Is AI leading to job losses or job evolution?

We’ve started to establish that AI is helping roles to evolve. But how is it doing that? As intelligent systems take on routine tasks, human roles are shifting toward higher-value, more strategic work. This evolution is creating hybrid roles, redefining job descriptions, and opening doors to entirely new career paths. For large organisations, understanding this shift is critical to staying competitive and future ready. With Gartner reporting that 77% of CEOs pursuing cost efficiency measures, integrating AI with existing employee bandwidth can be highly beneficial. 

What does job augmentation look like in practice?

Job augmentation refers to the process of enhancing human roles with AI tools, rather than replacing them. In practice, this means employees are supported by AI to make faster decisions, reduce manual work, and focus on creative or interpersonal tasks. According to PwC and the World Economic Forum, this approach is already reshaping work across industries, with up to 40% of global working hours expected to be impacted by GenAI in the next five years. 

Characteristics of Job Augmentation 

• Human-machine collaboration: AI supports workers in decision-making, creativity, and complex problem-solving. 
• Improved job quality: Augmentation can reduce repetitive tasks and increase employee satisfaction. 
• Productivity gains: GenAI can free up time for higher-value activities, with some roles reporting up to 50% time savings on certain tasks. (PwC Leveraging Generative AI for Job Augmentation and Workforce Productivity) 

Many organisations are investing heavily in upskilling and reskilling. Internal learning platforms, partnerships with edtech providers, and AI literacy programs are becoming standard. The investment into people will likely have an impact on the engagement and retention of employees as they will recognise that the organisation wants them to succeed. Engaged employees will often deliver more from a financial and innovation standpoint. The engagement piece, particularly in higher turnover sectors like manufacturing and retails, can have a significant impact on retention. We’ve discussed strategies to improve engagement in both retail and manufacturing sectors in our blog.

Retaining talent in an AI-augmented workplace requires thoughtful engagement strategies. Our guide to retention strategies in the operational workforce offers actionable insights to help operational teams stay motivated and future ready.

Many are conducting internal audits to assess which roles are most exposed to automation and where augmentation can add value. Workforce planning is increasingly data-driven, with HR and strategy teams collaborating to map future skill needs. Ultimately, it’s about taking the first step with AI, as Oli Quayle notes in Episode 6: Future Proof Your People with L&D of our Do the Best Work of Your Life series:

"You don't have to do a lot to get a lot of value early on, but what you have to do is take the first step. And so depending on your priority and what you're looking at, I guarantee you the first thing you should look at is what have you already got and how can you leverage what you've got and use AI to either update it or to make it more bite-sized so that it's easier for your organisation to do it in small pieces rather than a 90-minute course on a Friday that nobody really wants to be doing."

Taking inspiration from large companies can be beneficial for your organisation:  

Unilever

Unilever has launched multiple initiatives to future-proof its workforce:

• In 2024, over 23,000 employees were trained in AI, particularly within supply chain teams, to support digital transformation and open new career pathways. [unilever.com]
• The company partnered with Walmart, Accenture, and SkyHive to pilot AI-driven reskilling programs, using data analytics to identify hidden skills and redeployment opportunities. [unilever.com]
• Unilever’s factories involved in the WEF-McKinsey “Frontline Talent of the Future” initiative saw a 28% improvement in productivity through talent-focused AI integration
  

HSBC

HSBC is embedding AI across its global operations:

• The bank has deployed over 600 AI use cases, including fraud detection, customer service, and credit analysis. [hsbc.com]
• In Wealth and Personal Banking UK, GenAI tools assist customer support agents, improving service quality and reducing wait times.
• HSBC has launched an AI Academy to train staff from beginner to advanced levels, alongside mandatory training in responsible AI use.

Want to see how digital transformation can empower your operational teams? Download our guide to digital transformation for operational teams and explore real-world strategies for integrating AI and automation into everyday workflows.

What skills will be most valuable in an AI-driven workplace?

As AI steps in to help with routine tasks, human skills become even more valuable. Some of the most valuable capabilities include:

Adaptability

In a landscape where tools, workflows, and even job titles are constantly changing, adaptability is key. Employees must be comfortable with:

• Continuous learning: Staying current with new technologies and methodologies.
• Role fluidity: Embracing hybrid responsibilities that blend technical and interpersonal tasks.
• Experimentation: Testing new AI tools and workflows without fear of failure.

