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Fair warning . Five traps to avoid when using AI . Is AI your future teammate? 8 . | Redrawing the career curve . 19 . Overcoming investor bias . 35 . | Prevent digital plans failing . 53 .
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FIRST WORD.
Winner Excellence Awards 2025
In this edition you can learn more about her research, including how AI will transform teamwork and five traps that business leaders must avoid when using AI. Our Gillmore Centre for Financial Technology is exploring the use of AI in fintech, insurance, and property. Discover some of that research on page 27, where Ruowen Xu and Yuval Millo reveal the risks of using AI-generated synthetic data without understanding its limitations. WBS also played a key role in Nobel laureate Christopher Pissarides’ Review into the Future of Work and Wellbeing, leading the research on how companies should implement AI. Alongside this, we offer a range of programmes for professionals who are keen to develop their expertise in AI and digital transformation. This includes our two-day AI Leadership programme at The Shard, four Master’s programmes, and dedicated modules across our MBA programmes and wider teaching portfolio. You can also try steering your own AI start-up through its crucial early years using the Slingshot simulation, which was developed by Ammon Salter and is free to access. Of course, it is not just AI that is shaping the future of work. Also in this edition, Loizos Heracleous reveals why most digital transformation projects fail and how to make yours succeed (see page 53). Gongtai Wang and Susanne Beck share their new framework to help companies capture greater value from the connected products they create (see page 40). And, on page 16, WBS alum Lizzie Penny, who was recently named one of HR Magazine’s most influential thinkers, encourages business leaders to embrace autonomous working. After all, human expertise remains vitally important in the age of AI.
Core Edition 17 Editor: Warren Manger Cover image: Paul Atkins © Getty Images Staff contributors: Simon Wilcox Paul Atkins Donna Morris Mark Udall Rebecca Cutts © 2026 University of Warwick. All rights reserved. Neither this publication nor any part of it may be reproduced, stored in a retrieval system, or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior permission of the department of Warwick Business School at the University of Warwick. Published by Warwick Business School, University of Warwick, Coventry, CV4 7AL.
A round 40 per cent of (AI), according to the International Monetary Fund. It is increasingly clear that the future will favour those who recognise AI’s potential and deploy it effectively. At Warwick Business School, we are equipping business leaders with the knowledge to do that. Our faculty is delivering a range of world-class research on how companies can harness AI, spearheaded by Hila Lifshitz and her colleagues within the AI Innovation Network. Her work with thought leaders jobs globally are exposed to artificial intelligence such as Ethan Mollick at Wharton and researchers at Harvard Business School is shaping our understanding of how to use AI in the workplace.
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Where opinion is expressed, it is the opinion of the author and does not necessarily coincide with the views of the publisher or the University of Warwick. All information in this magazine is verified to the best of the authors’ and the publisher’s ability. However, Warwick Business School and the University of Warwick do not accept responsibility for any loss arising from reliance on it.
Professor Andy Lockett Dean of Warwick Business School.
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IN THIS ISSUE.
FUTURE OF WORK.
8. The AI-Team. Can AI improve collaboration? by Hila Lifshitz. 11. Self less? Avoid making yourself replaceable by Giovanni Radaelli. 14. Work of art. Finding beauty and meaning in unskilled work by Marjolaine Rostain. 16. Free style.
LEADERSHIP.
DIGITAL INNOVATION & ENTREPRENEURSHIP.
38. Blind data. A better way to buy consumer information by Ram Gopal.
24. Keep the faith.
Why autonomous work is the future by Lizzie Penny.
30: Cover story. Fair warning. Five traps to avoid when using AI by Warren Manger with: Hila Lifshitz, Steven Randazzo, Nick Chater, and Anh Luong. 34. 5 reads you need to harness Artificial Intelligence. 35. Pitch blacklisted. How female founders can beat gender bias by Noni Symeonidou and Dawn Eubanks. .
The value of an explicit psychological contract by Tina Kiefer, Graeme Currie, and Nicola Burgess.
40. The missing link. Capturing the lost value from
19. Over the hill. Are many careers peaking earlier than expected? by Redzo Mujcic. 22: Change maker. In it for the long run. How Bhavesh Vaghela is harnessing AI.
connected products by Gongtai Wang and Susanne Beck.
CAREERS.
FINANCE & MARKETS.
43. Using AI to boost your career .
27. Factory flaw. Beware the hidden risks in synthetic data by Ruowen Xu and Yuval Millo.
Artificial intelligence is rapidly reshaping how organisations hire by Sarah Jackson and Kate Friend.
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STRATEGY & ORGANISATIONAL CHANGE. 50. Reel deal. How should digital platforms pursue growth? by Joe Nandhakumar and Jochem Hummel.
49. How smart firms will measure marketing. by Laura Chamberlain.
DECISION-MAKING & ANALYTICS.
46. Hard sell.
5 steps to survive the B2B sales revolution by Nick Lee and Roland Kassemeier.
HEALTHCARE & WELLBEING.
