranking sixth overall. This places it just behind its counterpart, engineering, which scored significantly higher, revealing a notable gap between the closely related industries. 

With an AI score of 0.1, the sector’s near-total focus on automation (46.1) places it among the top three for investment in this area, but exposes a stark gap in AI readiness. 

Listings for automation roles made up 99.4% of total available jobs analysed, with just one AI-related role open. Yet, course availability for automation remains low at just 8.2, revealing a significant training gap that could impact the sector’s ability to scale automation effectively. 

Compared to IT & telecoms and the engineering sectors, which boasted training availability scores of 28.1 and 31.8, respectively, manufacturing lags in automation workforce readiness, with investment in AI-related job positions and training critically low. 

If left unaddressed, this disparity risks leaving manufacturing firms unable to fully harness the potential of advanced technology or keep pace with digital transformation across industries.  

Key industry bodies have already recognised this growing challenge, with Make UK launching the Industrial Strategy Skills Commission to help find a solution to the growing manufacturing and engineering skills deficit across the UK. 

This comes as the UK government has allocated £4.5 billion over five years, starting in 2025, to stimulate growth and innovation across industries integral to the economic landscape, with a strong emphasis on advanced manufacturing. Funding signals a significant step toward supporting the sector’s evolution, which may alleviate the limited training availability. 

Manufacturing also saw a 48.4% drop in vacancies between 2022 and 2025, highlighting a slowdown in the labour market. This downturn may be linked to limited training opportunities and a shortage of skilled workers, both of which could be suppressing sector growth and deterring new talent from entering the industry. 

AI skills gap, bottom 5 industries

Sector	Overall AI score	AI job demand	AI training availability
Manufacturing	0.1	0.1	0
Transport & Logistics	0.5	0.2	0.3
Construction & Property	1.8	0.3	1.5
Energy	3.1	0.8	2.3
Retail	4.5	1.2	3.3

Retail struggles with low automation and AI readiness

The retail sector ranked second lowest in the Automation & AI Readiness Index, with an overall score of just 10.4 out of 1,600. With an automation index score of 5.9 and an AI index score of 4.5, the sector demonstrates minimal adoption and investment in digital tools and talent.

While overall job demand for these specialisms in the sector is low, AI roles account for 75% of the skilled positions analysed. However, training availability is limited, with scores of just 5.6 for automation and 3.3 for AI indicating that retailers are not yet actively preparing their workforces for technological developments. 

This low readiness contrasts sharply with the projected growth of the global retail automation market, which is expected to rise from $31.77 billion in 2025 and is projected to reach $71.91 billion by 2034. As retail automation becomes more widespread, it will likely play a greater role in areas such as inventory management, order processing, SMS marketing communications and customer service, to streamline operations, reduce human error, and enhance the overall shopping experience.

Despite the growing market potential on the horizon, the sector’s underinvestment in skills and training for advanced technologies threatens to leave many retailers training in the race towards automation-driven transformation. 

Health and medical sees more training than demand 

Ranking 16th overall with a modest index score of 14.3 out of 1,600, the health and medical sector lags behind but shows a notably forward-thinking approach to workforce readiness. 

While current job demand is low, at just 0.5, its relatively high training availability score of 13.8 places it within the top ten sectors, signalling proactive investment in upskilling and preparing the workforce ahead of expected growth in automation and AI roles. 

This comes as healthcare organisations appear poised to capitalise on automation, as in 2024, 43% of healthcare leaders reported using AI for in-hospital patient monitoring, and 85% are planning further AI investments. The healthcare automation market is projected to more than double in the next 10 years, reaching $95.53 billion in 2034, compared to $39.29 billion in 2024. 

The sector also experienced the strongest cumulative workforce growth, with jobs increasing by 8.1% from 4,679,000 in 2022 to 5,059,000 in 2024. At the same time, vacancies fell sharply by 35.8% between 2022 and 2025, reflecting a drop in demand for new hires.

While technologies such as AI-powered diagnostics and automated scheduling can ease administrative burdens and improve accuracy in healthcare, the report reveals a disconnect between job demand and investment. Realising the full potential of automation in healthcare will require not only greater investment in training but also the recruitment of skilled professionals to implement and manage advanced systems.

AI skills gap, overall ranking by sector

Sector	Overall AI score	AI job demand	AI training availability
IT & Telecoms	498	443.7	54.3
Engineering	121.9	89.2	32.7
Banking	32.8	30.5	2.3
Marketing & PR	28.4	13.4	15
Education	25.3	1.5	23.8
Financial Services	22	4	18
Legal	14.9	2.4	12.5
Accountancy (Combined)	14.5	4.6	9.9
Sales	12.1	0.4	11.7
Health & Medicine	9	0.4	8.6
Human Resources	5.8	3.8	2
Insurance (General)	5.2	3.4	1.8
Retail	4.5	1.2	3.3
Energy	3.1	0.8	2.3
Construction & Property	1.8	0.3	1.5
Transport & Logistics	0.5	0.2	0.3
Manufacturing	0.1	0.1	0

Disjointed readiness signals skills gaps in many sectors

Marketing and PR ranked toward the top end of the Automation & AI Readiness Index, with an overall score of 50.3 reflecting a well-rounded investment in both automation and AI, along with an upskilling effort shown in its training availability score of 30.3. This indicates proactive workforce development to meet the growing technological demands of the industry.

