Organisations are embracing AI at an accelerating pace, with automation, faster decision-making and the promise of greater productivity reshaping how leaders think about work.
According to McKinsey & Co’s The State of AI report, 88% of organisations now use AI in at least one business function, while 79% use generative AI. As AI becomes embedded across more tasks, however, a paradox is emerging: the more work is automated, the more valuable human connection becomes.
Lance Neuhauser, CEO of The Predictive Index, a leading behavioral intelligence company, believes that AI is changing what it means to be valuable at work. As organisations automate more tasks, he argues that behavioural intelligence is becoming a key differentiator.
“Today, we have machines that are starting to take over work that people are most known for, and they often complete these tasks more efficiently with fewer errors. So what does this mean for the identity of the individual within work? What does that do to team design and dynamics when you have to account for new ways of operating?” asks Neuhauser.
“It is causing what some have referred to as the greatest advisory moment in the history of the world. Every institution, government and business is having to redesign the way they work without breaking the human system that underpins it. That is a huge challenge,” he adds.
As organisations redesign work around AI, employees are looking to leaders for more than technical direction. They want clarity about how roles are changing, confidence that AI will be used responsibly and reassurance that human judgement still has a place in decision-making. Those expectations make trust and communication more important than ever.
For Neuhauser, this new reality means that experience and technical skills are no longer enough on their own. Increasingly, value comes from an individual’s ability to apply judgement, provide context and understand how to work effectively with others in an AI-enabled environment.
“A year ago, a developer’s job would have been focused on coding and moving faster. Today, it’s about reviewing code and architecture, ensuring that you are giving the right prompts and context to AI to get your desired outputs,” he says.
“Similarly, a junior analyst used to be judged on providing data analysis promptly and without errors. Now, they have to think more broadly and bring unique context. With all this change in mind, we happen to think behavioural intelligence is having a moment,” adds Neuhauser.
Efficiency vs effectiveness
One of the key challenges of AI adoption is building trust with employees about how it will be used and what their roles will look like going forward. However, many organisations still grapple with the tension between using AI to drive efficiency and using it to make their people more effective.
A recent study by Ipsos Karian and Box surveyed 5,000 UK employees about their thoughts on the future of work. It found a clear disconnect between how leaders and employees view AI. Two-thirds of leaders believe that it is clear how AI can help their organisation, but just 23% of non-managers agree.
Furthermore, only 39% of employees believe that AI is currently being used to solve the right problems in their organisation, with just 38% saying they’d feel confident they’d be supported rather than punished if they missed an error by AI.
The findings suggest that successful AI adoption is as much a people challenge as a technological one. If employees don’t understand why AI is being introduced or how it will affect their work, organisations risk creating uncertainty and resistance at precisely the moment they need confidence and collaboration.
“While I believe that most leaders truly want the best for their organisation, there is a tendency for many to overemphasise efficiency,” says Neuhauser.
He believes there are two reasons for this. Firstly, it is clear AI can do some tasks more quickly and efficiently. However, as Wharton professor Ethan Mollick has described, AI is a ‘jagged frontier’ — able to do some tasks incredibly well and others surprisingly badly. Often, it isn’t until you get into the weeds of the work that you realise which.
The same principle applies to decisions about people. AI can surface patterns and recommendations, but managers still need to interpret those insights within the broader context of an individual’s strengths, aspirations and team dynamics.
“As great as LLMs trained on vast amounts of data are, it’s not until true experts in getting tasks done are involved that you realise where they might be going wrong. Until you have that context and human judgement, it might seem like you’re being more efficient, but actually you’re making things harder,” says Neuhauser.
Secondly, organisations often pursue AI efficiencies by hollowing out middle management and entry-level roles, creating future talent issues.
“Some tasks that junior employees do can be automated, but what organisations end up doing is blocking future managers. You remove their ability to learn and end up hurting your future self,” says Neuhauser.
“With middle management, these are the people who are creating and implementing your processes, the ones who keep work flowing. By automating their roles, you are hurting the backbone of your organisation,” he warns.
Avoiding AI pitfalls
For Neuhauser, the approach is twofold: understand your specific desired outcome from technological intervention, and then match the behavioural profiles of your people to the tasks within it.
“Before you even think about technology, take time to understand what your pain point is and what outcome you want. After you realise the problem, work on how to move this from idea to output. What is the process? What needs to be reworked? Then, and only then, look at new tools and where they can deliver value,” he advises.
Behavioural insights help organisations understand how people respond to change, communicate more effectively and build complementary teams. As AI takes a more prominent role in the workplace, that understanding can help preserve the human-to-human connections that underpin effective collaboration. With roles and skill requirements evolving rapidly, knowing how people work together may become more valuable than ever.
“Job roles are going to change, and so the behavioural profiles of successful individuals will do too. Match roles with behavioural identities. We’re in the midst of a transformative labour moment, but the organisations that do things the right way can walk out of this with more trust, organisational cohesion and the ability to deliver more value,” says Neuhauser.
AI may reshape how work gets done, but it doesn’t diminish the importance of people. If anything, it raises the value of leaders who can build trust, understand behaviour and create environments where both people and technology perform at their best.
Discover how The Predictive Index can help your organisation strengthen human connection and build more effective teams in the age of AI. It all starts with taking PI’s Behavioral Assessment — let’s get started.
Organisations are embracing AI at an accelerating pace, with automation, faster decision-making and the promise of greater productivity reshaping how leaders think about work.
According to McKinsey & Co’s The State of AI report, 88% of organisations now use AI in at least one business function, while 79% use generative AI. As AI becomes embedded across more tasks, however, a paradox is emerging: the more work is automated, the more valuable human connection becomes.
Lance Neuhauser, CEO of The Predictive Index, a leading behavioral intelligence company, believes that AI is changing what it means to be valuable at work. As organisations automate more tasks, he argues that behavioural intelligence is becoming a key differentiator.