53. Failure to launch. Prevent your digital transformation falling short by Loizos Heracleous.
56. Detri-mental. Tackling the mental health productivity crisis by Vicki Belt.
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CONTRIBUTORS. We believe that business should be used as a power for good. Our faculty of research and teaching academics is constantly striving for excellence in everything it does, from the latest groundbreaking research impacting on society, to inspiring our students. Contributors to Core include research-active academics, who produce cutting- edge theories with real-world impact, and Professors of Practice, who bring their knowledge gained from successful senior business and industry experience.
17 SUSTAINABLE DEVELOPMENT GOALS TO TRANSFORM OUR WORLD
HILA LIFSHITZ Professor of Information Systems Management & Analytics Hila.Lifshitz-Assaf@wbs.ac.uk
TINA KIEFER Professor of Organisational Behaviour Tina.Kiefer@wbs.ac.uk
GIOVANNI RADAELLI Associate Professor (Reader) of Operations Management Giovanni.Radaelli@wbs.ac.uk
GRAEME CURRIE Professor of Public Management Graeme.Currie@wbs.ac.uk
The 17 Sustainable Development Goals (SDGs), represented by the icons above, lie at the heart of the United Nations’ (UN’s) Agenda for Sustainable Development. They were adopted by all UN member states in 2015, creating a blueprint for a global partnership to provide peace and prosperity for all. They recognise that ending poverty and other deprivations must go hand in hand with strategies that improve health and education, reduce inequality and spur economic growth – all while tackling climate change and preserving our oceans and forests. WBS is committed to embedding the SDGs in its research, teaching and day-to-day operations. This includes striving to improve equality, diversity, and inclusion for under- represented and under-privileged groups. Alongside each article in Core , you will see one or more of the 17 SDG icons to show with which goals the associated research is aligned. We all have a role to play in building the better world we want to see.
MARJOLAINE ROSTAIN Assistant Professor of Information Systems Management & Analytics Marjolaine.Rostain@wbs.ac.uk
NICOLA BURGESS Visiting Professor of Operations Management
RUOWEN XU Associate Professor of Accounting Ruowen.Xu@wbs.ac.uk
LIZZIE PENNY WBS alum and Joint CEO of Hoxby
REDZO MUJCIC Associate Professor of Behavioural Science Redzo.Mujcic@wbs.ac.uk
YUVAL MILLO Professor of Accounting Yuval.Millo@wbs.ac.uk
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STEVEN RANDAZZO PhD Researcher and Co-Chair of the AI Innovation Network Steven.Randazzo@warwick.ac.uk
GONGTAI WANG Associate Professor of Information Systems Management & Analytics Gongtai.Wang.2@wbs.ac.uk
JOCHEM HUMMEL Associate Professor of Information Systems Management & Analytics Jochem.Hummel@wbs.ac.uk
ROLAND KASSEMEIER Associate Professor of Marketing Roland.Kassemeier@wbs.ac.uk
LOIZOS HERACLEOUS Professor of Strategy Loizos.Heracleous@wbs.ac.uk
LAURA CHAMBERLAIN Professor of Marketing Laura.Chamberlain@wbs.ac.uk
NICK CHATER Professor of Behavioural Science Nick.Chater@wbs.ac.uk
SUSANNE BECK Associate Professor of Information Systems Management & Analytics Susanne.Beck@wbs.ac.uk
ANH LUONG Assistant Professor of Business Analytics Anh.Luong@wbs.ac.uk
SARAH JACKSON Alumni and MBA Careers Manager Sarah.Jackson@wbs.ac.uk
NICK LEE Professor of Marketing Nick.Lee@wbs.ac.uk
VICKI BELT Director of Engagement and Impact, Enterprise Research Centre Vicki.Belt@wbs.ac.uk
DAWN EUBANKS Associate Professor of Behavioural Science & EI Dawn.Eubanks@wbs.ac.uk
KATE FRIEND Director of CareersPlus & Employer Relations Kate.Friend@wbs.ac.uk
DAVID RODRIGUEZ Senior Client Partner at talent consultants Korn Ferry
NONI SYMEONIDOU Associate Professor of
Entrepreneurship & Innovation Noni.Symeonidou@wbs.ac.uk
Download past editions of Core magazine for more insights from Warwick Business School. Read more now
RAM GOPAL Professor of Information Systems Management Ram.Gopal@wbs.ac.uk
JOE NANDHAKUMAR Professor of Information Systems Joe.Nandhakumar@wbs.ac.uk
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AI IN THE WORKPLACE
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Future of Work
T eamwork is the social interaction – people enjoy connecting with other people. Teams also tend to produce better results than individuals. They can tackle more complex problems, pool their expertise, and distribute the workload to improve efficiency. Credit for their collective endeavours can also be shared in a way that is good for morale. As the old adage goes, “There is no ‘I’ in team.” But what about AI? Many organisations have already adopted AI tools in one form or another. Could the next step be cybernetic teams where humans and AI work hand in hand? After all, most Large Language cornerstone of many modern organisations. This is hardly surprising. It meets a basic need for Models (LLMs) – such as ChatGPT, Claude, and Google Gemini – are trained on human language and often act more like a person than a machine. If businesses were to treat generative AI as a team member, what impact would that have on performance, collaboration, and innovation? I set out to explore these questions in my recent research with colleagues from Harvard, Wharton, ESSEC Business School, and Proctor and Gamble (P&G). We conducted a field experiment with 776 professionals at P&G, which owns global brands such as Gillette, Oral B, and Pampers. The professionals were all new product development experts; some had experience in research and development (engineers and scientists), others were marketing and commercial experts. Each professional was asked to complete a product innovation challenge. Some worked
