AI has dominated headlines, boardroom agendas, and transformation roadmaps for two years. However, the noise is starting to wane and reality is setting in as the results that many organisations hoped for have been underwhelming. Amid widespread layoffs and economic caution, business leaders are beginning to ask a more grounded question: how can AI support long-term strategic growth?
The answer lies not in the technology alone, but in how organisations go from proof of concept to production. AI is not a silver bullet and replacing people as your end goal is misguided. AI does not replace jobs; it undertakes certain types of work and tasks, under the stewardship of people. These are two very different things.
Ultimately, AI’s value depends on the humans it supports, as some high-profile companies have discovered to their disappointment.
The missing link in AI adoption
The biggest gap in AI adoption is the lack of a clear understanding of the work and how AI will affect that work, within the structures of the workforce. Put simply, what problem is it they want AI to solve? If organisations don’t first understand the work they’re trying to automate, any transformation effort will underperform. We all recognise AI’s enormous potential to improve business productivity, but only when it’s properly integrated and is used to add true to people’s workflows.
Too often, organisations rush to deploy AI solutions without first answering basic questions, such as: What skills do we have and what are we missing? Where are our people under or overutilised? Where can AI be deployed easily and what tasks can it quickly start automating? It doesn’t have to be complicated, but leaders often expect it to solve the most complex business challenges, instead of using it to automate simpler tasks and deriving value from it in the more obvious ways.
This is leading to mistakes that companies live to regret. In fact, our research found that of the 39% of business leaders who have made employees redundant as a result of AI, 55% say they made wrong decisions about those redundancies.
It’s time to face the fact that AI is not a panacea for all business ills. It won’t magically transform your workforce and make your business better by simply throwing money at it. AI implementation is no different to technology deployment in the 90s or early 2000s – if you don’t understand the work and how it relates to your value chain and people, then it will fail. Like everything else, successful deployment requires hard work and careful planning. Why would we think it would be otherwise?
What went wrong?
The recent wave of tech sector layoffs offers a cautionary lesson in transformation gone wrong. The initial AI boom saw many companies overinvest in headcount to meet projected demand but when growth slowed, it became clear that hiring sprees were not grounded in sustainable models of workforce demand.
What followed was sweeping job cuts, some in roles that had taken years to cultivate. These reactive decisions not only harmed employee morale and brand reputation but also left gaps just as businesses were trying to scale new AI capabilities.
Had workforce planning been prioritised from the outset, many of these decisions could have been made with more foresight. With scenario modelling, businesses could have predicted different outcomes and prepared more agile workforce responses.
Reframing AI as a strategic tool, not a solution
There’s the persistent danger that businesses see AI as the ultimate solution to all organisational challenges, especially when investors and media are pushing for quick wins.
But leaders need to take a more pragmatic approach: AI is a tool; a powerful one, yes, but still just a tool. It must be used with purpose, grounded in evidence, and aligned with strategic business goals. That means placing it within a structured ecosystem that balances technology, data, and most importantly, people.
Organisations that excel in workforce transformation are those that continuously review and adjust their business strategy based on data and insights. By doing so, they can anticipate challenges, mitigate risks and unlock new opportunities for growth and innovation. This applies equally to AI.
Human-first transformation
Sustainable transformation doesn’t start with algorithms; it starts with culture, capability, and communication. It goes without saying that when people understand the purpose behind AI deployment, and when they’re involved in shaping its implementation, they’re more likely to embrace it.
This is where workforce planning for AI becomes a human story, when organisations begin to map where their people are today, what skills they have, and where they could go. It enables conversations about reskilling and mobility, rather than redundancy and replacement. Also, it aligns AI investments with long-term value creation, rather than short-term business efficiency.
The organisations that thrive in the AI era will be those that blend technological ambition with human insight. They’ll treat AI as an enabler of better work, not a substitute for workers. They’ll understand that transformation is not something done to people, but with them.
Creating a smarter path forward
As we move into the next phase of AI adoption, the question for leaders is not “what can AI do for us?” but “how can AI support our plans for a better, more human-centred business?”. That shift in mindset is critical for long-term success.
Workforce planning may not be the most glamorous part of AI-driven transformation, but it’s essential for successful technology adoption. It helps bridge the gap between strategy and execution, between ambition and reality. It ensures that as we invest in the future, we do so with clarity, control, and compassion.
Workforce transformation for AI needs a clear view of organisational skills and a strategy that puts people first. Once businesses acknowledge this home truth, they’ll have a much better chance of delivering the value that AI promises.