Organisations can foster adaptability by creating a culture of curiosity, offering microlearning opportunities, and encouraging cross-functional collaboration.

Critical thinking

AI can generate insights, but it can’t judge their relevance or ethical implications. Critical thinking ensures that:

• Employees can interpret AI outputs with context and caution.
• Teams can challenge assumptions, especially when AI recommendations conflict with human values or business goals.
• Decision-making remains strategic and accountable, not blindly automated.

This skill is especially vital in sectors like finance, legal, and healthcare, where AI must be used responsibly and transparently.

Emotional intelligence

AI lacks empathy, intuition, and the ability to build trust. These qualities remain central to leadership, teamwork, and customer engagement. Emotional intelligence includes:

• Empathy and active listening: Understanding stakeholder needs and concerns.
• Communication: Translating complex AI-driven insights into clear, actionable messages.
• Leadership: Guiding teams through change with confidence and compassion.

In an AI-driven workplace, emotionally intelligent leaders will be the ones who can unite human and machine capabilities into a cohesive, productive force.

The question of whether AI is leading to job losses is no longer theoretical. Across sectors, automation and generative AI are reshaping roles, reducing headcounts, and prompting large-scale workforce restructuring. But again, it’s important to focus on the fact that roles are being restructured, relocated, or augmented.

The current picture of UK job losses due to AI

The Institute for Public Policy Research (IPPR) and the Tony Blair Institute vary significantly in their projections for job losses, which paints a clear picture of businesses being unsure what AI can and cannot do. The IPPR says that up to 8 million UK jobs are at risk from AI if no action is taken, but the Tony Blair Institute offers a more conservative estimate: 1 to 3 million UK jobs could be displaced over the next two decades, with 60,000 to 275,000 jobs potentially lost annually.

Sector breakdown

• Retail: The UK’s largest private employer has seen a 225,000 job reduction over five years, driven by automation (e.g. self-checkouts, inventory tracking) and outsourcing. [itsupplychain.com]
• Finance: Job postings in finance dropped 38% in 2025, with AI replacing roles in compliance, reporting, and customer service. [business-standard.com]
• Manufacturing: Robotics and predictive maintenance are reducing manual roles. Globally, up to 20 million manufacturing jobs could be lost by 2030. [sqmagazine.co.uk]
• Logistics: AI-driven warehouse automation has led to staff reductions of up to 80% in some UK facilities. [sqmagazine.co.uk]

What does it mean for a role to be restructured, replaced or relocated?

• Replaced: Jobs fully eliminated due to AI (e.g. data entry, routine customer service).
• Restructured: Roles adapted to include AI oversight or strategic tasks (e.g. HR managers using AI for screening).
• Relocated: Jobs moved to different departments or geographies due to AI efficiencies or outsourcing.

Automation and AI is embedded across various industries, from manufacturing floors to finance departments. According to PwC's 2024 UK Economic Outlook, around 30% of UK jobs could be impacted by automation by 2030, with the potential for both displacement and transformation. The Office for National Statistics reported in early 2025 that approximately 8% of current UK jobs face a high probability of automation within the next decade, particularly in sectors reliant on routine tasks and predictable workflows.

Enterprise organisations are investing in AI to drive efficiency, with cost efficiency measures at the forefront (77% pursuing them – Gartner Benchmarking). Many roles are being augmented rather than eliminated, with AI handling repetitive elements whilst humans focus on judgement, creativity, and relationship management. Understanding which functions face the greatest exposure helps HR and business leaders develop more informed workforce strategies.

Can finance jobs be replaced by AI?

Finance functions in large organisations are experiencing significant automation, particularly in transactional and data-intensive areas. These systems can process thousands of transactions with minimal error rates, often completing work in minutes that previously required days of manual effort.

1. Automation in accounting, auditing, and forecasting - Machine learning algorithms now handle much of the heavy lifting as they can extract data from multiple systems, identify discrepancies, and flag anomalies for review.
2. AI-powered risk modelling - Risk assessment and financial modelling are areas where AI demonstrates considerable capability. Large organisations use machine learning to assess credit risk, detect fraud, and model scenario planning at speeds humans cannot match. Real-time transaction monitoring powered by AI can significantly reduce false positive rates compared to rule-based systems.