individually, others in pairs. Some had access to AI, others did not. Our findings have significant implications for how organisations should structure teamwork in the age of AI. 1 . AI boosts performance. Individuals who did not use AI produced the lowest quality proposals. Those working in two-person teams produced higher- quality outputs, but took slightly longer to do so. Crucially, individuals who used AI produced better results than both lone workers and teams who had no access to the technology. They weren’t just more effective. They were also more efficient, finishing the task 8–10 minutes faster on average than those working without AI. Generative AI allowed them to quickly access a wider range of expertise (which they would traditionally seek from human colleagues), interrogate that information, and refine their work. In fact, it did this so effectively that – for some collaborative tasks – it could act as a substitute for their human teammates. This was underlined by the fact that teams which used AI performed only marginally better on average than individuals who did so. However, further analysis did highlight an additional benefit to using AI as part of a team. Many organisations place particular emphasis on what we call ‘exceptional’ outcomes. These are ideas which could generate disproportionately large returns if they were implemented. Therefore, we ranked the quality of the ideas the workers produced. This revealed that teams using AI were three times more likely to produce solutions that were ranked in the top 10 per cent.
This suggests that businesses seeking ‘breakthrough’ ideas would be well-advised to train their workforce to use AI effectively as part of their teamwork, not just as individuals. 2 . AI can break down silos. In many organisations, expertise is confined to silos. This restricts the flow of information between teams and leads to duplicated work, slower decisions, and lower efficiency. Our findings demonstrate that LLMs can remove these barriers by democratising expertise. “As the old adage goes, ʻThere is no ʻIʼ in team.ʼ But what about AI?” When workers had no access to AI, their ideas tended to reflect their background. R&D professionals suggested more technical solutions; commercial staff focused on their own field of expertise. Those with little experience of product development performed poorly. When it came to teams, we found their proposals tended to reflect the professional expertise of the more influential team member. However, when they had access to AI, both individuals and teams produced more balanced proposals that covered technical and commercial considerations. This suggests that AI can help professionals to operate across traditional boundaries and adopt a more holistic approach to solving problems.
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While AI cannot fully replicate the rich nature of human interaction, our findings suggest that LLMs could fulfil part of the social role traditionally performed by human teammates. In other words, it might help to motivate staff, as well as making them more effective and efficient. None of this removes the need for business leaders to take care when integrating technologies such as AI. My previous research shows that it is incredibly difficult to identify the limits of generative AI, and therefore to know when to use it, not least because that ‘jagged frontier’ is constantly moving. However, this study challenges the prevailing view that even when AI outperforms humans on a particular task, overall team performance will decline as trust and coordination are eroded. Our results show that generative AI is not simply another automated tool, like a calculator or a spreadsheet. It provides real-time feedback, enhances performance, breaks down silos of professional expertise, and influences how users feel. This dynamic interaction means that generative AI acts less like a search engine or text generator and more like a ‘cybernetic teammate’. It can occupy roles we normally associate with human colleagues. And that could force organisations to rethink both their team structures and their entire approach to collaborative work.
3 . Human input remains key. Many of the workers in our experiment included large quantities of AI-generated content (often in excess of 75 per cent) in their final proposals. This does not necessarily mean that they adopted its suggestions without critically evaluating it. They may have conducted several iterations of prompts – validating the responses using their own expertise and external sources – before incorporating the results into their proposals. There were also workers who did not incorporate any of AI-generated content into their submissions. Instead, they used AI to brainstorm and to refine and validate their own ideas. Those who relied more heavily on AI produced more similar solutions than those who did not. However, these proposals were still more varied than the results we produced when we asked ChatGPT-4 to solve the same
problem iteratively without any human input. This shows that human input remains vital to the process, as humans meaningfully shape and contextualise the suggestions they receive, rather than adopting them wholesale. 4 . Gen AI fulfils social needs. A common concern about new technology is its potential to destabilise workplace routines and reduce human interaction, making work less satisfying. But on the contrary, we found that professionals who used generative AI reported significantly higher levels of positive emotions such as excitement, energy, and enthusiasm. At the same time, they experienced lower levels of anxiety and frustration. These benefits were even more pronounced for professionals working in teams than they were for those who used generative AI individually.
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Future of Work
DEFINING YOUR VALUE
Avoid making yourself replaceable . by Giovanni Radaelli SELF LESS?
