We are reviewing Q1 2026 SaaS company earnings calls. So far we’ve gone through 17 which includes: Zeta, Freshworks, Procore, Amplitude, Cloudflare, Datadog, Sprout Social, Waystar, Health Catalyst, Klaviyo, Alkami, Certara, DoubleVerify, Dropbox, Figma, JFrog and Ziprecruiter. 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.
Ziprecruiter CEO — Ian Sigel
AI should be used to accelerate the product roadmap, not cuts. “AI is permeating really every department within our company. It is driving extraordinary efficiencies across the board, which we have not looked at as a cost-saving opportunity as much as we have looked at it as a mechanism by which we can realize and increase our ambition. So if anything, it has accelerated our roadmap as opposed to saved us money.”
LLM Marketing is the next SEO. “The new app went live on ChatGPT and on a percentage basis, the growth of LLMs in general has been impressive as a new traffic source. Overall, LLMs still represent a tiny contributor in the overall mix of where traffic comes from to ZipRecruiter. But it is good to be there at the beginning and to enjoy the ride up with them as they become an ever more popular way for job seekers to look for work.”
-ZipRecruiter CEO Ian Siegel on Q1 2026 earnings call
JFrog CEO — Ben Haim
AI needs software. “As AI generates more code, more models, and more artifacts at a speed no human team can manually govern, the need for a universal platform that tracks provenance, enforces policy, and ensures that only trusted software reaches production becomes existential”
AI Labs can’t replicate many core enterprise needs. “AI labs may offer binary reverse engineering, but they do not replace the need for a universal governance tool and system of record. No single vendor’s tools can govern artifacts across every language, every framework, every cloud, and every AI model provider simultaneously. That universality is what JFrog provides.” A company running Python, Java, and Go microservices across AWS and Azure, pulling from three different AI model providers, needs one governance layer that spans all of it. No AI lab can provide that.
More AI code means the need for more SaaS tools. “AI coding tools are dramatically increasing the rate at which developers pull open-source dependencies. AI-generated code tends to rely heavily on external libraries. As that dependency rate increases, the attack surface for supply chain attacks grows proportionally — and the value of JFrog Curation grows with it.”
Figma CEO — Dylan Fields
AI needs humans. “More design tools are launching, more people are creating, more software is now being built than ever before. And in this world where bits are abundant, what’s scarce is human creativity, actual point of view, care and craft and judgment. This is what makes a product, a company, a campaign cut through the noise.”
The hyper-scalers need software. “Google is a long-time Figma customer. Many of their most iconic products have been designed and built on our platform. As they build the next generation of AI-native products, they’re doubling down on Figma. The team designing agentic Gemini experiences for millions of enterprise customers uses Figma end to end, as their single source of truth, from the earliest concept work all the way through to shipping.”
Institutional knowledge is edge. “We expect more tools to emerge, some complementary and others competitive. Figma focuses on deep understanding of designer workflows and quality, shipping faster than ever. We aim to integrate with complementary tools and maintain strong partnerships”
Dorpbox CEO — Drew Houston
No software company is standing still. “We are evolving from file storage to AI-powered content management. Dash brings content from Dropbox and other cloud applications into a single experience — and we’ve built a context engine that gathers context across content and apps and connects it to AI models for faster and more accurate results”
Existing customer base gives incumbent SaaS a huge headstart on AI product rollouts. “18 million subscribers is our home-field advantage. We are investing heavily in deeply integrating Dash into the core Dropbox experience — and that’s where we have the most leverage.”
But some AI rollouts are not going great. “More than 30% of weekly engaged users used Dash’s AI features again the following week, and more than 50% of monthly engaged users used them again the following month. Retention patterns have been stable as we expand access to new cohorts.”
Opening a new market for old school SaaS. “Protect positions Dropbox in the security and governance conversation for the first time. In the AI era, where employees are sharing sensitive content with external AI tools in ways that IT cannot see or control, content governance becomes a security imperative — and that’s a new budget category for us.”
DoubleVerify CEO — Mark Zagorski
AI opening new markets for incumbent SaaS. “Slop Stopper is now being applied on the measurement side to about 40% of all of our impressions — one of the fastest scaling attach rates we have seen.”
Again on more markets. “AI is driving demand for our solutions in three distinct ways: it is generating more content that requires verification, it is powering more sophisticated fraud that requires detection, and it is enabling more efficient advertising that requires measurement. Every AI development that creates risk for our customers creates opportunity for DoubleVerify”
AI is driving more fraud, fast. “AI-powered bot scheme variants increased 140% in the first quarter of 2026 compared with the first quarter of 2025”
Certara CEO — Jon Resnick
The AI use case is velocity. “AI doesn’t replace biosimulation — it supercharges it. Our models are built on 30 years of validated pharmacokinetic and pharmacodynamic science. An LLM trained on general scientific literature cannot replicate that. What AI can do is make our scientists dramatically more productive, reduce the manual steps between simulation runs, and allow us to explore more of the design space in a fraction of the time. The result is better drug development decisions, faster — and that is what our customers are paying for.”