Despite these advances and automations, finance roles still require that all important human judgement, interpretation, and ethical consideration. We’ve discussed the ethical use of AI in our article ‘AI in Financial Services: How HR Can Prepare Financial Services Teams for Ethical AI Adoption’. Sometimes, professional expertise, particularly in complex or ambiguous situations, trumps any potential AI input. So whilst AI can provide significant support in financial roles, finance professionals who advise on commercial decisions, challenge assumptions, and translate data into strategic insight continue to add value that extends well beyond what automation can deliver. 

Will AI replace retail jobs?

Retail has been at the forefront of automation for many years, with large organisations investing heavily into tech that improves the customer experience. The technology has become so ingrained in our lives, it may not be immediately obvious.

Self-checkout systems, inventory automation, and customer service bots

Self-service checkouts are now ubiquitous in UK supermarkets and retail chains. According to recent consumer research by PMC Commerce, 87% of UK shoppers have used self-checkout systems, with larger retailers now dedicating up to 50% of their tills to these machines. The Office for National Statistics reported that retail jobs fell to 2.81 million in September 2024, down 225,000 compared to five years earlier, driven partly by automation alongside other factors including outsourcing of warehousing and logistics.

Inventory management is also supported significantly by automation as AI-powered systems track stock levels in real time, predict demand patterns, and trigger automated replenishment. Customer service chatbots also handle routine queries across digital channels and funnel any complex or escalated issues to human agents.

Will retail employees be replaced?

The retail sector illustrates the distinction between automation and replacement particularly well. Whilst transaction processing and basic information queries are increasingly automated, roles requiring problem-solving, emotional intelligence, and product expertise remain human-centric. The British Retail Consortium notes that despite job declines, the industry remains the largest private sector employer, providing approximately 2.9 million jobs in the UK with another 2.7 million in the supply chain.

Retail jobs combining technical skills with customer relationship capabilities continue to grow, even as purely transactional roles decline. Personal shoppers, visual merchandisers, and customer experience specialists represent areas where human skills complement rather than compete with AI. Pay growth in retail averaged 8.5% in 2024, well above the national average, reflecting the changing nature and value of remaining roles.

Impact on logistics and warehousing

Large distribution centres increasingly use robotics for picking, packing, and sorting. Research from McKinsey estimates that approximately one-third of retail tasks could be displaced by automation by 2030, with warehouse operations particularly affected.

However, even in highly automated facilities, human workers remain essential for quality control, exception handling, and maintenance.

Will AI replace operations management?

• AI in supply chain optimisation and predictive analytics
• Strategic decision-making still requires human input

Operations management relies heavily on data analysis and process optimisation, which AI excels at. However, operations decisions remain a human responsibility. Determining which markets to enter, how to respond to supply chain disruptions, or when to invest in new capabilities involves judgement and risk assessment that extends beyond data analysis. Operations management is a prime example of AI and humans working together as teammates. Rand have recently published an insightful article on the concept of a machine as your new teammate, and if humans are ready for that, with automation bias being one of the major concerns. Automation bias is essentially an over-reliance on an automated system, which can lead to errors. AI can handle:

• Demand forecasting
• Route optimisation
• Inventory management
• Pattern analysis
• Predictive maintenance

Humans, furnished with data processing and recommendations, can then:

• Provide context
• Challenge assumptions
• Make final decisions

Relationship management, stakeholder communication, and driving organisational change require emotional intelligence and cultural awareness that AI cannot replicate.

Will mechanical engineering be replaced by AI?

Engineering represents one of the fields where AI's limitations become most apparent. Whilst AI can optimise designs based on defined parameters and simulate performance under various conditions, defining those criteria, understanding real-world constraints, and evaluating trade-offs requires engineering judgement that remains distinctly human. [research.autodesk.com]

Physical testing and validation remain essential in mechanical engineering, particularly for safety-critical applications. Actual testing under real conditions identifies issues that models may not capture, especially in regulated industries like automotive and aerospace. [ntrs.nasa.gov]

Innovation in engineering often emerges from deep domain expertise, cross-disciplinary thinking, and creative problem-solving that extends beyond what AI can currently deliver. While generative design tools can suggest optimised solutions, selecting the best option still requires human insight. [autodesk.com]

AI will continue to automate routine tasks and streamline operations; however, all roles will still require human input to function effectively. Jobs that rely on emotional intelligence, creativity, and complex decision-making are less susceptible to automation. Many creative roles will generate original ideas with specific emotional resonance. Therapists and counsellors depend on empathy, trust, and a nuanced understanding of human behaviour to provide essential care. Strategic leaders across all industries also navigate ambiguity, balance competing interests, and make judgement calls that incorporate data but go beyond it.

