by Reza Salehnejad, Senior Lecturer (Associate Prof) on Alliance Manchester Business School’s MBA programme
Businesses are investing heavily in AI, recognising its potential to improve productivity, streamline work and reduce costs. But as business leaders push ahead with AI adoption, many are facing a significant challenge: bringing employees along on the transformation journey.
The technology itself is only part of the picture. If employees are reluctant to adopt AI or lack the skills and confidence to use it effectively, businesses risk failing to realise the benefits of their investment. As I explore when teaching the Digital Economy: AI, Platforms and Business MBA course at Alliance Manchester Business School (AMBS), leaders must recognise the organisational changes needed to successfully embed emerging technologies.
This includes learning how to integrate AI into organisational processes and mastering its application; developing training programmes that help employees reskill and use the technology to gain a competitive advantage; articulating a bright future for the firm that benefits all stakeholders, including employees; addressing employee concerns; building trust; and ensuring teams feel equipped and empowered to embrace new ways of working.
Understanding where AI resistance comes from
Understanding the reason behind employees’ reluctance to embrace AI is vital, particularly as their concerns do not necessarily mean they are opposed to the technology itself.
According to Boston Consulting Group (BCG), employees at organisations undergoing comprehensive AI-driven redesign are more worried about job security (46%) than those at less-advanced companies (34%). Likewise, Deloitte UK’s GenAI Workforce Study found that two thirds (64%) of weekly users are worried managers will think that GenAI could do their jobs
For this reason, leaders must develop a deep understanding of AI and past technological disruptions to articulate a vision of the future that challenges unfounded fears about automation and job displacement.
Most jobs are messy, comprising bundles of interrelated tasks. Even if AI automates some of these tasks, the jobs themselves survive. Communicating a more realistic vision of the future, characterising AI as an augmentation technology and emphasising human–machine collaboration, will be among the key leadership tasks throughout the transition brought about by AI.
Deloitte’s research also found that nearly a quarter (23%) of those using generative AI (GenAI) think there is a stigma attached to using the technology at work, while collectively spending almost £1 billion a year of their own money on GenAI tools for work. This suggests that concerns about how the use of AI may be perceived do not necessarily equate to a reluctance to use it.
This presents a different challenge for employers: shadow AI, where employees use AI without their organisation’s knowledge or approval which can create risks around data security and privacy.
Leaders must therefore cultivate a proactive organisational culture which views AI as a competency-enhancing technology that enables employees to improve productivity, perform previously infeasible tasks, reduce errors and learn new skills.
This must be complemented by recognising and rewarding good practices in AI use and establishing clear guidelines, creating an environment where employees feel comfortable discussing their use of the technology and openly raising concerns.
The importance adequate training
Another barrier to successful AI adoption could be a lack of relevant skills, knowledge or confidence in using the technology effectively. The EY 2025 Work Reimagined Survey found that just 11% of employees reported receiving adequate AI training.
Training must go beyond individual AI tools: it must help employees understand how they can use it in their role, which processes it can improve and how to use it securely. Teams must have the opportunity to practice these new skills to help build their confidence and see how AI could benefit them in their roles.
Deloitte also found that training would encourage 51% of the UK workforce to use GenAI more often, suggesting that upskilling employees in AI can give them the confidence needed to use the technology in their work.
There is also an appetite for leaders to receive specific training; the AMBS survey of business leaders found that 40% of respondents would like formal training to help them understand AI and how best to leverage it.
How managers can effectively lead the transformation
Managers have a crucial role to play in translating an organisation’s AI strategy into everyday working practices; an understanding of the technology alone is not sufficient. As with past general-purpose technologies, a fundamental challenge for firms is learning how to integrate AI into organisational processes. Successful adoption requires restructuring organisational processes and investing in complementary skills and assets.
This adds to the demands already placed on managers; almost three-quarters (73%) of decision makers says their role as a manager has become more complex over the last 3-5 years, with 30% attributing the increased complexity to the emergence of new technology, according to AMBS’ survey.
Without a clear vision of what AI-native or AI-centred firms look like and how they differ from legacy firms, leaders will find it difficult to chart a smooth transition towards an organisation that can benefit effectively from AI.
Indeed, McKinsey’s 2025 Global Survey found that redesigning workflows was the factor most associated with achieving financial benefits from GenAI. Similarly, CIPD research shows that more than 80% of companies that had strategically embedded AI in their organisations had redesigned jobs and undertaken reskilling activity.
Managers would therefore benefit enormously from reskilling and developing a richer understanding of strategic and organisational transformation in the face of disruptive technologies.
Successful transformation requires actively involving employees in the process and learning from their experiences of what works and what does not, carefully designed experimentation and learning through trial and error.
As AI continues to evolve, managers must approach its adoption as an ongoing process of learning, adaptation and refinement. Regular feedback provides an opportunity to understand where AI is improving employees’ work, identify challenges and adapt processes to ensure the technology continues to deliver value. This all requires proactively bringing employees on board.
An organisation’s AI transformation should not be judged on the investment a business makes in the technology, but by the improvement it makes to productivity, profitability and wider business performance. Achieving these outcomes requires more than simply encouraging employees to use AI. Leaders must have a clear vision for how the technology will change their organisation and the role that employees will play in determining whether the transition is a successful one. Those that combine strategic direction with a willingness to experiment, learn and adapt are best place to deliver meaningful improvements to how their organisation operates.