We read through the Q3 earnings call transcripts of 65 publicly traded SaaS companies we follow. We pulled all the quotes and comments regarding AI, and then like a college kid we dumped that 33 pages of data into ChatGPT and asked for a synopsis. Below are the key themes:
They’re pragmatic about AI. AI is no longer a side feature, rather it is becoming the fabric of enterprise software. Companies are embedding AI into their core workflows, building secure agentic platforms, leveraging proprietary data, and experimenting with monetization models. The overall tone is optimistic yet pragmatic, with management teams framing AI as both a transformational shift and a multi-year growth driver rather than an immediate revenue spike.
It’s a feature of processes. AI is being woven directly into everyday processes of the software tools. These processes include document preparation (DocuSign), design (Adobe), collaboration (Asana), customer engagement (Braze), service operations (ServiceTitan, Sprinklr), and developer productivity (GitLab). The companies are taking extra care to highlight trust and context, ensuring outputs are relevant, safe, and actionable.
Agents are coming. A defining theme is the shift toward autonomous agents that act, coordinate, and reason. UiPath, PagerDuty, CrowdStrike, Zscaler, GitLab, and Asana highlight orchestration platforms (e.g., Maestro, AIOps, AI Studio, Charlotte) as the next layer of enterprise software, enabling automation of judgment-based work and multi-system workflows.
Security is an issue. Security vendors underscore the risks of AI from shadow deployments to AI-powered threats. Companies like CrowdStrike, Zscaler, and Rubrik are positioning themselves as enablers of “trusted AI,” securing data flows, models, and agentic identities. Governance and explainability are seen as prerequisites for adoption.
SaaS companies are touting their data. Executives repeatedly stress that data quality and ownership differentiate winners from laggards. Asana’s Work Graph, DocuSign’s agreement data, Braze’s engagement signals, CrowdStrike’s threat graph, and GitLab’s code base exemplify structured, context-rich datasets that make AI outputs valuable and defensible. Without such data, new entrants face steep challenges.
Monetization is not here. Pricing approaches vary widely: some firms test consumption-based metrics (agent minutes, usage tiers), while others treat AI as a premium copilot or upsell. Most acknowledge that pricing is still evolving, and that customer ROI must be demonstrated first. Revenue impact is therefore expected to ramp gradually, with different sectors landing on different models.
The short paragraph synopsis: AI is reshaping software into secure, agent-driven, data-powered platforms. The winners will be those who combine deep workflow integration, trusted governance, proprietary data, and adaptable pricing models. While enthusiasm is high, the financial upside will unfold over the next 12 to 24 months as adoption matures and monetization solidifies.
In our view, current software companies are the absolute best positioned to do interesting things with AI. If you want the full 33 pages of quotes to run your analysis, email us.
Thank you for your readership. See more blogs and SaaS data at blossomstreetventures.com. Email the author at sammy@blossomstreetventures.com.