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consequences for the organisation, as clinicians became overburdened with new responsibilities and services suffered as a result. However, our research also identified five steps that professionals can take to cement their position as a vital part of the organisation’s structure. 1 . Be aware of the risks. Our study found those managers who tried too hard to impress and help clinicians temporarily succeeded in triggering change. But after a while they were treated as subservient and replaceable. Recognising that elements of their job could be consumed by ‘internal clients’ meant professionals were able to adapt accordingly. For instance, we found that quality managers would avoid sitting on the same table as executives and clinicians simultaneously, as sharing information with both parties could weaken their own position. 2 . Develop a strategy. We identified two strategies for organisational professionals to avoid blithely handing over knowledge to colleagues until they become replaceable. The first was a ‘selfless strategy’, where quality managers built their knowledge through conversations with executives and clinicians, combined that with their own operational expertise, and shared the resulting insights with others. These ‘selfless’ professionals deliberately co-produced integrated care initiatives with clinicians and executives to impress them and trained them to take over some responsibilities. But, in return, they expected to be rewarded with opportunities in different parts of the organisation. In some cases, they outlined this
in email templates that served as pseudo-contracts. These clarified what clinicians could expect in terms of contribution, time, and outcomes. One template read: “If you don’t agree, we don’t start.” The alternative is what we called the ‘selfish strategy’. Here, quality managers acted more as internal consultants, helping to deliver an innovative service without handing over valuable knowledge to executives and clinicians. These ‘selfish’ managers avoided co-producing initiatives, worked in the privacy of their offices, and only showed the results of the labour so nobody could imitate their ‘craft’. In this model, they remained in charge, rather than delegating responsibility to clinicians. They also protected themselves against being marginalised by approaching executives to develop new opportunities, rather than waiting for clinicians to vouch for them. 3 . Carve out a unique position, Organisational professionals need to increase their interactions with others, else there is a risk of becoming invisible in the organisation or being reduced to clerical workers. In our study, we noted how several quality managers unintentionally isolated themselves from decision makers by locking themselves in their office to perform their demanding tasks. As a result, they were easy to overlook. The more successful quality managers exploited their unique middle management position to interact with executives and clinicians on a daily basis. The ‘selfless’ managers used this to act as bridges between executives and clinicians who interacted far less frequently, and expected to be rewarded for bringing them closer together.
TO THE CORE
1. Professionals can make themselves easy to replace if they are too willing to share their expertise with colleagues in different departments. 2. One way to avoid this is a ‘selfless strategy’, which involves learning from others, combining that knowledge with their own expertise, and sharing the resulting insights with others. 3. A ‘selfish strategy’ is to become a buffer between executives and other teams, then present themselves as the solution. 4. Both approaches require them to develop a unique understanding of how the organisation works and why, then apply that in their role.
P rofessionals in they deserve. This is particularly true for those who are involved in developing new initiatives, only to be sidelined after sharing their expertise. Together with Graeme Currie, from WBS, and Saku Mantere, at McGill University, I explored the role of quality managers in 12 Italian hospitals as they supported the implementation of integrated care pathways. We found those who were too willing to share their knowledge functions such as HR, finance, and quality management play a vital role in the success of any organisation. Yet they do not always receive the recognition risked being replaced once they had taught clinicians how to perform key tasks themselves. This also had negative
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Future of Work
“AI has the potential to take over a range of activities that are currently performed by organisational professionals” The ‘selfish’ managers used their position to act as a buffer between executives and clinicians, presenting themselves as the solution to each other’s problems. They then expected to be rewarded for their ability to integrate the two. 4 . Gain organisational knowledge . To survive, professional workers must possess a unique knowledge base that others cannot replace. Cardiologists, for instance, could not be replaced by other professionals as they have a monopoly on the expert knowledge required to diagnose and treat heart failures. We noted that quality managers could not simply use their professional expertise as leverage. They had to blend that expertise with the contextual knowledge of the organisation that they acquired through their interactions with executives and clinicians. This helped them to develop innovative solutions and speak the language of different stakeholders. In our study, quality managers invested time completing extra work for executives and clinicians, even if that meant low-level activities such as organising meetings or taking notes. This exposed them to the inner
workings of the organisation and, if replicated across different departments, could help them develop a unique understanding of how things work and why. 5 . Maintain a distinctive identity. In hospitals, a lack of clinical knowledge has traditionally been seen as a drawback for organisational professionals. Operations and quality managers could be perceived as intruders whose influence is incompatible with clinical norms. We found that quality managers often tried to assimilate the identity, language, and values of clinicians in order to appear safer and more friendly. However, this was not an effective strategy. On the contrary, quality managers that promoted their identity as operations specialists were more effective in conversations with clinicians. They appeared more assertive in promoting their unique value in projects of integrated care, while not posing any competitive challenge to clinicians. Our study highlights that successful organisational professionals did not compete with executives and clinicians, and nor
did they try to completely align with them. Instead, they created a unique position and knowledge base which others found appealing and were unable to replicate. This could also help to protect organisational professionals from AI encroaching upon their roles. On the face of it, AI has the potential to take over a range of activities that are currently performed by organisational professionals, which could lead to some roles being made redundant. But those who develop more organisational knowledge and forge connections that help the organisation to function are less likely to be replaced by technology. AI could even help them by taking over some of their more mundane tasks, creating time to focus on more relational activities. They should embrace AI rather than fearing it. It might help them to keep their job and enhance their stature.
