AI rollout, investment, and ethics? Check. Now it’s time for upskilling in Canada.
McKinsey says organizations have had AI upskilling on their to-do lists for years. But Canadians are prioritizing it now more than ever, as shown by new research on AI adoption from IBM.
Let’s walk through some highlights from the research and how businesses can combat the biggest obstacle to AI adoption: upskilling.
Canadian companies spearheading AI adoption but face barriers
IBM found that 35% of Canadian enterprises already use AI, while 48% are “exploring it.” But what does the money say? AI deployment (and the investment required for it) has gone up from 34% to 37% in Canada.
Still, the fastest adopting country to AI is least likely to accelerate based on these profound obstacles: reskilling and workforce development (42%) and research and development (41%).
Skill shortage a top overall barrier to AI adoption
Limited AI skills are the biggest barrier for 41% of organizations.
About 20% of businesses have limited employees with AI and automation skills, yet only a quarter are actually investing in upskilling them. They might rely on new hires, yet IBM also found that 17% of companies can’t find skills to fill the gap.
But it’s not a matter of want. Upskilling is tricky when the content and guidelines around AI continue to change, and when AI keeps evolving at such a rapid rate.
Tips to upskill employees
That guest speaker at your employee engagement seminar just won’t cut it when it comes to upskilling your employees. They need hands-on experience that you can deliver via:
- Offer educational leaves: Certificate programs and even shorter boot camps can give your employees both theoretical and practical experience with AI. You might also establish a unique learning and development plan for each employee.
- Prioritize job shadowing: It’s one thing to read about AI and a whole other to get your hands on it. Look to your own or other departments for your employees to watch their more experienced peers handle AI.
- Leverage apprenticeships: You can combine paid training with mentorship to create your own internal apprenticeship model. Despite the high initial price tag, Google asserts it to be one of the most efficient returns on investment.
- Compensate accordingly: Incentivize upskilling with promotions in title and compensation.
Ethics remain a top priority in AI adoption
Slow AI adoption isn’t just due to a lack of technical expertise or difficulty upskilling.
On the positive side, the vast majority of Canadian IT professionals see consumers are most likely to buy from them if they have transparent and ethical AI practices (82% strongly or somewhat agree).
Read more about the study here.
