BCG on Why Reskilling Employees Is the Missing Link in AI Adoption

What if the greatest barrier to artificial intelligence (AI) adoption is not the technology itself but the way people experience it at work? That was the premise behind our recent conversation with Sagar Goel, Managing Director and Partner at Boston Consulting Group (BCG), who leads the firm's global work on digital workforce development and reskilling.

Goel shared the latest findings from BCG's AI at Work study with Techopedia, which explores the disconnect between corporate ambition and employee readiness regarding AI.

Key Takeaways

• Frontline AI adoption stalled at 51%.

• Only 25% feel supported by leadership for AI use.

• Leaders fear job displacement more than frontline workers.

• Reskilling needs executive mandate and business integration.

• Global South outpaces the US in AI workforce adoption.

• Collaboration across sectors is vital for scalable workforce development.

AI Adoption Has Hit a Wall on the Frontline

Sagar Goel opened our discussion with a reality check, saying:

"Frontline usage of AI is stalling at about roughly 50-51%. Companies are thinking about this from, I would say, the tools angle, but not so much from what it means for the actual employee."

Despite years of hype, the data shows that entry-level AI usage has plateaued, and many workers still do not feel equipped or supported to use the technology effectively.

According to Sagar, this is not a failure of technology, but of framing and leadership. He explained:

"We heard that only 25% of the frontline employees are really feeling that leadership support and role modeling when it comes to AI adoption." 

Training is also lagging. "Only 36% of the frontline employees that we surveyed were really satisfied with it," he said. For all the corporate fanfare about transformation, only a small fraction of workers believe their leaders are helping them adapt.

The Adoption Gap

Goel described what he calls a three-part breakdown in how organizations approach AI. "It really starts with companies thinking about the right framing, providing the leadership support, and the training that has to go along with it," he said.

However, many employees are still unsure of the boundaries for safe AI use. "What are some of the guardrails of how they're supposed to use or not use some of these AI tools? It really starts with that," Goel pointed out.

Even when tools like ChatGPT are available, they are rarely used with clear work objectives. Goel stated:

"A study with ChatGPT showed that the majority of ChatGPT usage today, about 70% of all the usage, is focused on non-work-related." 

He added that the most common use cases are "more information gathering, administrative uses, some creative tasks." This gap between availability and meaningful use is where many organizations are now stuck.

The implication, according to Sagar Goel, is that companies must stop assuming awareness equals adoption. The reskilling and upskilling only emerge when employees understand how AI fits into their roles, and when leaders model its responsible use. He said: 

"There is just a lot of untapped potential in how these AI tools can be used back at work. If, number one, companies think of the right framing, number two, providing the leadership support, and number three, the training that has to go along with it."

The Anxiety Divide

Interestingly, BCG's research found that leaders are more anxious about AI than their frontline teams. 

Goel told Techopedia:

"About 36% of frontline said that they feel that jobs might be potentially at risk, versus for managers and leaders, that number was around 43%." 

He sees two reasons for this reversal. "They are really ahead in terms of the understanding and the awareness of the structural shifts in the market and the business, how AI can disrupt their business model, and what it means for them. So their level of awareness is much heightened," Goel explained.

Second, many leaders have fewer years left in their careers and, therefore, "their own level of preparation and readiness to rescale and retrain might also be relatively lower compared to the frontline."

Yet the deeper risk, he argued, lies at the bottom of the hierarchy: "We might have more impact, especially on entry-level roles, as AI and agentic AI can help automate, and we will see a clearer shift." 

This is why clear communication and strong policy frameworks are now essential. Goel said:

"Companies need to be very clear on what the governance models and policies are, on what tools can and cannot be adopted by their employees. Yes, you have to drive innovation, but can it first come with clarity around communication and policies by the company on how they want their employees and where they want their employees to use AI?"

The Global Picture

Another notable finding in BCG's AI at Work report is that the United States lags behind the global average in regular AI use. 

"The share of employees who use AI several times a week is indeed lower in the US compared to the global average," Sagar said. "In the US, it's about 64% versus a global average of 72%."

The reasons are structural, not cultural. "The way I would explain this difference and lower uptake in the US is more a function of just the maturity of the market and the labor market policies in the US or a more developed economy," he said. In other words, the more established the economy, the more cautious the integration.

By contrast, the Global South is accelerating ahead. "Let's take a market like India," Sagar said. "We're talking about 16% youth unemployment rates in that country. So, it means that both the youth and we see that Gen Z and millennials are actually much higher adopters of AI. This comes naturally to them, and they also see this as a differentiator for themselves in the job market."

When opportunities are limited, he explained, technology becomes a lifeline rather than a luxury. 

"You will see higher adoption, you will see some of the early trends around adoption," he said.

When our conversation turned to reskilling in the age of AI, Sagar drew a sharp distinction between upskilling and reskilling the workforce. "The two are actually different, and both are important in the context of AI," he said.

What Companies Are Getting Wrong

Goel acknowledged that many organizations continue to misunderstand the characteristics of effective reskilling programs. "We see this story play out time and again," he said, recalling an example from North America.

