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A featured contribution from Leadership Perspectives: a curated forum reserved for leaders nominated by our subscribers and vetted by the HR Tech Outlook Advisory Board.
Juliet Latham is Director of Talent Development & Consulting Services at United Electric Supply, where she leads the organization's learning and development strategy. With more than 20 years of experience in learning, organizational development, and consulting, she works with leaders and employees to strengthen organizational capability, develop future talent pipelines, and align workforce development initiatives with business strategy.
AI, Expertise and the Future Leadership Bench
For most of my career in talent development, helping people learn faster felt like an unquestionably good thing.
Every year, new technologies provided faster avenues to learning and skill acquisition. Gamified assessments. Microlearning. Mobile-enabled LMS platforms where employees could complete coursework anywhere. Each innovation helped people acquire knowledge faster and become productive sooner.
AI has flipped the script. It is the first technology that forces us to reconsider whether becoming productive sooner results in stronger organizational capability over the long term.
For generations, productivity and development generally moved in the same direction. Employees became more capable because they spent time learning the fundamentals of their role. AI introduces a new dynamic where employees can often perform sophisticated tasks before they fully understand the thinking behind them.
Today, a new employee can retrieve complex information in seconds, draft persuasive emails before they have mastered business writing and access answers that once took years of experience to accumulate. Historically, those same interactions required time spent learning products, talking with customers, understanding applications and discovering why a customer needed something in the first place.
As I listen to veteran employees helping newer team members learn the business, I hear a common concern. If information, recommendations and answers are always readily available, how will employees develop the judgment to evaluate them?
People develop judgment and expertise by encountering ambiguity, making mistakes, receiving coaching and revising their thinking. Think about how many of us learned to communicate professionally. Chances are, we wrote an email we wished we could take back, received some not-so-friendly feedback and adjusted our approach the next time. The lesson stayed with us because we experienced the consequences and changed our behavior.
Traditionally, many of our employees learned the business at the counter. They searched catalogs and Googled, worked with physical inventory, asked experienced coworkers for help and talked with contractor customers about what they were building and why they needed a particular product. They struggled. They got things wrong. They asked follow-up questions. Over time, they developed product knowledge, customer understanding, confidence and judgment.
Today, employees and customers expect immediate answers. Customers often have information on their phones before a newer employee can finish searching. The expectation for speed has changed dramatically, but the process through which humans develop expertise has not. Learning still operates at human speed.
"People learn best from other people. AI can provide information, but mentors provide context, judgment, perspective and feedback."
This creates a serious talent risk. Today’s trainees will eventually be expected to advise customers, coach employees, make decisions and lead through situations where information is incomplete and the appropriate response is unclear. If a tool has always organized the information, suggested the questions and produced the answer, will trainees have enough experience to recognize when the answer is wrong?
Learning leaders must help organizations build that capability intentionally. We are still figuring out the balance, but several practices are becoming clear.
Several veteran employees that I have spoken with intentionally create opportunities for newer team members to work through problems before relying fully on AI tools. They want employees to understand the “why” behind an answer before accepting the shortcut.
For our training programs, we’re making sure learning assignments require employees to ask customers questions, seek help from internal experts, work through obstacles, receive feedback, and revise their efforts. Mistakes show the contrast between what works and what does not in a way people remember. Psychological safety gives learners room to be wrong, learn why and try again.
Employees need practice questioning AI output, requesting sources, comparing results with manual efforts, and looking for missing context. AI can deliver a flawed answer with remarkable confidence! Judgment allows a person to interrupt the faster process, challenge the output and improve it. When a professional can exercise judgement over AI, they are entering the realm of expertise.
Employees need practice questioning AI output, requesting sources, comparing results with manual efforts, and looking for missing context. AI can deliver a flawed answer with remarkable confidence! Judgment allows a person to interrupt the faster process, challenge the output and improve it. When a professional can exercise judgement over AI, they are entering the realm of expertise.
As organizations adopt AI-enabled tools and redesign the way work gets done, I find myself wondering about the employees who will eventually become our experts, trusted advisors and leaders.
Will they have enough opportunities to struggle with problems before receiving answers? Will they learn to recognize when information is incomplete or when a recommendation doesn't quite fit the situation in front of them? Will they develop the confidence to challenge an AI-generated conclusion when something feels off? Will they have enough experiences, mistakes, conversations and feedback to build the kind of judgment that customers and colleagues depend on?
At some point, every employee stops being the person asking the questions and becomes the person others come to for answers. The people entering our organizations today will eventually become our experts, trusted advisors, mentors and leaders. As learning professionals, we need to keep foundational skill development at the center of our strategies, even as technology changes the way work gets done.
