Bill Patterson, Salesforce EVP of Corporate Strategy, shares candid insights on the gap between AI tool adoption and tangible business value, underscoring the company’s approach to guiding enterprises through new AI economics and dismissing the ‘SaaSpocalypse’ narrative.
- CFOs are cautious as AI use grows but yield lags
- Tokenomics offers potential but remains nascent
- Salesforce focuses on outcomes over token consumption
What happened
Bill Patterson, EVP of Corporate Strategy at Salesforce, acknowledges a common sentiment among CFOs who are investing in AI technologies but remain uncertain whether these investments will pay off. Despite impressive adoption rates of AI tools that enhance content creation, coding, and design, many organizations struggle to convert this usage into measurable business benefits across teams and enterprises.
Salesforce is witnessing a rise in interest around tokenomics and concepts like token-maxxing, which aim to optimize AI usage costs. However, Patterson notes that these ideas are still evolving, with early indicators showing that burning more tokens does not necessarily translate into better business results or product output.
Why it matters
The disconnect between AI tool usage and actual business yield has significant implications for enterprises deciding how to invest in AI. High spending on AI without clear returns is unsustainable, driving demand for more strategic guidance and flexible consumption-based pricing models. Salesforce’s introduction of pay-as-you-go offerings reflects this shift, helping customers avoid costly commitments on unproven technology.
Patterson emphasizes that Salesforce differentiates itself by focusing on outcomes rather than raw usage metrics. Using the example of Piper, Salesforce’s AI sales agent, he illustrates how value is measured by business results like lead closure rates rather than tokens consumed, marking a shift towards outcome-driven AI adoption.
What to watch next
Moving forward, Salesforce aims to act as a navigator for enterprises attempting to harness AI effectively while managing risks and expenses. The company’s strategic push to open its platform in a ‘‘headless’ manner is designed to foster innovation by enabling richer interactions with data and AI capabilities, ultimately embedding AI more ubiquitously in business processes.
Market observers should watch how tokenomics matures and whether it can deliver clear frameworks for AI cost efficiency and value creation. Patterson’s optimistic outlook on the future of enterprise AI counters the ‘‘SaaSpocalypse’’ fears circulating in the industry, suggesting that AI will become more integral and beneficial to enterprise workflows over the next few years.