Overcoming the AI Adoption Hurdle in Finance
Integrating artificial intelligence (AI) into core business functions is a growing priority, but making that a reality is often easier said than done. Cameron Kinloch, former CFO of enterprise AI developer Weights & Biases, discovered this firsthand. Despite leading a tech-savvy finance team, Kinloch found it difficult to get her staff to consistently use AI in their daily workflows.
“I could see that people weren’t playing around with it or using it,” Kinloch shared. “There needed to be a bit more top-down push to get people just to even experiment with it.”
Kinloch, who now runs True Vantage Partners, an advisory and fractional CFO firm, isn’t alone in this experience. A recent survey conducted by OneStream revealed that 75% of CFOs oversee their company’s AI strategy. Yet, even as nearly 70% of businesses report adding AI tools, successful implementation remains elusive.
Why Finance Teams Resist AI
Kinloch noticed several barriers preventing her team from embracing AI. One major issue was the perception of AI adoption as an additional burden.
“Learning AI is like taking on a second job,” she said. “It’s really hard to pick up a new tool and learn a different way of working without a top-down mandate and/or time to set aside to come up the learning curve.”
Richard Ranieri, an AI business consultant, agrees. His strategy involves conducting workflow audits to identify bottlenecks and then showing how AI can resolve them. “You find out the company’s biggest pain points,” he explained. “Then show how AI can work hand in hand with people to create a human-first solution that’s simply enhanced by AI.”
The Fear of Failure
Another significant hurdle is the fear of making mistakes with AI. Kinloch recounted a story about a finance team that used ChatGPT to generate commentary for a board deck. The results were unusable, and the immediate reaction was to ban ChatGPT altogether.
“That’s actually part of the learning curve,” Kinloch said. “You’re going to see failures first, then you can figure out how to tweak your usage.”
Misguided Metrics
Adding to the complexity is how companies measure AI success. A widely cited MIT study found that most businesses implementing AI failed to see direct revenue gains. But Ranieri believes tracking revenue is the wrong approach.
“Although their revenue might not have changed instantly, they were able to save 10 hours a week on repetitive tasks,” he said. “That time savings allows employees to focus on higher-value work.”
Kinloch agreed, noting that isolating revenue as a KPI doesn’t capture the incremental benefits AI can bring.
Gamifying AI Adoption
To overcome these challenges, Kinloch introduced a gamified approach to using AI. At monthly meetings, employees demoed different AI use cases, with prizes awarded for the top three. “A little incentivization goes a long way,” she noted.
Ranieri supports this method. “Make it fun,” he said. “Engaging employees in a dialogue and idea exchange definitely helps.”
Training and Change Management Are Crucial
Kinloch observed that junior employees were quicker to adopt AI tools than their more experienced counterparts. This insight led her to emphasize the importance of training and structured onboarding for AI tools.
Ranieri pointed out that many companies rush into AI adoption without preparing their teams. According to a survey by OwlLabs and Pulse, only 38% of companies offer training for employees using AI tools.
“It’s unrealistic to expect people to spend their nights and weekends learning AI,” Kinloch emphasized. “Humans are creatures of habit, so adopting new tools and processes requires deliberate effort and investment.”
Companies that succeed in deploying AI at scale often do so by prioritizing change management. They allocate time for training, encourage experimentation, and foster a culture that tolerates initial failures as part of the learning process.
The Path Forward
As AI continues to evolve, CFOs and business leaders must balance strategic oversight with practical implementation. Encouraging experimentation, offering training, and using incentives can all help teams adopt AI more effectively.
“You have to make it accessible and engaging,” Kinloch said. “That’s how you build a culture that embraces innovation.”
This article is inspired by content from Original Source. It has been rephrased for originality. Images are credited to the original source.