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MEANINGFUL LABOUR Work of art Finding beauty and meaning in unskilled work by Marjolaine Rostain
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Future of Work
T he UK is not short of menial jobs. Government statistics show that, by 2027, more than 10 per cent of the workforce are likely to have low-level qualifications or no formal qualifications at all. And as automation and artificial intelligence reshape the job market, many more roles could be reclassified as ‘low-skilled’. When you think of these jobs, what comes to mind? Many of us imagine monotonous days with little freedom or recognition for workers. This view may be unnecessarily gloomy. I spent eight months at an unremarkable French factory that makes moulds for the automotive industry and other products. During that time, I watched the machine operators and fitters on the factory floor as they went about their repetitive and low-paid jobs. These factory workers had strict working hours, set break times, and largely worked alone. Their actions were closely monitored as they had to swipe a card each time they began a new task. Like many workers in menial roles, they liked to moan about management. Some did the bare minimum to get by, taking additional breaks when the opportunity arose and leaving the machines to run unsupervised. Yet there were instances when they appeared to enjoy their roles and find meaning in their work. It has previously been suggested that employees in such positions often cope by embracing small acts of resistance, or by reframing their work as a contribution to society. For example, a rubbish collector may consider themselves as an environmental services provider, emphasising their contribution to cleaner neighbourhoods, public health, and the natural world.
However, I witnessed a different approach: workers managing to find meaning in low-skilled, controlled environments not by resisting or merely coping, but by engaging more deeply with their work through ‘aesthetic improvement’. They did so by embracing the beauty of the task itself, rather than focusing on its repetitive or controlled nature. These instances tended to occur when workers took on additional tasks outside of their routine work. This was not easy to do as their working day allowed for little wriggle room. However, they seized opportunities when production was disrupted, worked through breaks, and even arrived early or stayed late. There was no financial reward. Nor were they hoping to improve their prospects of promotion. So why did they do it? To engage in what Richard Sennett defined as craft or the sake of “doing a job well for its own sake”. This allowed them to gain autonomy and recognition at work, two important pillars of meaningful work. For example, when a machine operator worked through her lunch break to create a new tool that reduced an unsightly mark on a mould, she took pride in presenting it to her grateful colleague. Suddenly, she was no longer just an executor of repetitive tasks; she had become a designer, contributing to the conception phase of the work. She later told me: “I love doing challenging things at work where I have to figure things out.” Similarly, when a fitter spent extra time – outside his paid hours – repolishing a mould that had already passed quality control, simply because “it did not look good” to him, he became the one setting the standards. He decided how the work should be done and when it was truly finished.
In doing so, he gained a sense of autonomy and the prospect that his manager might acknowledge that a new polish was indeed needed. If this is possible in a small factory, what does this mean for low-skilled workers in call centres, care homes, or warehouses? Or the ‘click’ workers, who train AI models by clicking a mouse and whose routine work typically lacks recognition and autonomy? Should we reintroduce the notion of aesthetic judgement in low-skilled, controlled work? Should we allow workers to define when a task is done ‘well’ rather than adhering to rigid, repetitive standards? Software developers could refine their code until they deem it ‘nice’ rather than merely functional. Call centre operatives could improve their interactions with clients until they judge them ‘good enough’, instead of rigidly following a script that deprives them of all sense of autonomy. Could moving from measurable objectives to goals based on judgement and appreciation help staff to find meaning in their work? This would require more time and may also require space for collaboration – things that managers may be reluctant to provide. In an age of automation, where time is critical and rational choice dominates, is it time to redefine how work is done? If we prioritise the aesthetic in order to give employees a sense of meaning, perhaps we would achieve better organisational outcomes in the process.
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Sustainable Development Goals
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REMOTE WORK
FREE STYLE . Why autonomous work is the future by Lizzie Penny
O ver the past couple of years, I’ve watched a familiar pattern emerge. Businesses that once championed progressive working have begun quietly reinstating office mandates. Some are doing it openly, others through subtle pressure: ‘anchor days’, compulsory in-person meetings, career-limiting signals for those who aren’t present in person often enough. The rationale is always similar.