Education took a different approach, instead standing out for its future-proofing strategy. With an overall index score of 45.3, the sector reported one of the highest training availability scores (43.7), especially in AI (23.8), indicating strong foresight and clear commitment to long-term investment in digital readiness. This also put it ahead of sectors like financial services (33.4) and marketing and PR (30.3) in training provision.

However, with one of the lowest skilled job demands (1.6), the sector appears held back by a structural challenge as a shortage of digitally skilled educators may be slowing the transition of training investment into more tangible workforce transformation. Nonetheless, this infrastructure positions the education sector as a key enabler of digital literacy, which will boost skills not just within its workforce but across sectors.

Accountancy (44.9) and sales (41.2) both scored moderately, with primary focus on automation investment over AI. Both sectors showed higher job demand for automation skills (20.3 in accountancy and 19.5 in sales), however, training infrastructure in both industries is underdeveloped, signalling a need for upskilling strategies. 

In transport & logistics, the focus skewed heavily towards automation (28.8), with AI uptake nearly non-existent (0.5). Although job demand was modest (2.7), investment in automation training (26.3) was notably heavier, likely in response to operational pressures to improve automation transport and logistics automation for better efficiency.

Legal services (24.7) placed more emphasis on AI (14.9) than on automation (9.9), with training investment aligning accordingly (12.5 and 6.3, respectively). While current job demand remains low (6.0), the sector appears to be laying the groundwork to start leveraging AI. 

The energy sector recorded a low overall score of just 13.8, with modest automation adoption (10.6 out of 800) and minimal AI integration (3.1). Although job demand is low, with just 22 relevant positions out of 640 open roles, a training availability score of 11.2 suggests some early-stage efforts to build digital capacity. Workforce growth of 3.73% between 2022 and 2024, paired with a 55.6% drop in vacancies, signals a sharp cooling of the hiring market, which may result in talent bottlenecks. 

Insurance scored just 10.7 overall, remaining underinvested across the board with nearly equal scores in automation (5.4) and AI (5.2). Weak job demand (7.7) and a low training availability (3.0) point to missed opportunities in a sector where streamlined workflows and predictive analytics could offer significant efficiency gains.

HR closely followed with a score of 10.5, albeit had a slightly higher AI index score (5.8) than automation (4.7). Automation training (3.7) also marginally outpaced AI training (2), however, both figures indicate minimal upskilling despite HR being a sector ripe for transformation through AI-powered recruitment and workforce analytics.

Closing the automation skills gap: How businesses can become digitally ready

As industries face increasing pressure to adopt automation and AI technologies, our ‘Automation Skills Gap Report’ reveals that many sectors will be held back by a widening skills gap. This critical challenge is more than just an underskilled workforce, as it puts companies at risk of falling behind more digitally mature competitors, and threatens the UK’s leadership in innovation and technology on a global stage. 

Bridging the gap requires a proactive approach to upskilling, empowering teams to adapt to new tools and investing in technologies that will streamline operations and strengthen customer relationships. 

1. Upskill and reskill your workforce

Businesses should invest in targeted upskilling programmes in automation engineering and tools, AI technologies, and digital communication platforms, which are essential to ensure teams can adapt and thrive in increasingly digital environments.

2. Use automation to enhance, not replace, human teams

Automation can support, rather than replace, human interactions, which are integral to maintaining strong customer relationships. Automating repetitive tasks like FAQs, order updates, and appointment confirmations, through methods such as SMS automation, allows staff to prioritise complex, value-driven work and improve efficiency on tasks. 

3. Deliver seamless 24/7 support through automation

With a growing skills gap, investing in user-friendly tools like AI-powered chatbots and automated SMS software can provide an immediate, scalable solution. These technologies ease pressure on human resources and enable real-time engagement on familiar platforms, ensuring customers receive timely responses around the clock.

Methodology

To assess automation and AI readiness, Esendex collected and analysed the number of open automation and AI job roles available across 17 industries using Reed. Search terms included titles such as ‘automation engineer’, ‘automation controls engineer’, ‘robotic process automation’, ‘automation test analyst’, ‘machine learning engineer’, and ‘data engineer’, ‘data scientist’, ‘algorithm developer’, ‘AI developer’, and ‘python engineer’. 

The team then analysed data on the number of relevant training courses available in automation and AI for each sector from Reed’s course listings, to produce the overall Automation & AI Readiness Index. 

Finally, sector-level employment statistics were cross-referenced using Office for National Statistics (ONS) data, including workforce size and vacancy rates between 2022 and 2025, where available, to provide an in-depth analysis of industry readiness and demand for automation and AI adoption.