Why Corporate Training Matters More Than Ever in the Age of AI

What makes a workplace truly work?

In the late 1960s, thousands of workers built cars by hand on factory floors, but over time automation dramatically reduced those roles while increasing demand for specialized, non-repetitive skills.

“When my Dad started at Ford in ‘67, there were 3,000 mostly men working on the line. By the time he left, there were maybe 700,” recalls Derek Cairns, MA, business leader, AI educator, and growth strategist, who is one of the speakers at the upcoming AI in Action Summit, hosted by The Chang School at Toronto Metropolitan University in June. Derek is presenting at the one-day event where he will be leading a workshop on how to get better results from AI through prompting.

 

Derek went on to say that there’s a similar shift underway today. But instead of factory floors, it’s happening across offices and industries everywhere.

“AI is going to do the same thing to any work where you’re sitting in front of a screen,” he says.

That shift from manual labour to knowledge work once felt like a step toward stability. But with AI now capable of performing many cognitive and repetitive tasks, even traditionally “safe” office roles are being redefined.

Derek’s lesson from his father’s experience is clear: survival wasn’t about working harder, it was about doing work that machines couldn’t easily replicate. The same principle applies today and at a much broader scale.

“If your job is mostly repetitive tasks, that’s where you have to really retool. Don’t try to compete with the AI — leveraging the AI will get you somewhere,” says Derek.

That need to “retool” is where corporate education and training come into sharp focus.

As AI accelerates change across industries, organizations can no longer rely on traditional hiring or static skill sets to stay competitive. Instead, they’re being forced to rethink how they develop talent from within — continuously, strategically, and at scale.

And the stakes are higher than ever.

“Everyone needs to be a lifelong learner. You can’t say, ‘I’m five to 10 years away from retirement, I’ll just rely on my existing skills,’” says Derek.

In other words, corporate training is no longer a periodic investment — it’s becoming a core business function. In a landscape where roles are evolving in real time, the organizations that prioritize learning won’t just keep up — they’ll define what comes next.

A Workplace in Flux

The challenge is no longer just adopting AI tools — it’s learning how to manage a hybrid workforce of people and intelligent systems.

For leadership, AI becomes a question of how do you manage a workforce that is using AI tools or agents.

Derek adds that many organizations aren’t underestimating AI so much as struggling with the speed and uncertainty surrounding it.

“It’s a bit of a deer-in-headlights moment,” he says. “Most organizations don’t even know which models will be dominant yet, and enterprise-level decisions take time. But at some point, companies are going to have to place a bet and move.”

He adds that organizations waiting for certainty risk falling behind competitors that are already experimenting and adapting.

“If you wait for all the right answers and things to fall into place with AI, you’ll get so far behind that you can’t catch up.”

From Job Loss to Job Transformation

While some organizations are using AI to reduce headcount, others are focusing on redeploying talent into new roles.

“There are jobs within organizations that are becoming obsolete, but they may have really great talent in those people — so do you just wipe them out, or do you help them pivot?” says Sylvia Franklin, Director, Business Development, The Chang School.

In fields like marketing, this transformation is already underway.

“In marketing, a lot of companies are downsizing their teams because they’re using AI to do a lot of those roles,” she explains.

The alternative, she argues, is reskilling.

“Let’s help these people pivot — maybe into project management or another area that supports the organization.”

Derek encourages organizations to shift the conversation away from jobs being replaced and toward tasks being transformed.

   

“Look at the tasks you do and quickly become efficient at the tasks AI can do, while becoming even better at the things AI can’t do yet.”

That includes areas requiring judgment, relationship-building, and strategic thinking.

“A lot of business is still relationship-based — whether that’s with customers or suppliers. Those human-centered skills are still incredibly valuable.”

The New Skills Equation

As AI takes over more technical execution, the value of human skills, particularly critical thinking, is rising.

In this environment, soft skills are no longer secondary — skills like communication, critical thinking, and adaptability are more important now than they ever were before.

Derek says one of the biggest skill gaps organizations face today is knowing how to effectively work with AI systems.

“Most people write two- or three-sentence prompts and treat AI like a search engine,” he says. “But for complex work, your prompts should be detailed and highly structured.”

He also warns against blindly trusting AI-generated outputs.

“Most people are taking AI outputs at face value and not thinking critically about what’s actually being produced,” says Derek. “You still need human judgment and critical thinking to evaluate what’s useful, biased, or inaccurate.”

What Effective Corporate Training Looks Like Today

That shift is exposing the limitations of traditional training models.

“It’s not about clicking through training and just checking off boxes to get to the next page,” says Sylvia.

Instead, she says, learning must be practical and directly tied to real work.

   

According to Derek, organizations also need to move beyond one-size-fits-all AI training models.

“Everybody needs foundational AI literacy, but organizations also need specialized teams that are moving much faster,” he says.

Those teams, he explains, are often the ones identifying entirely new ways of working and developing AI-enabled business models.

“This shouldn’t just be about doing the same work more efficiently,” says Derek. “The real opportunity is creating offerings and ways of working that weren’t possible before.”

Reshaping Human Value

Ultimately, what happened on the factory floor in the late 1960s is what’s happening in today’s knowledge economy. The car didn’t disappear — the way it was built simply changed. Thousands of repetitive roles gave way to fewer, more specialized ones that required new skills, new thinking, and new ways of working alongside machines.

AI is following the same pattern. It’s not removing the need for human work; it’s reshaping where human value sits in the system. The question for organizations now is the same one that faced that factory generation: are we preparing people to do less of the manual, repeatable work — and more of the adaptive, judgment-driven work that actually moves the business forward?

Learning as the Future of Work

One thing remains clear: learning is no longer separate from work — it is becoming inseparable from it.

And in a world where technology is reshaping roles in real time, that continuous learning mindset may be the most important skill of all.

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