Can human resources be replaced by AI?

AI in human resources can be an incredibly valuable tool, particularly in large organisations, where the recruiting process involves many steps, across different departments, locations, and high numbers of applicants. AI can support HR in:

• Recruitment: AI tools screen CVs, match candidates to roles, and can even conduct initial interviews
• Onboarding: Automated workflows help new hires complete paperwork, access training, and integrate into systems
• Performance tracking: AI can analyse productivity metrics and flag patterns for review
• Absence tracking: AI can track and analyse absence patterns

However, once again, the human side of HR remains irreplaceable. Conflict resolution, fostering workplace culture, and supporting employee wellbeing demand empathy, discretion, and trust. Ultimately, HR professionals are at the forefront of company culture and advocates for the people in their organisations.

Roles that require human empathy and judgment

Some professions are deeply rooted in human connection and moral reasoning. For example:

• Healthcare: Doctors and nurses make life-altering decisions and provide emotional support to patients and families.
• Education: Teachers adapt to diverse learning needs, inspire curiosity, and nurture growth.
• Leadership: Effective leaders motivate teams, resolve ethical dilemmas, and build inclusive environments.

As highlighted in RAND’s commentary, AI is reshaping jobs. RAND researchers found that while some businesses have reduced employment by automating tasks, a larger share reported increases in employment related to AI adoption. 

In sectors like transportation and warehousing, AI adoption was just over 2%, while finance and insurance saw around 10%, and even in information technology, only 25% of businesses were using generative AI to produce goods and services. 

The commentary also emphasises that fears of mass unemployment may be overstated. As Jonathan Welburn and Vegard Nygaard write:

“Jobs are more than individual tasks. They are a string of tasks assembled in a specific way. They involve emotional intelligence. Crude calculations of labour market exposure to AI have seemingly failed to account for the nuance of what jobs actually are.”

As artificial intelligence continues to influence workplace structures and processes, large organisations are increasingly assessing how best to prepare their workforce for ongoing change. Strategic planning across HR, operations, and leadership functions can help mitigate disruption and support long-term adaptability. For a deeper dive into how large organisations can restructure roles and future-proof their teams, download our guide to operational workforce transformation, which offers practical frameworks for aligning workforce strategy with AI-driven change.

Organisations can start with the following:

1. Workforce Audits - Conduct role-based assessments to identify positions most susceptible to automation
2. Skills Development Initiatives - Introduce targeted upskilling programmes focused on digital literacy, emotional intelligence, and systems thinking
3. Employee Engagement and Change Readiness - Support employees through transitions by promoting continuous learning and open communication

AI is not expected to eliminate all jobs, but it is altering how tasks are performed and how roles are defined. While some positions may be phased out, others are being reconfigured to incorporate new tools and workflows. Roles that depend on human judgement, empathy, and creativity are likely to remain essential.

Organisations that take a proactive approach to workforce planning and invest in employee development may be better positioned to navigate future disruptions. Oli Quayle summarises this sentiment about the proactive approach in Episode 8: Supercharge talent & drive performance:

"You need to start taking action now. Make sure you're using something that’s secure for your company, private for you personally, and based on roles and permissions. Get on it, because the sooner you learn how to interact with AI, the better. Prompt engineering is a real skill. You can even ask AI, 'How do I get the best out of you?'—and it will tell you. That’s pretty cool, isn’t it?"

PeopleXD Evo integrates artificial intelligence across the full spectrum of HR functions, supporting organisations in automating routine processes, enhancing decision-making, and improving employee experience.

Its AI capabilities include predictive analytics for workforce planning, intelligent automation of administrative tasks, and tools for personalising employee engagement at scale. By embedding AI into core workflows, PeopleXD Evo enables HR teams to respond more effectively to organisational change while maintaining a focus on people-centred outcomes.