Uber has spent the last year quietly pushing beyond the two businesses most people associate it with. There’s ride-hailing, of course, and delivery, but spend time in the app and you’ll now find hotel bookings powered by Expedia, “shop for me” concierge features, and boat rentals in Europe.

Under the hood, so to speak, there’s also a lot happening. Think debit cards for drivers, a data-labeling side hustle for these same earners looking to make more moolah, and a six-month-old business unit called AV Labs, which is developing a fleet of sensor-equipped vehicles that’s separate from Uber’s regular driver network and designed to gather ever-larger amounts of driving data. Uber frames the initiative as a way to strengthen its relationships with autonomous vehicle partners, several of which it also holds equity in, but it sure looks like a hedge, as well. Uber competes directly with some of those same partners, with Waymo chief among them, and owning the data layer gives Uber both some leverage and optionality.

Whether Uber becomes a full-blown “everything app” similar to some Asian super-apps like Grab, remains an open question. But in this conversation, Uber Chief Product Officer Sachin Kansal walks TechCrunch through the company’s financial services ambitions, its increasingly complicated relationship with Waymo, its new AV Labs data operation, and how AI is starting to show up in ways riders and drivers will actually notice.

This interview has been edited for length and clarity.

You unveiled hotels, boat rentals, and more shopping features earlier this year. How did that list get made, and what didn’t make the cut?

Every year our teams are obviously building a lot of stuff, and a subset of that we decide is worth sharing with the world on the biggest stage. This year the theme that we gravitated towards was really travel — 1.5 billion trips on the Uber platform every year actually happen outside of a user’s home city, so we know that travel is something that’s a very common use case for Uber users. Our headline announcement this time was actually introducing hotels on Uber as a partnership with Expedia. But travel is so much more than that — you need rides to go from the airport to the hotel, and you need food. We heard from a lot of our users that a lot of them had stopped using room service and were just using the Uber Eats app. With “shop for me,” the goal was for us to enable you to shop from any local store even if that store is not available on Uber Eats with the entire catalog. Travel really is, in my opinion, the third leg of the stool — we had rides, then we added eats, and now we are adding travel.

Is Uber moving toward offering its own financial services, the way “everything apps” in Asia do?

Financial services for us cuts across multiple different entities — consumers, but also drivers and couriers, and merchants. We have multiple products today focused mostly on drivers and couriers, where we have what we call the Uber Pro card, which they can use as a debit card and transfer all their earnings onto. We are starting to experiment with some of those products for merchants in certain parts of the world right now. As far as consumers are concerned, we’ll see if that makes sense for us in the long term. Right now there is a currency for consumers to use — we call them Uber credits — and this ties to our membership program. On hotels, for example, members get 10% cash back on a $1,000 transaction, that’s $100 back as credit that you can then use on rides and eats.

Would Uber ever offer its own buy now, pay later product?

I’m not sure, because we want to make sure that the experts do what the experts do. We already have announced partnerships with others in the industry who are already providing that service, so that at checkout you have the ability to do that. In terms of our general product strategy, we’re not trying to be everything to everyone.

With boat rentals, in Europe, tapping the tab hands users off to a partner’s own booking flow rather than checking out inside Uber. Is that handoff model a template for what’s coming?

Definitely there are some instances, especially when we are doing something new, for us to rely on our partners, because a two-way integration just does take a lot of time, and in some cases it’s good for us to try before we integrate deeply. In the case of Expedia, we decided it just makes sense to integrate deeply — we built the entire UI on our own in partnership with Expedia. But in some cases it may make sense for us to hand off the rest of the experience to the experts in that field, and if you get great traction, we can always integrate them deeply.

Your Uber One membership product now has 51 million members and accounts for roughly half of bookings. Do you have data showing the cross-sell actually works — that a delivery user later starts taking more rides?

On the delivery side, it takes you two to three orders for you to break even the monthly fee that you pay. As members get more habituated to the program, it’s increasing their frequency within the line of business they are already using. And it’s also leading to more usage of the other sides of the business — we are seeing people who are mobility only also start to use delivery, and people who are delivery only also start to use mobility.