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Future of Work
Leaders tell me collaboration is suffering, culture is fraying, productivity is harder to see. I understand the anxiety. But I believe this fundamentally misdiagnoses the problem. The issue is not where people work. It’s how work itself is designed, measured, and led. Forcing people back into offices is not a return to stability; it is a retreat to familiarity. And familiarity is not the same as effectiveness. For more than a decade, my business partner, Alex Hirst, and I have been exploring a different approach, one we named ‘workstyle’: the freedom for individuals to personalise their work around their unique needs. We didn’t arrive at this idea theoretically. We arrived there through burnout, parenthood, two cancer diagnoses, caring responsibilities, and running a business by engaging people in a completely new way. We have supported thousands of individuals to define and
respect their own workstyles, and gathered longitudinal research into the impact of autonomy on wellbeing and productivity. As a result, we were named as one of HR Magazine’s five most influential HR Thinkers 2025 and among the most progressive organisations in the world by Thinkers50 and the Haier Model Institute. Yet we remain frustrated because so many organisations are moving in the wrong direction. What we have learned is simple, but uncomfortable for many leaders: autonomy, not attendance, is the lever that drives sustainable performance and competitive advantage in the digital age. Hybrid working is often presented as a sensible compromise between the old world of offices and the new reality of remote work. In practice, it usually adheres to the assumption that work happens at set times, in synchronous ways. The only change is that sometimes this happens at home
rather than in an office. Hybrid working, flexible working, and the 4-day-workweek do not challenge the deeper question: why do we still measure work through time and location? Workstyle is different. It offers a practical framework to shift the focus from hours to outcomes, from control to clarity, and from compliance to trust. This improves results by strengthening wellbeing, removing the structural barriers that disadvantage many groups, and allowing everyone to be at their personal productive best. The evidence for autonomous working is robust. Randstad’s 2025 global survey identified work-life balance as the top criteria for attracting talent; Gallup found employees with greater schedule control are 2.7 times more likely to be highly engaged; and Stanford University found that self-chosen work arrangements can increase productivity by up to 22 per cent. Moving to autonomous working
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does not mean lowering standards. It sharpens accountability. The first shift is letting go of presenteeism. Many of us were taught, implicitly or explicitly, that good work involves being busy and visible. When time and presence are removed as proxies for effort, leaders must become much more precise about what outcomes matter, what quality looks like, and how success is measured. The second shift is from control to clarity. Autonomy without clarity creates anxiety, not freedom. The most effective autonomous organisations invest heavily in intentional work design and the culture that is needed to support it. This includes a shared understanding of responsibilities, decision rights, roles, and boundaries. Employees are upskilled in the behaviours to underpin this way of working. Drawing on our Digital-Age Performance Model, the following five steps help organisations transition from traditional oversight to a system rooted in trust and high performance. 1 . Design freedom within a framework. Autonomy works best with well-defined parameters. Set out the essential boundaries – purpose, priorities, outputs, and decision rights – so everyone knows what matters. Then give people real freedom to decide how they deliver within that structure. This balance of clarity and choice enables consistent performance without unnecessary constraint or wasted energy. 2 . Accountability and autonomy go hand in hand. Autonomy does not remove interdependence. High-performing
workstyle teams rely on transparent commitments, clear communication and strong, proactive cooperation. Encourage individuals and teams to articulate not just how they work best, but how they will remain dependable to others. This clarity transforms autonomy from a solo endeavour into a collective capability. 3 . Invest in the skills for autonomous working. Autonomy works when individuals have the right skills and self- awareness. Support people to develop the core capabilities for personal productivity: self-understanding, self- motivation, self-management, and self-improvement. These are not ‘nice-to-have’ traits; they are the building blocks that allow people to work Leaders must shift from supervising activity to enabling performance. Digital-age leadership is defined by context-setting, trust-building, and role-modelling the behaviours that support autonomy. When leaders demonstrate confidence in their teams, set expectations around outcomes, and create psychological safety, they unlock independence and alignment. 5 . Reinforce performance, not presence. Workstyle thrives when the environment supports it. Ensure your organisation has an authentic purpose that is lived and visible. in a workstyle way without losing focus or momentum. 4 . Redefine leadership.
asynchronous practices, and provide ‘work-anywhere’ technology. Resistance to autonomous working is rarely about employees. It is about leadership anxiety: fear Our experience shows that these risks are highest when autonomy is half-hearted. Partial flexibility creates ambiguity and mistrust. Full autonomy, designed intentionally, replaces informal assumptions with explicit of losing control, lowering productivity, and culture dissolving without proximity. agreements. Culture becomes something you articulate and live, not something you hope emerges from a shared space. Another of the biggest fears I hear is that autonomy will advantage some more than others. In reality, opaque norms already do that. When progression, reward and recognition are tied to outputs rather than conformity, fairness improves, not deteriorates. The debate about returning to the office is a distraction. The choice facing leaders is whether they will continue to retrofit flexibility onto an Industrial-Age model of work, or redesign work for the reality we now live in. Workstyle is not about where people sit. It is about whether we trust adults to do meaningful work in ways that allow them to thrive. The future of work is already here. The real test for a leader is whether they are brave enough to embrace it, and design work intentionally for their organisation.
