Common barriers to AI adoption in business

Despite the promise, many companies struggle with AI adoption in business. Greg highlights three major roadblocks:

• Fear and anxiety: Media narratives often frame AI as a job killer, creating resistance among employees and uncertainty among leaders.
• Lack of training: Many employees haven’t received meaningful AI training—if any at all.
• Restrictive data policies: Without access to proprietary company data, AI tools lose much of their utility, particularly for high-value decision-making.

Greg argues that companies often treat AI like traditional software, which he says is a big mistake. “AI is not software,” he said. “It doesn't behave like software. We don't interact with it like software. It’s more like a co-worker or a teammate—sometimes brilliant, sometimes not.”

To overcome these barriers, he urges leaders to reframe how they think about AI tools. Instead of locking down usage or centralizing ownership under IT, companies should empower employees across functions to explore and innovate.

Language-intensive functions are leading the charge

When it comes to identifying early success stories, Greg points to language-intensive roles such as marketing, sales, customer service, and software development. These areas have been quick to adopt AI-powered decision making because the tools can easily slot into existing workflows.

In fact, he calls software engineers the “canaries in the coal mine” for enterprise AI strategy. “Code is just a language. And wherever language is core to the work, AI will go there first,” Greg said. 

At Section, functional AI courses like AI for marketers and AI for finance professionals are among the most popular—underscoring how employees want to apply generative AI directly to their day-to-day tasks.

How to start experimenting with AI in your organization

The key to successful AI transformation? Experimentation—with intention.

Shove encourages leaders to run small, focused pilots across two domains:

• Internal workflows: Use AI to streamline repetitive or high-effort processes like reporting, analysis, or internal communications.
• Customer experience: Prototype AI-powered interfaces, chatbots, or agents that can help reduce friction and elevate customer service.

He likens the approach to drilling for oil: some holes will be dry, but the ones that hit will pay off big. “Forget the AI toys and gimmicks,” Greg said. “Focus on high-value use cases that deliver meaningful business outcomes.”

Who should lead your AI transformation?

When asked who should be responsible for driving AI efforts, Greg says the ideal candidate is a blend of three personas:

1. The technologist – Ensures data integration, tool access, and security
2. The change manager – Drives upskilling and builds a culture of curiosity
3. The business strategist – Knows the workflows, priorities, and opportunities

Greg emphasizes that AI transformation is not just a tech initiative—it’s a strategic, creative, and human process. “The primary challenge isn’t technical,” he siad. “it’s knowing where AI fits, and getting the humans on board.”

How leaders can approach the change with empathy and honesty

Greg closes the conversation with a refreshing take on leadership: be transparent about what you know, what you don’t, and where you're headed.

Some teams may grow. Others may shrink. But the constant should be communication and intentionality.

“Say to your team: We’re going to work with AI, and do it together,” Greg said. “Let’s drive the change instead of playing catch-up.”

For employees, his advice is equally practical: start small, start now. Play with tools like ChatGPT, take a course, and find your own use cases. That familiarity will become your superpower.

The future belongs to the curious

As more organizations explore enterprise AI strategy, Greg believes the most successful ones will be those that lean into learning and creativity—especially from the top.

His final message is simple, but powerful: “Don't put your head in the sand,” he said. “This is coming faster than we realize.”

Episode links: 

• Connect with Greg Shove on LinkedIn
• Connect with Michael Domanic on LinkedIn
• Section School
• Greg’s website
• ​Five practical things a business should do about AI right now: This blog post offers actionable steps for businesses to effectively integrate AI, emphasizing the importance of treating AI as a strategic partner and addressing common adoption challenges.
• Generative AI chatbots: overhyped but still underestimated: This report delves into the current state of AI chatbot adoption in businesses, highlighting usage patterns, productivity impacts, and the need for proactive deployment strategies.
• How to tackle AI adoption to develop a competitive advantage and empower your teams: This webinar discusses strategies for evaluating organizational AI readiness, building trust in AI, and identifying impactful use cases to empower teams and drive competitive advantage.