Delivery has been one of the hardest businesses in tech to make profitable. Is Uber Eats still leaning on ride-hailing to stay healthy?

During the early years of Uber Eats it was not profitable yet, but over the last several quarters, Uber Eats has been independently a profitable business for us, and generating a lot of profit.

A story I wrote this spring framed Uber as unexpectedly competing more directly with Airbnb, which is now offering airport transfers through a partner. Do you see it that way? Who are you most focused on?

There’s no dearth of competitors — Lyft in the U.S., Didi and 99 in Latin America, Bolt, Ola around the world, and on delivery, DoorDash, Delivery Hero. But I only spend a very small percentage of my time thinking about that. The bigger percentage of my time, or what keeps me up at night, is are we providing our users all the value that we can provide.

You recently wound down the Waymo pilot in Phoenix while scaling elsewhere. How do you keep the experience coherent when you’re partnering with — and in some cities competing with — the same supplier?

Phoenix was the first city that we launched with Waymo, with about a dozen cars, but our scale launches have been in Austin and Atlanta, where we have hundreds of cars with them. When we recently looked at the Phoenix pilot, we mutually decided that it doesn’t make sense for us to continue. Waymo is an excellent partner of ours, but in many cities they’re also a competitor. We are not in the race to be an L4 autonomy provider — what we are focusing on is laying down the race tracks so we can work with multiple players. We believe in the hybrid network, human drivers as well as autonomous vehicles in the same city, because it allows us to balance demand and supply.

Regarding AV Labs, what can Uber offer autonomy partners that they don’t already have?

We are going to be equipping hundreds of cars with sensors, deployed through our fleet partners, and through that we’ll be collecting millions of miles’ worth of driving data. That really helps with the long-tail problem — you want to see all the edge cases, not just the P95, P99 level. Beyond the data itself, there’s so much know-how from our 10 million earners in terms of how pickups and drop-offs work. We handle 25 million lost items every single year — how do you operationally handle that in the world of autonomy? That’s the kind of operational expertise we can bring.

Is Uber selling driver and rider data to GenAI companies?

I would divide this into two parts. In terms of GenAI companies, we are able to label data for them using our earner base, or through audio collection, and yes, we have commercial relationships with them and we are selling it to them — that’s a part of the business that is new, and we are extremely bullish about it. AV Labs is separate, and we are still figuring those models out for sharing that data with partners. It’s a little early.

Are drivers recording conversations with riders for this data work?

No, no, no — I want to be very clear, there’s no conversation being recorded as part of that while they’re on a ride. When they’re not on a trip, they’re not driving, they’re not delivering, they’re just talking, or they’re listening to a piece of audio and transcribing it. They get paid for doing that, by the way.

Where has AI actually shown up in ways a rider or driver would notice?

If you are an earner on our platform, we have an earner assistant — the number one question on their mind is how do I make more money, and it will say, look, it’s actually pretty light in the South Bay, but you may want to go five miles away where there’s a lot of demand. On the Eats side, there’s a grocery cart assistant where you can say “I want milk, eggs, bread” and it creates the cart very quickly. And on rides, you’re able to use voice to request a ride — say “I’m looking for a ride to the airport, I have six pieces of luggage, six people.”

So a fully agentic Uber — “plan and book my whole trip” — is on the horizon?

I can’t put a date on it, and I can’t tell you exactly what the feature set will be, but I think AI is going to be a huge enabler of that, where I can leave the complexity to the platform and just tell an agent what exactly I want. Easier said than done — we want to make sure we’re not just checking a box by shipping an agent that maybe doesn’t work that well.

As CPO, how do you personally prioritize with so many ideas in flight?

I would say I spend 70% to 80% of my time making sure that our existing products, or the products we are about to launch, are as solid as possible. All the new ideas are like shiny objects — if you have 100 ideas, maybe five of them are good, and those five then need a lot of cultivation and conviction. So probably 20% of the time is on new ideas — including, by the way, I go out and drive and deliver myself, just to see our product from the other side firsthand.

