How widely do employees use AI?

“We are seeing at the moment near 100% adoption with our engineers on AI-based coding tools.”

Balaji KrishnamurthyChief Financial Officer · Executive, Uber

“More than 80% of engineers are now using AI tools.”

Brian CheskyCo-founder and Chief Executive Officer · Executive, Airbnb

“from February to Aug 2026, weekly active users across all agentic offerings across all our employees (engineers & non-engineers) grew 7x, and weekly agentic requests grew 9.4x.”

Uday Kiran MedisettyDistinguished Engineer · Practitioner, Uber

“Today, 83% are weekly active users, including nearly all of GTM (marketing, sales, customer success managers, and technical account managers).”

Sharadh KrishnamurthyEngineering manager, Agent Foundation team · Leader, Stripe

“Today, 99% of our engineers use AI tools. More than 70% of pull requests are attributed to local or cloud agents. And our engineers have built 2,500+ agent skills across the software development lifecycle.”

Praveen Neppalli NagaChief Technology Officer · Executive, Uber

“Glass gives every employee, from engineering to legal, a fully configured AI workspace, helping the company reach 99.5% AI adoption.”

RampPublished by the organization itself (post), no named author

“more than 99% of our engineers use AI coding tools every week, 94% report that AI has made them more productive”

SpotifyPublished by the organization itself (post), no named author

“84% of AI users are now working with agent-style workflows, not just tab completion. Claude Code usage nearly doubled in 2 months (32% → 63%), while IDE-based tools have largely plateaued.”

Praveen Neppalli NagaChief Technology Officer · Executive, Uber

“9 out of 10 Klarna employees (87%) now harness the power of Generative AI in their daily work.”

KlarnaPublished by the organization itself (post), no named author

“Effectively, 100% of our employees are using AI on a daily basis here.”

Rob WitoffHead of platform · Leader, Coinbase

“we haven't done any mandates inside of Airbnb. It's all been organic adoption.”

Christopher SansonProduct Lead, AI Developer Experience · Leader, Airbnb

“For a long time, we had a 'capability overhang': the models were capable but the products didn't fully bring that out. Now, we're seeing an awareness gap. Some people have figured out they can use Codex to monitor Slack, update Airtable, or create onboarding materials. But many others still use it for one task and then discover more uses from teammates via word-of-mouth.”

Akshay NathanEngineering Lead, Productivity team · Leader, OpenAI

“The number one thing that is changing is that people are starting to use threads for much longer, and this longer usage has been a breakthrough. It's surprising to see the sheer length of time that people spend on a thread – even days! They often set a goal and then have the model crank.”

Andrew AmbrosinoLead, Desktop · Leader, OpenAI

“about a quarter of all the pull requests … in any given month were completely or at least largely generated by AI. Then I backtracked this data to the last 12 months. And it turns out that this number is growing really fast. In fact, early last year, fewer than 1% of pull requests had any evidence of being completely … generated.”

Daksh GuptaCo-founder · Executive, Greptile

“the adoption is uneven. We have teams that are very AI-forward and have already transformed their entire workflows and then we have teams that are still experimenting in the earlier acts or have lost confidence”

Eyal BlumSoftware Engineer · Practitioner, Figma

“It's actually our best engineer. … they know where all the pitfalls are. They are … together with like their mental duct tape, all the places that agents are not working well and they're preventing all the really bad stuff from coming in … slower to adapt because they see all the problem …”

Eyal BlumSoftware Engineer · Practitioner, Figma

“Figma has pivoted very strongly from being a traditional tool to an AI-first tool. But in this talk, I'm not … talk about our product, I'm … talk more about our internal organization and how our engineering org has been adopting AI agents.”

