Artificial intelligence is reshaping every business, including ours. But the hardest challenge is not adopting it. It is rewiring your company around it. How corporate leaders respond to that test will determine whether AI shrinks their ambition or raises it.
Throughout history, progress has come from pairing new tools with enterprising people who want to build what comes next. For companies that mistake AI’s greatest value as cutting costs, this moment will be painful. For those willing to bet on equipping good staff with extraordinary technology, this is a golden opportunity.
The reason why some will miss out is straightforward: AI adoption and spending are soaring, but many businesses are still struggling to turn that investment into better decisions, faster execution, new capabilities — and measurable returns.
To see what they’re missing, we can look at some of our own client work. After one recent software-delivery project, a team that had needed about 10 people now operates with four, supported by AI agents that help build code, test software and do analysis. The group’s manager validates the agents’ work and has more time to take responsibility for what’s produced. The team’s engineer spends their day building, supervising and improving the system itself.
Elsewhere, a large manufacturing client introduced an agentic AI system that reduced human error in a production process from 5% to 0.5%.
Does this all make it inevitable that AI adopters will need fewer workers? No. When tech improves, the best people move on to the next hardest problem. That’s why we’re hiring more client-facing consultants, aiming for a 20% increase this year — most of them in entry-level positions.
And it is not just consulting. Some recent studies have found that companies investing more aggressively in AI are also hiring more. This technology changes the work people do, but it also creates the capacity to do work that simply was not possible before.
Our own research has found that 88% of companies use AI in at least one business function, but far fewer are realizing meaningful value from it. Closing that gap is a leadership and talent problem.
The trickiest questions for companies are around how the technology will affect their operations and culture, and the risks it might entail. That feeds into the hiring and talent question, too. Business leaders must decide where AI should be allowed to make decisions and where people must remain accountable.
One of the greatest difficulties for firms is how to redesign the way they work around intelligent systems, and how to try to carve out an advantage when their rivals have access to the same models. Beyond that, they need to work out how to make AI strengthen the values that define their organizations.
Given the rapid evolution of AI tools, and the profound challenge of how to reengineer entire organizations around their use, finding people who are comfortable navigating complexity is essential. Other assets coming to the fore include the ability to exercise sound judgment without as much oversight as in the past, and a gift for knowing what to trust and what matters when working with an emerging technology.
Fortunately, many students coming out of university today are AI-native and have grown up through Covid disruptions and political uncertainty. They are more used than previous generations to operating in a state of flux.
People from non-traditional recruiting backgrounds are in demand, too. If they can show technical, leadership or problem-solving skills, they can be trained on the rest. That means earlier client exposure, greater ownership of projects from the get-go and the experience of leading change within organizations — an urgent and critical task in the AI era.
AI is, of course, changing how we work in our firm as well. It is taking on repeatable tasks and freeing people up for more consequential stuff.
One team cut its document review time from days to minutes; another compressed a week of analysis into half an hour. We have more than 500 consultants working in “agentic team rooms,” alongside AI coding and research bots that can spin up working prototypes and analytical workflows in days rather than weeks.
That raises a bigger question: If AI can do more of the work that once trained future bosses, how do we prepare the next generation to lead?
For us, the answer is getting people to do work that builds their judgment. AI lets our new joiners spend less time searching for information and more time structuring problems, testing ideas and deciding what matters. Entry-level work is no longer just about analysis.
For students and graduates deciding where to invest their time, the answer is simple: Don’t gamble on today’s technology. Think about the human attributes that will become more valuable as these tools proliferate and improve. These include working well with others, a desire for constant learning and being able to apply judgment when an AI’s answer isn’t enlightening.
For chief executive officers, there is no playbook to copy. There is no benchmarking against rivals. The challenge is reshaping organizations so AI changes the very nature of how decisions are made and work gets done. Doing this at enterprise-scale will still demand human expertise and staying power.
The firms that treat this moment as a headcount problem will shrink to fit it. Those that bet on talent will gladly fill that space.
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