David Beckham’s startup IM8 has taken on $1 billion in funding from General Catalyst’s Customer Value Fund (CVF), the company announced on Tuesday.

CVF doesn’t make standard venture equity investments, but offers what are essentially loans with some non-traditional repayment terms. Startups funded by CVF repay the loan amount along with a fixed, capped the percentage of revenue they generate.

As such, GC isn’t buying stock, and won’t have an ownership stake in IM8. Likewise, the startup’s ownership will not be diluted. As GC previously told TechCrunch, this is an option for startups that have predictable revenue streams and a plan for how more capital will supercharge their growth.

IM8 was co-founded by CEO Danny Yeung, a self-described high-school dropout who founded a health company called Prenetics that went public in 2022. From there he landed in the kinds of circles where he found himself having dinner with David Beckham. That dinner led to IM8, a subsidiary owned by Prenetics that sells a vitamin drink stuffed with compounds linked to longevity that range from açai fruit extract to Coenzyme Q10. Customers buy the drink via subscriptions.

The loan is structured to finance up to 70% of IM8’s customer acquisition costs and, in return, GC receives a capped share of what it calls “reference income.” That’s defined as the revenue generated from those customers “multiplied by a fixed gross-margin assumption.” Once GC has recovered its investment and hits its cap on the revenue share, all subsequent revenue from those customers will go to Prenetics.

As we previously reported, Grammerly also took $1 billion from GC’s CVF in May 2025, just prior to acquiring Superhuman.

Since the large language model (LLM) explosion started, companies have been trying to solve the problem of overflowing inboxes by using AI to categorize emails and draft replies that sound like you. Email client Superhuman is launching a new version of its auto-draft feature that identifies important emails and creates draft replies that sound less robotic.

Superhuman has attempted this in the past with features like instant replies and follow-up auto-drafts. However, a lot of those emails sounded like an overly enthusiastic AI salesperson, and I didn’t use them much. The new version of the auto-draft feature feels different. In the last few days, after gaining access to the beta, I have sent emails with little to no editing for some generated drafts.

The app understands which emails might need replies and drafts a response based on your tone from previous conversations. It also generates two other variations that you might want to send instead.

In my experience using the feature, I saw drafts agreeing to embargoes on a pitch to get more details, or confirming timing for a meeting that I could send with minimal edits. The feature also generated responses to emails asking for an authored post on TechCrunch, saying that I don’t handle that work. (TechCrunch does not accept authored posts.)

The feature is far from perfect, though. By default, it often generated a positive response to a pitch, or agreed to a meeting at a post-midnight time. Thankfully, I could select another response from the other variations quickly and send it away.

The feature learns from your usage and improves responses. For instance, after the midnight meeting debacle, when someone suggested a similar time, the feature generated a draft saying that the timing doesn’t work for me.

I receive thousands of emails every month, partially thanks to AI making first drafts easier for others, like comms and PR professionals. I don’t have the confidence to hand over the reins to AI to handle my inbox completely, but this feature could help me respond to more people when I don’t need to type out long messages.

Users can personalize emails by heading to Settings> Personalization and adding details about themselves and their role, along with adding files or links for more context.

Superhuman’s co-founder, Rahul Vohra, said during the testing phase that 40% of auto-generated drafts were sent within one day, and 60% of those were sent without any manual editing.

Vohra said that earlier features like Instant replies were built from older models like GPT-3.5, which were less intelligent or had a smaller context window. With this new implementation, the company is using an array of models.

“Today, we are using a mixture of models to make this work. The actual writing is done by frontier models from both Anthropic and OpenAI. So we’re applying the maximum amount of intelligence and context to this that we possibly can to make the feature work,” Vohra said.

Last year, Grammarly acquired Superhuman and then rebranded the company as Superhuman. Now, the company is building an assistant called Superhuman Go that spans platforms while carrying context over from one app to another.