We reviewed the Q1 2026 earnings calls for Zeta, Freshworks, Procore, Amplitude, Cloudflare, Datadog, and now Sprout Social. Below are the most salient quotes from their respective CEO’s about AI. We will be updating this blog frequently as we get through each Q1 earnings call for all the publicly traded software companies. At the end are key take-aways.
SproutSocia — CEO Justyn Howard
On why Sprout Social is doing a $50mm share repurchase: “We have a meaningful disconnect between current valuation levels and the long-term value we expect to create….We are seeing customers making longer-term commitments to Sprout with multiyear contracts now representing nearly half of our contract mix, up from about a third two years ago. This reflects growing confidence in Sprout as a strategic platform.”
Cloudflare — CEO Matt Prince
They did a 20% RIF while achieving 34% YOYG. “Just because you are fit does not mean you cannot get fitter. Over the last six months especially, the productivity gains from the people directly talking to customers and directly creating code have been incredible, and a lot of the support roles behind them are not going to be the roles that drive companies going forward.”
On internal use of AI: “internal AI usage increased more than 600% in a single quarter….97% of Cloudflare’s R&D employees use AI coding tools….with productivity gains of “two, ten, even 100 times”
Software is the backbone of AI: “Cloudflare is now processing hundreds of billions of agentic requests per month” according to their latest earnings call. Every AI agent calling a tool, querying an API, or taking an action on the internet is generating a request that may pass through Cloudflare’s network.
Datadog — CEO Olivier Pomel
AI training is becoming production infrastructure. “AI training was very new a couple of years ago. It was something that was only done by very few companies, and it was, in a way, very artisanal — it was not a production workload. It was something that researchers were building, and it was very one-off. And now it’s turning into production. It’s turning into something that many more companies are doing. It’s scaling by orders of magnitude, and it’s becoming something that has to be on all the time, reliable — and every minute you lose, or every failure you have in your training round, is a week you give away to the competition.”
The dual strategy. “We’re talking about our AI efforts in two buckets: AI for Datadog and Datadog for AI. AI for Datadog — these are AI products and capabilities that make the Datadog platform better and more useful for our customers. Datadog for AI — this includes Datadog capabilities that deliver end-to-end observability and security across the AI stack.”
Hours to seconds. “We’ve seen Bits AI Security Analyst reduce investigations that could take hours to as little as 30 seconds.”
The cloud still matters. “We showed broad-based acceleration of revenue growth across cohorts, including both our AI and non-AI customers. Non-AI customer revenue growth accelerated again this quarter — we think this is a sign of strong continued cloud migration, greater adoption of our products, and customers of all kinds accelerating their use of AI.”
Amplitude
The most honest confession from any CEO we’ve seen. “It is much more important to get there with a lot of speed for a lot of different reasons than it is to say, ‘Hey, let’s try to protect some existing thing we have.’ The existing thing we have, frankly, isn’t valued much.”
The goal of Amplitude’s AI. “We’re entering a new era of analytics — one where AI can monitor your product around the clock, and free up your team to focus on improving the experience. The real advantage is how quickly a team can learn, iterate, improve, and automate. Agentic analytics is the key.”
AI generated code means you need more software. “AI has dramatically lowered the barrier to building and shipping software, boosting productivity for experienced engineers and enabling non-traditional roles to become AI builders. While teams can generate more code than ever before, the software development life cycle remains bottlenecked in many other places. AI builders are generating code faster than they can understand its impact. The challenge is now evaluating code before it’s released, tracking what’s working after release, knowing when you need to roll things back, and turning behavioral signals into what to build next.”
On their own coding. “Over 90% of the code our team ships today is written by AI.”
On the internal adoption of AI. “We paused normal work across the entire company so that every function could build and ship AI-powered workflows to reimagine their daily jobs and functions. The team shipped hundreds of amazing demos, including automatically creating custom demo websites per customer, automating part of the quarter close process, and automating how we create new creative assets in marketing.”
Gross margin is compressing, but that means…“The inference cost growth is a leading indicator of how much our customers are actually using our AI tools. That is what we want.”
Zeta
AI’s impact on the market now. “AI is no longer a feature. It is driving a replacement cycle where enterprises are demanding fewer systems, measurable results, and applied intelligence that works today.”
We can’t just talk about AI anymore. “Customers want to invest in applied AI, not road map AI.”
The data and software flywheel. “As adoption increases, Athena learns from more data, outcomes improve and usage deepens, driving ARPU expansion and ultimately reinforcing the same flywheel that has powered our growth. That flywheel is powered by more than just Zeta’s AI models. It’s driven by the data and infrastructure behind them.”
The data moat. “Zeta SuperGraph, our proprietary identity and intelligence graph, unifies data across the enterprise and enables a complete deterministic view of the consumer that we believe is difficult to replicate at scale.”
Freshworks
The AI conversation is about impact. “AI is not causing sales delays — it has become a core requirement in nearly all large enterprise deal discussions. Customers are not asking whether we have AI. They are asking which AI, how it works, and what outcomes it delivers. Freshworks is winning those conversations because Freddy AI is embedded in the platform, not bolted on.”
AI is the last thing listed. “We had our biggest deal ever — a large nutrition company that was a 10-year customer of one of our competitors — that is moving over to us for all the reasons we have discussed: enterprise-grade scale, much faster time to value, easier to manage the platform, and AI capabilities.”
Procore
A big advantage of the incumbents. “Procore AI is a reasoning engine purpose-built for construction. It understands the language and logic of the project — how an RFI connects to a submittal, how a submittal connects to a drawing, how a change order gets approved. It works as a multi-step system that holds context across multiple steps. It doesn’t just answer a question — it understands the thread.”
The data moat. “This data and context can only be accessed within a system of record and collaboration like Procore. Building on our flagship system of collaboration with nearly 3 million active users and a massive proprietary dynamic data set, Procore AI can deliver outcomes simply not possible with traditional software.”
A real ROI use case. “By leveraging Procore AI, Crest has taken a manual process that could span weeks of effort down to an automation that can take as little as 20 minutes. This isn’t just an incremental improvement in speed. It is a fundamental shift in their competitive advantage.”
There is more to come. “It is still early. As we continue to develop Procore AI, going deeper into our proprietary data and broader across project types, the reasoning engine will only become more capable. We expect our solution to continue to improve with every layer we unlock, and we have a long runway ahead of us.”
Our big take-aways so far: AI conversations in enterprise software are now about ROI and performance. Zeta’s Steinberg put it well when he said “customers want to invest in applied AI, not road map AI”. The companies winning are winning because their AI sits on top of proprietary data and workflow context that no model can replicate from scratch. The model is the commodity; the data and the workflow layer are the moat.
CEOs are also being very candid about AI’s impact on their own organizations. Cloudflare did a 20% workforce reduction on the same day it reported 34% revenue growth. Amplitude’s CEO said “the existing thing we have, frankly, isn’t valued much” and paused the entire company to rebuild workflows from scratch. Freshworks attributed its 11% headcount reduction directly to AI coding productivity, with over half of all code now AI-originated. Software companies are positioning for a structurally lower cost base at the same time they are building higher-value AI revenue. We believe that this combination will ultimately justify premium multiples for the enterprise software category, well above where they are today.
Thank you for your readership. See more blogs and SaaS data at blossomstreetventures.com. Email the author at sammy@blossomstreetventures.com.