Shopify CEO Tobi Lütke publicly shared an internal memo titled “Reflexive AI usage is now a baseline expectation at Shopify” in which he says leveraging artificial intelligence (AI) in daily tasks is now essential for Shopify employees.
This shift underscores that AI is no longer a corporate nice-to-have but an existential necessity for the company’s long-term survival. While many companies have integrated AI into their workflows over the past two years, some large enterprises and non-tech firms still struggle to become truly AI-first despite recognizing its potential.
For Eric Vaughan, CEO of IgniteTech and GFI Software, the transition to being an AI-first company is far more urgent. “When we first realized how important this was… I started using the word existential, and I meant it,” he says. “Companies were going to fail. People were going to lose their positions in the world if they weren’t developing this new skill.”
Vaughan was surprised Shopify hadn’t pursued AI talent development sooner. “I would assume almost all tech companies are far down this line,” he says. “Some people don’t see it as critical, and others are seeing it [the way] I do: existential, literally existential.”
Three approaches have emerged as the best ways to help employees acquire AI skills: self-directed upskilling, certifications and establishing AI centers of excellence. Companies must adopt an approach or blend multiple approaches to stay competitive and meet the needs of their workforce. Organizations that fail to adapt aren’t just falling behind; they’re putting their future at risk.
From curiosity to competency with self-directed AI learning
Self-directed learning is one of the most effective ways to build AI skills. When people are genuinely interested in a topic like AI, they invest their free time exploring and experimenting until they achieve mastery. With YouTube, LinkedIn Learning and other self-study courses, employees can access tutorials and demonstrations that accelerate their learning.
When ChatGPT launched in November 2022, I immediately joined the waitlist. By December, I was spending several hours daily experimenting with it. I eventually found YouTube channels that simplified complex AI concepts and gave tutorials on practical applications of generative AI in business.
This pattern of self-directed exploration, followed by structured learning, is common among early adopters. Forward-thinking leadership teams increasingly recognize that innovation flourishes when employees pursue their AI curiosity independently. By nurturing self-directed learning rather than controlling it, companies can unlock creative implementations they might never achieve through top-down mandates.
“We spent all of 2023 investing in tools and training [and] education. We provided $1,200 [of spending on] literally every employee in the company that could use [it] to license any tools,” Vaughan says. His companies also brought in Ethan Mollick from the Wharton School of the University of Pennsylvania to teach prompt engineering workshops and sponsored internal contests with cash prizes for the best AI implementations. Sustainable skill development happens when people see a direct personal benefit in mastering new tools.
Strategic AI credentialing with certification programs
Encouraging employees to earn AI certifications offers a flexible middle ground between top-down mandates and organic adoption. Audra Nichols, COO of MBO Partners, implemented a three-tiered certification program at her company. “We set up a certification program, but we didn’t demand [participation],” Nichols says. She was pleased that within two months, 23% of employees had completed the first level, with some progressing through all three tiers.
The business case for AI credentials is compelling. A recent LinkedIn Workforce Confidence survey shows that 52% of U.S. workers believe gaining AI skills will help their career advancement. This career-focused motivation is reinforced by economic incentives as indicated by PwC’s 2024 AI Jobs Barometer report. It notes that roles requiring AI skills can command up to a 25% wage premium in specific markets.
Organizations are responding to this talent need, which helps explain why U.S. job postings requiring generative AI skills have risen by more than 1,800% in recent years, according to Deloitte and Lightcast. Despite these market signals and positive incentives for workers to upskill, there’s still a significant shortage of qualified AI talent across sectors from tech to finance to manufacturing.
With this clear business incentive in mind, companies must carefully consider how to structure their certification efforts. Determining the appropriate technical depth is crucial for organizations considering launching certification initiatives. In my opinion, nontechnical employees should focus on certifications that teach highly transferable skills like effective prompt engineering, workflow automation and understanding the practical differences between AI models.
In contrast, technical employees can pursue rigorous artificial intelligence and machine learning certificates to give them complementary skills. Organizations should prioritize certification programs that balance technical knowledge with practical business applications to maximize return on investment.
Building AI centers of excellence
A third strategy for developing AI talent is to create formal structures and allocate protected time for innovation and knowledge sharing. This gives employees time to apply AI tools in real work and helps spread AI capabilities across the organization.
At IgniteTech, Vaughan launched “AI Mondays,” dedicating 20% of the workweek to AI exploration. This initiative institutionalized innovation by allowing employees to build AI skills within their roles without treating it as an extracurricular activity.
For maximum impact, companies can hire AI specialists and embed them across departments, including sales, finance and marketing, so their teams learn how to apply AI to their specific workflows. According to Mohib Yousufani, digital transformation partner at PwC, just putting in generative AI won’t give you results. You have to work across the functions. “AI upskilling is definitely an important element,” he says. But he breaks it into three buckets: first, helping employees do their jobs better and faster; second, transforming processes so some tasks are eliminated entirely; and third, evolving roles upward so employees move from lower-value work to higher-value tasks.
Whether companies build AI centers for excellence, invest in certification programs or empower self-upskilling initiatives, one thing is clear: AI talent development is no longer optional. It’s a competitive edge.
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