Are We Using Yesterday's Measures to Identify Tomorrow's Talent?
By: Richa Joshi
I have been thinking a lot about careers lately, not just my own, but how we evaluate people in general.
For most of the last century, we have operated under a fairly straightforward assumption. A good career is one that shows progression within a particular discipline. We expect people to pick a field, gain experience, deepen their expertise, and move up through increasingly senior positions. The deeper the specialization, the more valuable the individual becomes.
That model made sense for the world that emerged after the Industrial Revolution.
But I am beginning to wonder whether we are crossing a threshold similar to the one society crossed during that period, and whether many of our assumptions about careers are becoming outdated. One of the things that fascinated me while studying architecture was how cities changed during the Industrial Revolution. Entirely new building types appeared. Warehouses, factories, train stations, office buildings, and industrial facilities suddenly became essential parts of society.
The interesting part is that nobody initially knew what these buildings should look like. Industrial buildings borrowed elements from churches, government buildings, and traditional architecture because architects were trying to solve new problems using old frameworks. Only later did architecture evolve forms that reflected the true purpose of these buildings.
Globalization created a similar shift. Over time, office towers in Toronto, Moscow, Dubai, Tokyo, and New Delhi started looking remarkably similar despite dramatically different climates, cultures, and histories. The world became increasingly standardized. Business practices became standardized. Education became standardized. Careers became standardized.
The successful professional was expected to follow a predictable path. But I am not convinced that the next phase of economic evolution will reward the same things. Artificial intelligence is doing something much bigger than simply automating tasks. It is changing our relationship with information, knowledge, and work itself.
Information has been abundant. Unfortunately, misinformation is becoming abundant as well.
The challenge is no longer finding information. Most people can access information instantly. The challenge is determining what is accurate, relevant, useful, and trustworthy.
Knowledge is not information. Knowledge is the ability to evaluate information, challenge assumptions, identify bias, understand context, and separate signal from noise. Wisdom is knowing what to do with that knowledge.
As information becomes more accessible, I suspect these higher-order capabilities become more important rather than less.
At the same time, many of the problems we face no longer fit neatly into traditional categories.
Take economic development. Is it a business issue? A workforce issue? An immigration issue? A housing issue? An education issue? An infrastructure issue? The answer is yes.
It is all of them.
The same can be said for healthcare, community development, climate change, talent attraction, nonprofit leadership, and many of the challenges organizations are dealing with today.
These are specialist problems and systems problems. They exist at the intersections. And that is where I think our hiring systems may be lagging behind reality.
For decades, we have rewarded specialization. We built job descriptions around it. We built educational systems around it. We built hiring processes around it. Artificial intelligence has the potential to help us move beyond those limitations.
Ironically, many organizations are using AI to do the opposite. Instead of identifying patterns, transferable skills, adaptability, and potential, we are often using AI to automate keyword matching. The very technology capable of understanding context is frequently being reduced to a compliance tool. A resume becomes a checklist.
Exact title….Exact degree…Exact years of experience…Exact industry.
The candidate either matches or does not. But is that really the best way to identify talent in a rapidly changing economy?
Imagine two candidates.
One has spent twenty years doing essentially the same thing in the same environment. The other has worked across industries, functions, countries, cultures, and organizational structures. Traditionally, the first candidate often appears safer. Yet the second candidate may have repeatedly demonstrated something increasingly valuable: the ability to learn, adapt, and become effective in unfamiliar situations. They have had to build credibility from scratch, learn new systems, understand different stakeholders, translate ideas between disciplines, operate with incomplete information, recover from mistakes. And most important of all: start over.
Those experiences leave patterns.
If you ask someone who has gone through multiple transitions how they handle change, they rarely need to think very hard about the answer. They have lived it. The answer is not theoretical and almost always experiential. This does not mean expertise becomes irrelevant. I do not want my surgeon learning on the job. I do not want a structural engineer designing bridges based solely on transferable skills. Society will always need deep technical specialists.
But many leadership, strategy, innovation, community development, nonprofit, and management roles operate differently.
The value of these roles often comes from connecting expertise rather than possessing all of it. Interestingly, we already recognize this principle in other parts of society. National leaders come from remarkably different backgrounds. Lawyers, economists, business leaders, military officers, teachers, lifelong politicians, entertainers and some inherit leadership through lineage.
What they share is not a profession. What they share is an ability to operate in complexity, make decisions with incomplete information, navigate competing priorities, and lead through uncertainty. Yet when evaluating talent for roles much lower in organizational hierarchies, we often become far more rigid.
That contradiction fascinates me.
Perhaps it made sense during periods of stability. I am not sure it makes as much sense during periods of transformation. And transformation is exactly where I believe we are today.
We are crossing the threshold as we speak.
Just as architects during the Industrial Revolution could not fully imagine what modern cities would become, we cannot fully imagine what work will look like twenty years from now. What we do know is that periods of significant change tend to reward different capabilities than periods of stability.
The Industrial Revolution rewarded specialization.
Globalization scaled specialization.
Artificial intelligence may increase the value of integration.
Not because expertise becomes less important.But because expertise alone may no longer be enough. The future will still need specialists. But it may increasingly reward people who can connect specialists.
People who can learn quickly, move between disciplines, understand systems rather than silos, who can recognize patterns where others see categories. Perhaps the question organizations should be asking is not "Has this person done this exact job before?"
Perhaps the more important question is: "What evidence exists that this person can solve problems that neither they nor we have encountered yet?" Because if we are truly crossing a threshold, that may become one of the most valuable capabilities of all.
About the Author
Richa Joshi is a Program Lead with the Sarnia-Lambton Newcomer Hub, where she designs and delivers workforce integration initiatives that connect newcomers, employers, educational institutions, and community organizations. With experience spanning architecture, education, business development, strategic partnerships, and economic development across India, Japan, and Canada, she is particularly interested in the intersection of workforce development, systems thinking, and the future of work. Richa also serves as Co-Chair of the Women in Communications and Technology (WCT) London Chapter.
Connect with Richa on LinkedIn here.