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Future of Work
THE FUTURE OF CAREERS
Over the hill Are many careers peaking earlier than expected? by Redzo Mujcic
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be promoted (or, at the very least, to remain at the same level) and enjoy more independence in their roles. Yet my research with Professor Andrew Oswald, from the University of Warwick, suggests this is not the case. Using four sets of longitudinal survey data from three wealthy countries – the United Kingdom, Australia, and Germany – we analysed the responses of more than 400,000 workers. This allowed us to identify which workers felt they were allowed to work independently and track how these feelings of ‘autonomy’ changed over time through their working lives. Our results were surprising. We found that the level of autonomy reported by workers rose during the early part of their career, but peaked around the age of 40. It then declined sharply over the next 20–30 years of their working life. By the time they reach their early 60s, many reported little or no autonomy – and, in some cases, less than workers at the beginning of their careers. This ‘hill-shaped’ career curve was almost identical across all three rich countries. It also remained broadly the same regardless of gender, education, whether workers were full-time or part-time, length of service, and whether or not they had supervisory roles. This peak in workplace autonomy at around 40 years old seems perplexingly premature, which poses the question: are people’s perceptions accurate? Prior research has shown that older workers prefer jobs with greater autonomy, which allow them to use the judgement they have developed through years of experience. Does that mean they set the bar
higher when considering how much autonomy they have? And that, as a result, the decline in autonomy is a largely imaginary trend? Our findings suggest not. We analysed workers’ job titles and supervisory responsibilities, their salaries, and the flexibility they had on when to start, finish, and take breaks. These are more objective measures of an individual’s “For many years, we have believed that seniority in terms of age and position go hand in hand” autonomy and all revealed a similar hill-shaped pattern. In Australia, Germany, and the United Kingdom, the number of people with ‘manager’ in their job title peaked before the age of 40. Some who moved out of this category were promoted to more senior positions, such as director. However, these promotions were too few and far between to have a significant impact. Employees were far more likely to move downwards, rather than up, when the word ‘manager’ was removed from their job title. Nearly 40 per cent moved into the ‘professional’ category, more than a fifth became clerical and admin workers, and 14 per cent became technicians or skilled tradespeople. Another 10 per cent ended up in blue collar roles, such as labourers, machinery operators, and drivers. We also conducted a survey of approximately 400
TO THE CORE.
1. Older workers prefer jobs with greater autonomy that allow them to use their judgement developed through years of experience. 2. In reality, autonomy for most workers peaks around the age of 40, regardless of gender, education, and length of service. The exception are those managers who achieve repeated promotions through their career. 3. This ‘hill-shaped’ curve dramatically changes our understanding of the typical career trajectory. 4. Business leaders should be mindful that this could lead to experienced workers being less motivated and less loyal, especially as remote working and the retirement age increase. W hen Katalin Karikó won one aspect of her career dominated the headlines. While conducting her award- winning research into mRNA ‘messenger molecules’ – which enabled scientists to rapidly develop effective vaccines against Covid-19 – she was demoted not once but four times. She also had her salary cut, putting her at risk of being deported from the US. the Nobel Prize in Medicine in 2023, One reason this attracted so much attention is that it contradicted the generally accepted narrative that career progression follows a linear trajectory. For many years, we have believed that seniority in terms of age and position go hand in hand. In other words, as individuals gain more experience, they are more likely to
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Future of Work
experienced professionals, most of whom were MBA and Executive Education students at Warwick Business School. More than 60 per cent said they knew someone who had been demoted from a supervisory role in an organisation they had worked for, and nearly half said they knew someone who had lost their managerial title. Thirteen said they could name multiple people this had happened to. Again, these demotions happened most frequently between the ages of 40–49. It appears that demoting or sidelining previously valued employees is a common practice. So why does autonomy peak so early for many employees? In truth, we do not know. No-one appears to have identified this trend previously and there is a strong case for further research to understand what causes the phenomenon. It cannot be adequately explained by workers changing employers and accepting a lower-level role in their new organisation. A relatively small proportion of those who reported having less autonomy had also moved jobs. Neither is it because workers with more autonomy are leaving the workforce in larger numbers. One thing we can say is that those who enjoy managerial status throughout their careers, and who are promoted again and again, are less likely to experience a loss of autonomy. Managers in the charity sector are also more likely to retain higher levels of independence. This may point to a stronger, age-based hierarchy in the sector. Why does this pattern of dwindling autonomy matter? Put simply, humans hate being monitored. The anthropologist Donald E. Brown listed
autonomy as one of the most basic human needs in his influential book, Human Universals . In the workplace, autonomy is widely regarded as a key source of motivation and job satisfaction. This is particularly significant when you consider two other trends. The first is the rise of hybrid and remote working. If this continues to spread, self-motivation is likely to become an increasingly important quality for workers. Employers should be mindful that lower levels of autonomy could result in experienced workers becoming less driven and less productive. countries are retiring later. This means they could spend a larger proportion of their careers working without the autonomy they crave. This could result in older employees who feel less loyalty to the organisation and are more inclined to take their skills and experience elsewhere. By the time the wider scientific The second is the fact that employees in many wealthy
community began to fully appreciate the potential of Karikó’s research, she had long since departed the university that demoted her. She took her expertise to BioNTech Pharmaceuticals in Germany, where she eventually became Senior Vice President. The company later worked with Pfizer to develop the first mRNA-based vaccine to combat the Covid-19 pandemic. Few employees who are demoted or sidelined will go on to enjoy the success achieved by Karikó. But her story should serve as a warning to employers of the expertise they could lose if they sideline workers relatively early in their careers, when they have so much more that they could offer.
