The prevailing narrative is that AI will eliminate retail jobs. But a report bu ServiceNow suggests a different story for Canada: retail employment is expected to remain essentially flat through 2031 (+10,000 jobs, +0.4%).
The AI Workforce Skills Forecast Report said the skills employers value are undergoing a significant shift. Demand is projected to grow for skills like Python, SQL, data analysis and leadership, while declining for routine transactional skills such as customer service, cashiering and cash handling. Rather than replacing retail workers, AI and automation appear to be replacing routine tasks—placing a premium on employees who can work alongside digital tools and leverage data.
The implication for retailers is clear: competitive advantage is likely to come less from expanding headcount and more from reskilling existing employees for an AI-enabled future.
In an interview with Retail Insider, Josh Newman, Vice President, Workforce Skills & Talent Readiness at ServiceNow, discusses the report.
Question: Your report suggests AI won’t significantly reduce retail employment in Canada by 2031. What data or trends led you to that conclusion, and why does it differ from the common perception that AI will eliminate retail jobs?
Answer: I think there’s an important distinction we need to make here, and it’s one that gets lost in a lot of the conversation right now. The data tells a much more nuanced story than “AI will eliminate retail jobs”.
Here’s what we’re seeing: In Canada, retail employment is projected to remain essentially flat through 2031, we’re talking an increase of about only 10,000 jobs, or 0.4%. AI is likely to change tasks before it changes entire jobs. That’s a critical difference. What’s actually shifting is the skills those employees will need as the sector becomes more digital and AI-enabled.
The Canadian retail findings point to growing demand for skills such as Python, SQL, data analysis, and leadership. At the same time, demand for certain frontline skills such as customer service and transactional skills like cashiering and cash handling is expected to decline as automated payment systems and self-checkout technologies handle routine point-of-sale transactions, particularly as more commerce shifts online.
This is why we see the retail story as one of workforce transformation, not workforce replacement. The report shows that as digital processes take on more routine work, the value of human capability becomes even more important: can your team lead? Collaborate? Make good judgment calls? Adapt when issues arise?
Demand is quickly shifting toward these kinds of qualitative capabilities which shape how effectively new tools are adopted, governed, and applied. Organizations that invest in both technical and human capabilities will be better positioned to translate AI adoption into real business impact.
Q: Which retail roles are likely to see the biggest transformation as demand shifts from traditional customer service and cashier skills toward data, technology, and leadership capabilities?
A: As mentioned, demand for skills such as customer service is projected to decline, while demand for skills such as Python, SQL, data analysis, leadership, collaboration and project management is expected to grow.
This suggests the greatest change will be in retail roles centred on routine transactional activities, as employers increasingly value digital, analytical and leadership capabilities in place of traditional customer-facing experience—with new roles emerging around online customer experiences and chatbot-managed interactions.
But I want to be really clear about this: frontline employees are being augmented, not replaced. AI takes on the routine tasks, the stuff that doesn’t require judgment. That frees people up to focus on the work that actually matters. Think about a cashier today. Right now, the’re spending most of their day processing transactions, handling cash, managing point-of-sale systems. With AI and automated checkout, that transactional work largely goes away. But that same person is now helping a customer solve a problem, recommending products based on what they know about that customer, managing a difficult interaction, mentoring newer staff. The routine work shifts to machines.
The human work becomes the priority. And that human work—the work that requires collaboration, problem-solving, judgment—that’s where retail creates value.
Q: How prepared are Canadian retailers to reskill their existing workforce, and what are the biggest barriers they face in making that transition?
A: I’ve seen this pattern across organizations and the honest truth is that the biggest barrier for retailers is mindset. Organizations that are making the greatest progress recognize something critical: AI adoption and workforce development must happen together. They can’t be separate initiatives. When they are, things fall apart.
The biggest barrier I see is treating AI as a technology initiative instead of a workforce transformation initiative. That’s the wrong frame entirely.
Building real AI capabilities requires organizations to invest in both technical and human skills, create clear development pathways, and—this is crucial—make learning part of everyday work rather than relying on one-time training programs. One-time training won’t cut it in this environment. The pace of change is too fast.
Q: What practical steps should retailers be taking today to help frontline employees develop AI-related skills without disrupting day-to-day operations?
A: What I’ve learned from working with organizations at scale is that the goal is to embed learning into the work itself, not pull people away from it.
As AI becomes more embedded in the workplace, organizations have an opportunity to move beyond the old training model. You know the one—you send someone to a class for two days, they take a test, and then they go back to their job unchanged. That doesn’t work anymore, and frankly, it never did work that well.
What works is making learning part of everyday work. Help employees build future-facing skills through their actual work. Create clear development pathways so people know where they’re heading. Support continuous learning over time, not one-and-done training events.
Take a store associate working on the floor. To learn new data analytics skills, instead of sending them to a two-day data analytics workshop, they can learn by analyzing the store traffic patterns they see every day. They start asking questions like: which products move fastest during which hours? What patterns do we see in customer behaviour and how can we adapt to meet customer needs? That’s real learning happening in the context of their actual work. Or a customer service rep learning to manage an AI chatbot by actually working with the technology to help streamline daily customer conversations, getting real-time coaching on how to handle the handoffs and the nuances that machines can’t figure out yet.
The good news: many of the high-growth roles build on capabilities employees already have. That makes targeted development both practical and achievable. You’re not asking people to become completely different people. You’;re helping them evolve.
The goal isn’t simply to teach people how to use new technologies. It’s to help them build the confidence and capabilities needed to adapt as work continues to evolve. Organizations that embed learning into everyday work are better equipped to respond to changing skill requirements and unlock the full value of AI.
Q: For retail workers concerned about AI, what skills or capabilities should they prioritize over the next five years to remain competitive and create new career opportunities?
A: If I were talking to a Canadian retail worker right now who’;s worried about AI, here’s what I’d say: the most important skill is adaptability.
Our research shows growing demand for both technical and human capabilities, reinforcing the idea that success in an AI-powered economy comes from combining digital fluency with uniquely human strengths.
Technical skills are growing rapidly, absolutely. But so are skills like leadership, collaboration, mentorship, and project management which help people navigate change and work effectively alongside new technologies.
AI can accelerate work, but people create value through judgment, collaboration, creativity, and responsible decision-making.
Rather than trying to predict every new tool that might emerge—and there will be many—focus on developing a mindset of continuous learning. Build skills that can evolve alongside technology. The individuals who are most successful will be those who are comfortable learning, adapting, and applying new capabilities as work changes.
In Canada retail specifically, we’re seeing growing demand for Python, SQL, data analysis, leadership, collaboration, and project management.
That’s an opportunity for retail employees to build digital and analytical capabilities while continuing to strengthen the customer, teamwork, and leadership skills that remain critical in a people-centered industry.
The competitive edge isn’t what you know today. It’s being willing to keep learning tomorrow.
More from Retail Insider:
