Artificial Intelligence (AI) is about to expose how little we know about talent 

We’ve built hiring, promotion and succession systems around a familiar type. We tend to trust people who present themselves confidently, progress at the expected pace and describe their achievements in language senior leaders understand. These “well-rounded” people may be excellent, and indeed many are. But employers often only notice talent when it looks familiar to them.

AI could blow a hole in this system. As it becomes part of everyday work, it’s changing the link between what someone can do and what other people can see. For example, a person may have strong ideas but struggle to turn them into a clear document. AI can help organize and express those ideas, making existing ability easier to recognize.

It can also create the opposite effect. Someone with limited understanding can use AI to produce polished work that sounds more thoughtful than it is. A strong document may therefore tell us less about the person who wrote it than it did before.

Meanwhile, for some neurodivergent people AI may remove barriers that have little to do with their ability to do the job. It will not make everyone suitable for every role, but it could give more people a fair chance to show what they can do. It may also reveal how much talent employers have missed because jobs and assessment methods favored familiar ways of thinking, communicating and working.

Potential is becoming more dynamic as the work, tools and skills around a person change. Past performance still tells us something but it’s likely to become a weaker signal to what someone could do next. As quite frankly the future is being continuously rewritten as we envisage a future where work processes are redefined and human capabilities amplified. 

Before organizations celebrate an exciting new era of human potential, they should admit how little they can see. Most do not have a reliable view of the potential already sitting inside the business. And too often the picture is blurred by un-synthesised information on a variety of personality factors, thinking skills, leadership style with tenuis links to the changing world of work. 

Its therefore no surprise that only 32% of employees believe their company is aware of their ability to operate in more complex or senior roles. And just 35% of human resources (HR) leaders believe their talent data allows them to identify quickly who might be best suited to a role or assignment. These figures suggest a remarkable amount of guesswork.

Companies often search outside for scarce skills while people inside are overlooked. Talent intelligence can reveal skills and experience that job titles miss. But there is a danger here too. An algorithm built on a narrow or outdated view of potential will simply repeat the same narrow judgments faster.

Only 37% of HR leaders believe their organization handles high-potential identification and succession planning well. This figure should make companies cautious as they bring in new assessment tools and question the return their ‘tried and tested; tools are really delivering

Potential assessments often look backwards. They draw heavily on experience, past performance and the qualities that helped previous leaders succeed. They also capture a single moment, even though people continue to learn and the work around them continues to evolve. Never has potential been more dynamic. 

Experience will only take you so far, it’s the breadth of a leader’s business thinking that they can deploy in any new situation that is the real differentiating factor. Yes, this is built from experience and exposure but not necessarily a correlate. Measure it directly, don’t infer it from what they’ve done – too often people apply their tried and tested methods over and over again until they don’t work. Leaders who thrive today have a broad lends on strategy, risk and commercial matters that enable them to adapt and learn at pace. 

The challenges leaders face today are not complicated (leaner and solvable), they are complex with many intersecting trends and challenges. It’s no surprise that 78% of the C-suite agree that managing paradoxes is key for effective leadership. This will only become more critical in the years ahead, but too few companies measure a leader’s ability to manage competing demands – knowing when to focus on the task, or the people, and when to be directive or empathetic. Our research points five critical leadership paradoxes.

Finally, success is no longer about balancing intelligence quotient (IQ) and emotional quotient (EQ), its bringing these to bear with DQ (Digital Quotient). The latter of which is needed in leadership, but also now underlying many technical skills – from how you code with AI to how you do strategic workforce planning, to how you leverage AI in performance feedback skills. Our research found that 67% of HR leaders planned to improve how they measure technical skills in 2026, while 62% planned to use tools such as psychometrics and simulations to deliver a more robust and rounded view of capabilities. Almost half planned to share assessment findings with managers and leaders.

Despite the proliferation of skills assessments, there is no getting away from the predictive power of modern psychometrics built for our age. Once you have baseline information on your workforce’s capabilities, you can add skills, performance, even information from an employee’s digital exhaust, to build up a more robust picture – enabling greater prediction around what helps someone to thrive, where they fit best and what might grow their career. 

AI is already helping a more diverse range of people show what they can do, especially where old ways of working or outdated tests have hidden their strengths. However, much will depend on who gets access to the tools and how decisions are made in the evolving field of talent science.

Uneven access could give some employees an advantage from the start. Algorithms trained on past success may also keep favoring people who look like previous leaders, while others are judged by systems they do not understand and cannot challenge. Overuse of traditional personality and cognitive models, assessing skills without AI assistance may miss the nuances in leadership and skillsets necessary to succeed in today’s workplaces. 

Companies need clear rules on access to their data and how assessment insights are being used but also should be active partners in building their own profiles. Get it right and talent development and deployment can be based on real science - driving much needed workforce agility and closing the gaps in knowledge and exposure bought about by AI-robbed development experiences.

AI is already disrupting work people often do at the start of their careers, such as research, first drafts and simple analysis. The challenge now is how to ensure we build the wisdom workers of tomorrow when young talent doesn’t have experiences that show how decisions are made and give them feedback on mistakes (when the risks are still relatively low).

As knowledge work is done in ever more Ai-powered ways, companies are seeking other ways to build the experiences that can shape futures. We are seeing dividends in measuring individual’s AI Agility to drive customise training, based on their unique needs with real-time simulations aligned to their role. We’ve also seen rapid immersion labs useful – not only to see where AI can rethink a process but to expose young talent to what is involved in the tasks today and where value is created. The honest fact is its not about replicating past experiences, its figuring out what human skills now become more relevant. And this, in turn, reshapes our notion of potential.

AI is making companies look again at how they identify potential and decide on who is a successor. Traditional models – human or algorithmic - relied heavily on past experience and a one-off view of someone’s assessed ability often on tests or tasks that didn’t resemble todays challenges. When jobs, tools and business needs keep changing, our blueprint and our methodologies need to advance in step.

Companies should use AI to question their old assumptions before using it to make decisions about people. Otherwise, they may spend heavily on new technology while keeping the same limited view of talent. Keen to talk more on how this space is evolving, reach out or catch up on our latest article Global Talent Trends 2026 – Leap forward with insight report explores how talent intelligence can strengthen workforce resilience, address the AI skills gap and improve decisions about talent as work changes.