AI opens a new market. “We want to democratize biosimulation. Today, the most sophisticated quantitative pharmacology is accessible only to large pharmaceutical companies with deep scientific teams. AI-assisted biosimulation can make those capabilities available to biotech startups and smaller organizations that currently cannot afford or staff a full modeling and simulation function”
AI also is forcing a restructuring. “Regulatory writing and medical writing are areas where AI-assisted tools are advancing rapidly. By divesting those businesses, we are reallocating resources to our core biosimulation platform — the part of our business that AI cannot replicate and where our validated scientific models create the most durable competitive advantage.”
Alkami CEO — Alex Shootman
Incumbents are trusted. “Once on the Alkami platform, our investments in service and reliability, the mission-critical nature of our platform, and high switching costs drive gross retention rates 8 to 10 points above typical SaaS companies”
The data moat. We have had 39 client meetings since February where AI has been on the agenda, and every one of those clients has a specific, concrete use case they want to pursue. This is not exploratory conversation anymore. These are financial institutions that have identified workflows they want to automate, compliance processes they want to accelerate, and member experiences they want to improve — and they want to do it on our platform because their data is already here.”
Software side is still wonderful. “Every five years, our clients grow by more than 100% of their original platform investment, with our 2021 through 2023 cohorts spending above 2x their landing ARR and clients 2016 and older spending close to 4x their landing ARR”
Klaviyo CEO — Andrew Bialecki
Data-less AI is useless. “Delivering meaningful customer experiences at scale requires AI grounded in real data. Agents are only as good as the systems beneath them, and we’ve spent 14 years building exactly that foundation”
What AI means for software. “We have entered the era of agents and infrastructure, at least so far as software is concerned.”
Software that is revenue facing always wins. “Unlike most enterprise software, we are focused on revenue generation. If you can help grow top line and profits, there is insatiable appetite to spend more, and we see that constantly.”
AI makes the software customer smarter. “When we think about Composer, ultimately what we are providing is intelligence, delivered in the form factor of tokens. Customers are using it to review who their customers are, the effectiveness of their marketing, and then figure out what to do next. Those sessions are incredibly valuable — generating thousands, even hundreds of thousands of dollars in incremental revenue. We can go much deeper because our agents have access to internal benchmarks and best practices that are not publicly available. That intelligence is an entirely new revenue stream.”
Service providers have a place. “What you can do with Klaviyo and the infrastructure that we built is actually a lot more than our customers and businesses are taking advantage of. Our agencies have always helped close that gap. Now, with our agents — Composer and Customer Agent — agencies are accelerating the adoption of both”
Agent timing. “The company anticipates that AI agents will become standard and ubiquitous within the year, creating a positive feedback loop where agent usage generates data that further improves the underlying infrastructure.”
HealthCatalyst CEO — Ben Albert
More data moat arguments. “We have 18 years of proprietary healthcare improvement data — the largest such repository in the world — and we are building AI models on top of that foundation that no competitor can replicate. AgenTeq is not a generic AI layer. It is intelligence built from the specific clinical, operational, and financial patterns of healthcare delivery at scale.”
Internal dev performance is doubling. “Our initial pilots using new development pods and proprietary AI agents resulted in up to 100% more story points delivered per developer. We are applying the same intelligence we are building for clients to our own engineering operations.”
Generic AI won’t suffice. “Generic AI can tell you what the literature says about reducing readmissions. Our models can tell a specific hospital which interventions have worked for patients with their specific case mix, in their specific market, given their specific operational constraints — because we have seen those patterns play out across hundreds of health systems over 18 years”
AI makes incumbent software even more powerful. “Health Catalyst exists to be the intelligence layer of the American health system. AI makes that mission more achievable than ever — and more urgent than ever.”
Waystar CEO — Matt Hawkins
Some software companies see an expanding TAM with AI. “That shift unlocks a much larger opportunity — the approximately $100 billion in annual revenue cycle labor services performed across the industry today. We believe we are well-positioned to automate a meaningful portion of this labor pool through new AI-powered capability launches like denials, prior authorization, and recoupment. We’re building toward what we believe is the future of this industry: the autonomous revenue cycle platform.”
AI is increasing bookings velocity. “AI traction is accelerating. AI-powered capabilities drove roughly 40% of new bookings in Q1. Our clients leaned into the platform for prevention, automation, and visibility rather than downstream rework.”
AI will lead to tool consolidation. “I was with a CIO of a very large system not long ago — very impressive lady. She said, ‘Matt, can you help us? I currently use more than 12 point solutions just to manage our revenue cycle process.’ And of course, that’s where the platform approach really comes to play.”
SproutSocial — 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. As Klaviyo’s Bialecki put it: “agents are only as good as the systems beneath them.”
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.
It also appears AI is splitting into two camps: i) you’re either using it as an excuse cut headcount because you still have too many employees from covid (Cloudflare, Freshworks, Health Catalyst); or ii) you’re using it to drive the product roadmap faster (ZipRecruiter, Figma, Datadog).
One of the things we didn’t appreciate until now is the TAM expansion argument. AI both protects incumbent software and expands what incumbents can charge for. Traditional services TAMs are becoming markets software can serve with agents (Waystar, Procore, Certera).
Thank you for your readership. See more blogs and SaaS data at blossomstreetventures.com. Email the author at sammy@blossomstreetventures.com.