Walking the Talk: Communicating a Clear AI Vision Correlates with Outsized Financial Performance 

The Data

1. 1

   In our analysis of earnings calls from 150 companies, 86% are talking about AI, 24% are talking about it within supply chain, and just 12% are talking about the impact of AI on performance metrics.

2. 2

   The top 20 companies discussing AI most frequently have seen higher revenue growth (+21% as compared to their peers), margin growth (+159pp), were more accurate against EPS estimates (2.76x), and saw particularly strong stock performance (23% greater than the market average).

Talking the AI Talk 

There’s a lot of data and discussion around AI, from achieving ROI to tech spend, cutting waste to getting executive buy-in. With all the talk and implementation, we wanted to zoom in on the link between them. How does communicating AI strategy – the frequency, quality, and depth – correlate with implementation and, in turn, performance metrics?  

We analyzed earnings calls for 150 companies to see how often AI was coming up and how deeply companies were talking about their strategy. Five out six companies discussed AI, but only about a quarter talked about its impact on supply chain. Fewer still talked about results – just one in eight companies talked about the impact AI was having on performance. 

Looking at the bigger picture and the 86%, we found that AI communications correlate with increased revenue growth and margin growth, greater EPS accuracy, and even stock price growth. The top 20 companies discussing AI most frequently have seen higher revenue growth (+21% as compared to their peers), margin growth (+159pp), were more accurate against EPS estimates (2.76x), and saw particularly strong stock performance (23% greater than the market average). 

Though our data shows a correlation between overt and clear communication around AI and improved performance, it’s clearly not just a case of speaking success into existence. Our take is that companies discussing their AI efforts in earnings calls with specificity are more likely to have an enterprise-wide AI deployment strategy and have simplified their problem statements through strategic prioritization. But you can’t close the say-do gap without first saying something.  

Who’s Saying What 

Building confidence in investors, your board, or even your CEO requires a complete vision, tangible results, and specificity to bring the story to life. Here are a few examples from recent earning calls: 

• Cardinal Health, Q2 2024 earnings call: CEO Jason Hollar discussed the company’s “first-to-market clinically integrated supply chain, the Cardinal Health InteLogix platform. This innovative solution leverages artificial intelligence and machine learning through the Palantir Foundry platform to help providers reduce costs, optimize drug inventories, and generate actionable insights to simplify and streamline medication supply.” 
• Target, Q1 2024 earnings call: Target’s EVP and Chief Growth Officer detailed AI-driven improvements in personalization: "Newly developed generative AI and personalization capabilities are expanding the scope and reach of what we can offer our guests... We recently engaged in a pilot with one of our biggest vendors to test our latest personalization capabilities with guests shopping our personal care categories. We're very encouraged by early test results, which showed a nearly 3x lift in conversion rates from personalized promotions versus mass offers, including higher sales lift across the rest of the category...” 

The Takeaway 

The first step to seeing AI ROI is crystallizing a clear vision for it – clear enough that the vision shows up regularly, consistently, and in depth, reaching executive communications. This means proper prioritization within an enterprise-wide roadmap and clear targets for tangible results. While it’s interesting to note the correlations with financial performance metrics, it’s no surprise that companies that can articulate their AI vision better are performing well in the market.  The hype is still real – the results are still coming – but the strong communicators have an early lead. 

To see a different data cut or to dig deeper into this topic, reach out to our Head of Research Analytics, Cody Stack, at Cody.Stack@zero100.com. 

Methodology 

Zero100’s proprietary data and analytics are a combined effort between our data scientists and research analysts. We provide data-first insights matched with our own research-backed points of view and bring this analysis to life via real-world case examples being led by supply chain practitioners today.     

For this study, we analyzed the most recent earnings calls for 150 B2B and B2C companies.  

Further Reading  

• The AI Advantage: Winning Executive Buy-In
• Data Insight: Tech Spend Set to Keep Rising as Digital Investment Delivers Business Value   
• The Signal: AI Time to Value: Three Steps to Achieve Results