"We were working with a software company when we did the first survey to understand the sentiment of this new AI tool that we wanted the software engineers to adopt. Seventy-five percent of the software developers and engineers told us, ‘This is fantastic. We are very, very excited about that.’ But when it actually came down to adopting these new tools, it was only 25% of them really doing that in a meaningful way."

He described the gap between perception and practice as "a stark difference between what's the perception and the reality on the ground." 

The issue, he said, can be broken into three parts: the why, what, and how: "The why is really starting from why are we doing this? Why do we need our software engineers, customer service staff, or frontline staff to adopt these new AI tools? What's in it for them?"

This is where most companies fail. "This can't be just a productivity conversation, which is where companies are missing the point. This is an opportunity for companies to actually bring more enjoyment back to work, where AI or GenAI can be used to automate away some of the work that is perceived as toil by the employees versus joy,” he said.

When implemented thoughtfully, reskilling employees is not about survival but satisfaction. "This is also an opportunity for companies to help their employees think about how this will improve their efficiency and effectiveness at work, which is beyond productivity," he added.

Beyond Technical Skills

Goel believes that organizations often over-index on technical training. He said:

"The challenge that I'm seeing is companies focusing a lot on more of the technical skills. But this is beyond just the core technical skills. The core critical skills are becoming more and more important."

These critical skills include "the ability of an individual to actually frame the business problem, understand what the pain points and the friction points I'm solving for." That, he explained, is the proper foundation of applied AI. "The first step is not the tool or the technology," he said. "It is identifying what the problem statements are and how I can then bring the technology solution to it."

Even when employees are familiar with the tools, companies must still address the human side. "We can't think of this as being one day training or a few hours of an online module that at best gives us some basics of how to use these tools," he warned. "Companies need to think of the long tail of change management to drive the adoption of these new tools."

For leaders seeking measurable outcomes, Goel's message was clear: 

"Companies that want to do this well and succeed, have their employees satisfied, and get the business results, have to rethink their ‘why, what, and how’ of upskilling."

Collaboration at Scale

To tackle the global skills crisis, BCG's Human Futures Lab is studying how different sectors and governments can collaborate more effectively. 

Goel said:

"I'm a firm believer that upskilling and reskilling at scale, where you're talking about millions of people globally every year who need to be upskilled and reskilled, it is going to take a village. Individuals, companies, industry associations, NGOs, governments, all of them need to work in tandem if you were to solve this challenge at scale.”

He cited the half-life of skills, which "is now at five years, which means every five years, half of your skills become redundant."

That, he said, is a challenge "that no one stakeholder could solve." The most promising solutions are collaborative. 

"Here in Singapore, more than 20 banks and financial services companies have gotten together, stating we all have a common challenge of attracting technical talent into banks," he said. 

Instead of competing, they built a shared program. "They worked together to create a program along with IBF, which is the Association for Financial Services Skilling Work here in Singapore. They collaborated to create a common program to help individuals move from traditional operational job roles, maybe with no banking experience, and get reskilled into technical roles in banks," Goel explained.

In the US, a similar effort is underway. "We've also seen this in the US, in the auto sector in Michigan, for instance, where different companies are coming together and the government is playing an orchestrator role as well," he said. "These models where companies are actually collaborating versus competing for talent, I think, are the future models."

The CEO Imperative

When I asked what advice Goel would give to CEOs preparing for the next wave of automation, his answer was straightforward:

"If skills don't show up on your balance sheet, they won't show up in your P&L. As CEOs, if you are not upstream thinking about what the impact of the workforce and the new skills that you need, or the existing skills that you have untapped today, and link them up front with your business strategy, I feel that's a huge loss of opportunity."

Sagar believes the connection between strategy and skills will define the next generation of high-performing companies. 

"Your strategy is going to be as good as your skills," he said. "So my message or the first step would be, think of how you identify the implications and impact on your workforce and your skills, right upstream as part of your business strategy."

To illustrate what success looks like, he pointed to an IKEA example that captures the actual benefits of reskilling and upskilling, where new skills drive new revenue streams rather than merely yielding cost savings.

The Bottom Line

While technology is changing faster than it has in our lifetime, some things don't change, and enterprises cannot improve what they don't measure. This is why upskilling and reskilling efforts for AI need to be measured: to deliver on its promises and drive company progress.

The message from Sagar Goel is that transformation can be sustainable rather than just symbolic. But only when leadership treats talent development as seriously as revenue growth.

FAQs

How to stay employed in the age of AI?

Always keep learning and focus on integrating technology knowledge with human capabilities in areas that AI cannot compete, such as communication, management, reasoning, and creativity.

What is upskilling and reskilling in the age of automation?

Upskilling prepares workers to use new technology in their existing jobs while reskilling equips them to take new jobs that AI and automation will create.

Who benefits most from reskilling?

Companies should focus on employees in positions most vulnerable to automation and treat talent as an investment rather than a cost.