Eyal BlumSoftware Engineer · Practitioner, Figma

“because they're seeing … where you're lacking validation, where your tools fail. So, and their feedback is basically the roadmap of how to improve your agent …”

Eyal BlumSoftware Engineer · Practitioner, Figma

“90% of these teams used Kiro, among other internal tools that we have, and what they found was it wasn't about the tools, it was about the way that they worked. The teams that achieved step function improvements intentionally changed the way that they worked, and the other simply kind of sprinkled Kiro and some of the other tools that we have on top of their existing way of working.”

Clare LiguoriSenior Principal Engineer, AWS · Practitioner, Amazon

“Previously, writing code manually was the bottleneck. I find that with an Amazon, we've found the speed of decision making becomes a new bottleneck. … When it used to take nine to 12 months to build a new product, it didn't matter so much in the overall wash of things if it took two months to make the decision to build the product and then two months to approve the launch. But now, those are the bottlenecks. … Often, I find that frontier engineering teams spend more time making decisions than they do writing code.”

Clare LiguoriSenior Principal Engineer, AWS · Practitioner, Amazon

“The second one is slowing down to speed up. In almost every team that was interviewed, they reported that their productivity actually went down, as they intentionally adopted a new way of working. That's counterintuitive, right? You have to do intentional engineering work before you're gonna see that hockey stick curve in productivity improvement.”

Clare LiguoriSenior Principal Engineer, AWS · Practitioner, Amazon

“They watched 50 teams that were totally … distribution of early career folks, mid-career senior engineers, and that worked on existing systems. … And they watched them for the better part of last year, and they found something super interesting. They found that there was a big difference in the productivity gains that they saw between half of the teams and the other half. And in this case, they used a productivity metric of deployment velocity to production. … And they saw that for half of the teams, they achieved less than 3X increase.”

Clare LiguoriSenior Principal Engineer, AWS · Practitioner, Amazon

“we've been trying to build … platform layer around AI tooling at Cloudflare, not just coding … but the stack that makes the tools useful and safe inside a real engineering organization.”

Rajesh BhatiaSenior Director of Engineering, Cloudflare · Leader, Cloudflare

“sometime in November, we started looking and seeing a lot more benefit for some of the models that we were trying to leverage. I think Opus 4.5 maybe was the inflection point where that then generally made it so that it was very easy to see the kind of results we were seeing and expecting.”

Rajesh BhatiaSenior Director of Engineering, Cloudflare · Leader, Cloudflare

“the good part was that we were ready with all the background work that we were doing with respect to the building of the context and building of the right sort of MCP infrastructure internally. So when that became a reality, we started seeing a lot more adoption and because it started helping in the real work that people were doing.”

Rajesh BhatiaSenior Director of Engineering, Cloudflare · Leader, Cloudflare

“We also reduced or canceled contracts with over 1,700 suppliers following our AI adoption and standardization”

KlarnaPublished by the organization itself (regulatory filing), no named author

“Since the beginning of 2025, we've seen a 30% increase in output per engineer, with the majority of that growth coming from the adoption of agentic coding, which saw a big jump in Q4.”

MetaPublished by the organization itself (earnings call), no named author

“a 5% decline in case volume —and 12% fewer cases than forecasted—even while product adoption grew”

SalesforcePublished by the organization itself (post), no named author

“we run around 50,000 builds a week, a number that is only increasing with AI adoption among our engineering teams accelerating commit rates and productivity”

Aditya AnchuriTech lead, Ruby Infra Platform team · Practitioner, Stripe

“every engineer must be able to explain, even if an AI generated the PR, must be able to explain what they built.”

Ahmad Al-DahleChief Technology Officer · Executive, Airbnb

“The big theme of the past months has been that everything is now a coding agent. Whether the visible code is your output or not, agents write your artifacts.”

Andrew AmbrosinoLead, Desktop · Leader, OpenAI

“But most usage is actually much more delegating via tagging… And then more advanced version is really trying to think of it as a teammate that is actually … has memory and can be proactive. And that's just really changed how we operate internally. It's much more like this multiplayer async proactive way than it is most people off in their own CLIs.”

Mike KriegerHead of Anthropic Labs · Leader, Anthropic