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MEET THE CHANGE MAKER IN IT FOR THE LONG RUN How Bhavesh Vaghela is harnessing AI T here are many things that might go awry on the day of the TCS London Marathon – the world’s biggest mass participation event – but Bhavesh Vaghela and his team will be ready. As chief product technology and
uses maths to model it. There can be no delays. “Even moon missions can be postponed if something’s wrong. But the Sunday marathon will happen regardless – you have 60,000 people rocking up,” he says. Amid the excitement and chaos, Bhavesh tries to exude calm. “The worst thing you can do is panic. In the weeks before, when mission-critical items must be in place, the energy of the team goes through the roof.” For one day, London stops for a magical celebration of humanity. People congratulate each other, restaurants offer finishers free food, and train and tube passengers talk to one another. Last year, participants raised a world record-breaking £87 million for charity. “It’s a really beautiful time, a party atmosphere. I joined LME because it has such a high purpose – charities tell us how much the donations mean to them – this can be very emotional.” Friends often assume he takes a breather after the big day, but his attention turns to the Bath Half and Brighton marathons, swims, cycle races and many other running
AI officer at London Marathon Events (LME), he’s poised for the problems no-one saw coming. That includes rats munching through internet cable, as they did at the marathon’s sister event, the Vitality London 10km, in September last year. “It’s such a complex event to organise – things will go wrong,” he says. “What’s key is to be prepared for every eventuality. The team mantra is – whatever happens, we will get through it.” Bhavesh never imagined this success growing up in Salford. After his father died in his early 40s, his mother was forced to sell their car and possessions to feed her young family. But, at school, he discovered an affinity with technology, which led him to a degree in computer science and an Executive MBA at Warwick Business School. He began work as an engineer
in technology and defence, moving to digital innovation within retail banking, before entering the start-up world. At LME, his job spec includes crowd control, communications, and creating a hybrid world of interactive maps and apps to connect runners and spectators. “You have no idea how much maths is involved in a marathon,” he says. Each wave of runners departs to a strict timetable, which keeps the data team busy. “We have someone who works full time on crowd dynamics, looking at road widths, calculating pinch points, ensuring everyone is separated in a logical way for the start times to avoid build-ups,” he says. From queues at loo stops to well-placed water stations, the team
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Future of Work
code to use AI,” he says. “You must be AI literate,” he adds. “You can read blogs all day long, but you need to use it. Learn the basics, understand how it works, what your real use case is, and what outcome you’re after. And if at any point it’s not delivering, just kill it and look again.” His mechanic father taught him to take things apart – mostly cars – and put them together again. “This way you get an overview of how to fix things and make them better.” Bhavesh may be a family man with little spare time, but the marathon has inspired him to take up jogging. He is also leading AI-driven start-ups in collaboration with WBS. During his executive MBA, he taught himself to speed read and learned the wider language of business. “It opens your mind to thinking critically and trains your brain. I’ve learned to communicate complex ideas in simple language and with metaphors.” Currently part of the Warwick Enterprise Programme, he’s building a business, Ethita.com, using an AI-driven matching platform. One product – Volunteer Connect – aims to link professionals
to a range of charities that need their specific skills, such as project management and data analysis. Charities pay nothing, while companies, who do pay, fulfil a volunteering requirement and keep staff engaged. “Employees will be more inspired to volunteer if they know they’re not going to pick up litter or paint a wall,” he says. Another product will link mentors with mentees who are seeking specific advice. The AI will match feedback styles, skills, and the specific needs of individuals wherever they are in their business development. He also runs a popular food blog, hungryhindu.com, with more than 60,000 monthly users. “Both my kids can cook; it’s a shared thing. I find making food meditative.” While his new companies won’t make him a millionaire, they provide help that would otherwise be hard to find. “I genuinely believe in making a difference and having an impact upon society,” he says. “I don’t want to be the richest guy in the graveyard.”
events. LME also organises a range of events for children and young people, including the TCS Mini London Marathon. Bhavesh is proud of the range of technology that connects spectators with runners. Last year saw the rollout of an AI agent informed by years of detailed knowledge and experience. Nearly nine in ten queries were resolved on first contact, providing a tangible benefit. This year, Bhavesh took it upon himself to create an audio guide scripted and voiced by AI, delivering huge cost savings. “Every weekend, I played around with different technologies and tools to see what worked. You can use AI in very smart ways. But you have to ask smart questions.” Despite being a computer scientist, he would never describe himself as an AI expert. “But you don’t need to
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