Organisations worldwide stand at a decisive moment. Nearly 90% of companies report investing in artificial intelligence, yet fewer than 40% are seeing measurable results. This disconnect highlights a common misconception: many companies focus on using AI to automate individual tasks, rather than rethinking how work is fundamentally organised.
According to McKinsey Global Institute, the most significant value comes from redesigning workflows to enable collaboration between humans and machines. Only by integrating AI into comprehensive, reimagined processes can organisations fully capture the technology’s potential.
Unlocking Trillion-Dollar Value
Analysis from the McKinsey Global Institute suggests organisations could unlock approximately $2.9 trillion (£2.3 trillion) in annual economic value in the United States alone by 2030, but only if they fundamentally redesign how work gets done. This suggests companies may want to fully reconsider how work gets done, rather than simply adding AI tools to existing processes.
“Work in the future will be a partnership between people, agents, and robots—all powered by AI, today’s technologies could theoretically automate more than half of current US work hours. This reflects how profoundly work may change, but it is not a forecast of job losses.”
McKinsey Global Institute Report, Agents, Robots, and Us: Skill Partnerships in the Age of AI
Rethinking Workflows
The leap from task automation to workflow redesign is the leap from incremental improvement to genuine transformation. A bank, for instance, may introduce a chatbot to answer quick internal queries—useful, but limited. Redesigning the entire loan approval process, where humans and AI systems jointly manage assessment, processing, and customer communication, delivers far greater gains in speed, accuracy, and customer experience.
McKinsey’s analysis of 190 processes across the US economy reveals that approximately 60% of the potential value sits within industry-specific workflows—manufacturing supply chains, clinical diagnostics in healthcare, regulatory compliance in finance, and other essential, high-impact activities.
The rest lies in cross-functional areas such as IT, finance, HR, and customer service, where organisations can build repeatable, scalable solutions that work across sectors.
Leadership, Culture, and Long-Term Thinking
The rise of AI is also reshaping what it means to be a manager. As intelligent systems take on more analytical and routine tasks, managers are shifting from overseeing day-to-day activity to orchestrating teams where people and AI work together. This influences the duties of their role, instead of monitoring progress, they focus more on guiding their teams, building capability, and strengthening relationships.
With AI handling data-heavy work, managers can spend more time on high-value leadership activities such as coaching individuals, understanding customer needs, and shaping long-term strategy. At the same time, they need a clearer understanding of how AI works, not at a technical level, but enough to know when to rely on automation and when human judgement is essential.
“Leaders will play a central role in shaping this partnership. The most effective will engage directly with AI rather than delegating, invest in the human skills that matter most, and balance gains with responsibility, safety, and trust. The outcomes for firms, workers, and communities will ultimately depend on how organizations and institutions work together to prepare people for the jobs of the future.” McKinsey Global Institute Report, Agents, Robots, and Us: Skill Partnerships in the Age of AI
In practice, the role becomes more dynamic. A sales manager might help their team interpret AI-generated insights to tailor client conversations more effectively. A customer service leader may oversee a blended workforce of people and AI agents, ensuring that both operate smoothly together. In technology functions, development managers focus on architecture, quality, and team capability while automation accelerates coding and testing tasks.
Ultimately, the evolution of the manager’s role is less about replacing responsibilities and more about advancing them. As AI becomes embedded across workflows, managers become the bridge between human expertise and digital capability, guiding their teams through change and helping the organisation get the best from both.
What it Takes to Succeed
What sets successful organisations apart is not just their investment in AI, but the way they approach this transformation. It always starts at the top. When CEOs and executive teams champion the work, it shows that transformation is central to the organisation’s future. Executive involvement helps set direction, secure the right resources, and ensure the entire organisation understands the ambition behind the change.
Equally important is the culture that surrounds this work, companies that make real progress create an environment where teams feel comfortable experimenting, testing new ideas, and learning from early missteps. This openness encourages innovation and builds confidence, allowing people to adapt more naturally as new AI systems are introduced.
Another defining characteristic is that these organisations don’t view AI as a standalone tool. Instead, they rethink the roles, skills, and processes that surround it. They invest in training their people, redesigning workflows, and updating structures so human expertise and AI capabilities reinforce each other. This ensures that technology becomes an enabler of performance, not just another layer of complexity.
Finally, successful organisations look beyond the immediate horizon. Rather than chasing quick wins, leaders imagine what their business should look like in three to five years’ time and work backward from that vision. This longer-term perspective helps them make thoughtful decisions today about skills, systems, and strategy that position the organisation to thrive as AI continues to evolve.
Seizing the Opportunity
The technology is ready, and the economic potential is enormous. Early adopters have demonstrated that thoughtfully redesigned workflows can deliver faster results, better customer experiences, and stronger organisational capability. What remains uncertain is how many companies will make the deeper, sustained investment required.
Redesigning work requires rethinking processes, retraining people, updating performance systems, and often reshaping organisational culture. The £2.9 trillion question is whether leaders are willing to redesign work boldly enough to capture its full potential while ensuring their people remain engaged, capable, and valued in the AI-enabled future.
Organisations that get this right won’t just become more efficient, they will become more agile, innovative, and resilient, fully equipped to seize the opportunities of the next decade.