Aurora Innovation, Inc. (NASDAQ:AUR) Q1 2024 Earnings Call Transcript

Aurora Innovation, Inc. (NASDAQ:AUR) Q1 2024 Earnings Call Transcript May 8, 2024

Aurora Innovation, Inc. beats earnings expectations. Reported EPS is $-0.11, expectations were $-0.14.

Operator: Greetings, and welcome to the Aurora First Quarter 2024 Business Review Call. [Operator Instructions] As a reminder, this conference is being recorded. It is now my pleasure to introduce your host, Stacy Feit, Vice President, Investor Relations. Thank you. You may begin.

Stacy Feit: Thank you, Camille. Good afternoon, everyone, and welcome to our first quarter 2024 business review call. We announced our results earlier this afternoon. Our shareholder letter and a presentation to accompany this call are available on our Investor Relations website at ir.aurora.tech. The shareholder letter was also furnished with our Form 8-K filed today with the SEC. On the call with me today are Chris Urmson, Co-Founder and CEO; and Maday, CFO. Chris will provide an update on the progress we have made across the key pillars of our business, and David will recap our first quarter financial results. We will then open the call to Q&A. A recording of this conference call will be available on our Investor Relations website at ir.aurora.tech shortly after this call has ended.

I’d like to take this opportunity to remind you that during the call, we will be making forward-looking statements. This includes statements relating to the achievement of certain milestones around and realization of the potential benefits of the development, manufacturing, scaling and commercialization of the order driver and related services, market opportunity and profitability of our products and services, our anticipated time frame, the expected performance of our business and potential opportunities with partners and customers, expected contract commitments from customers for our products and services, regulatory tailwinds and framework in which we operate, expect the cash runway and overall future prospects. These statements are subject to known and unknown risks and uncertainties that could cause actual results to differ materially from those projected or implied during this call.

In particular, those described in the risk factors included in our annual report on Form 10-K for the year ended December 31, 2023, filed with the SEC as well as the current uncertainty and unpredictability in our business, the markets and economies. Additional information will also be set forth in our quarterly report on Form 10-Q for the quarter ended March 31, 2024. You should not rely on our forward-looking statements as predictions of future events. All forward-looking statements that we make on this call are based on assumptions and beliefs as of the date hereof, and Aurora disclaims any obligation to update any forward-looking statements, except as required by law. Our discussion today may include non-GAAP financial measures. These non-GAAP measures should be considered in addition to and not a substitute for or in isolation from our GAAP results.

Information regarding our non-GAAP financial results, including a reconciliation of our historical GAAP to non-GAAP results may be found in our shareholder letter, which was furnished with our Form 8-K filed today with the SEC and may also be found on our Investor Relations website. With that, I’ll now turn the call over to Chris.

Christopher Urmson: Thank you, Stacy. 2024 is off to a strong start as we purposefully drive toward our planned commercial launch at the end of the year and the subsequent scaling of our business. The team’s commitment to our mission to deliver the benefits of self-driving technology safely, quickly and broadly, remains steadfast and is fueling some of the highest levels of employee engagement we’ve seen as a public company. This enthusiasm drove our continued progress in the quarter, including improving the Aurora Driver’s autonomy performance, advancing our launch Lane safety case and continuing to execute with financial discipline. We recently hosted an Analyst and Investor Day where we demonstrated the maturity of our ecosystem, the depth of our partnerships and enthusiasm of our customers.

These factors support our expectations that we can drive rapid, capital-efficient revenue growth, high gross margins and most importantly, mature into a self-sustaining company. We gave attendees a chance to experience driverless truck rights and a first look at how our driverless trucks navigated advanced road scenarios at our test track. Page 4 through 7 of our presentation include examples of the exceptional performance of the Aurora Driver without vehicle operators in these highly demanding situations, including handling interactions with aggressive drivers, avoiding dangerous debris, responding to pedestrians who unexpectedly entered the path of the vehicle and navigating tire blowouts. In the first video, we see the power of the rare driver as it monitors an aggressive driver approaching at high speed.

The aggressive driver accelerates to overtake the truck, merges just feet in front of the Aurora Driver without signaling and slam on the brakes in order to exit the roadway. The Aurora Driver perceives the dangerous driving behavior, anticipates the potential for an aggressive cut-in and safely breaks to avoid collision. It doesn’t break a sweat and continues on its journey. The second video showcases the Aurora Driver, navigating a common yet demanding and dangerous situation, evading road debris, including tires and trash cans. It also expertly avoids a mattress and suitcase that have fallen out of the bed of a pickup truck just ahead. The or driver properly identifies these hazards and swiftly execute safe but rapid lane changes to avoid them.

The third video illustrates a potentially catastrophic scenario and obscured pedestrian unexpectedly entering the roadway. As Aurora Driver approaches, the pedestrian steps in front of the oncoming truck. In both variations of the scenario, the Aurora Driver identifies the pedestrian and act quickly in the subsequent moments, either merging when space is available or rapidly decelerating to come to a complete stop when other vehicles are traveling adjacent to the truck, preventing a safe lane change. The final video showcases the Aurora Driver responding to a particularly severe issue, a tire blowout. In this scenario, we place a spike strip in the path of the truck. The Aurora Driver promptly recognizes that the tier has blown and brings the truck to a safe stop on the shoulder.

There Aurora Driver impressed performance in scenarios like these reinforces our belief in the safety advantages our technology can provide. At its core, the Aurora Driver is all about making transportation safer and more efficient. It does not lose focus, get tired or become impaired. We believe it not only replicates the behavior of the most proficient drivers, it also redefines performance with superhuman capabilities. The system can simultaneously perceive 360 degrees of the operating environment and anticipate and respond to seemingly unpredictable road users’ behavior with the support of advanced modeling. We continue to lead the industry with our commitment to safety and transparency. To provide the safety of our — to prove the safety of our product and earn public trust, we utilize a safety case, which is a comprehensive evidence-based approach to confirming that our self-driving vehicles are acceptably safe to operate on public roads.

We quantify our progress toward closing our Dallas and Houston launch Lane safety case through the Autonomy Readiness measure or ARM, which is a weighted measure of completeness across all claims of the safety case for our launch late. We’re the only company in the industry that has provided this level of transparency. As of mid-April of this year, ARM was 95%, which is a significant achievement. As we said when we introduced the ARM, approximately 95% is related to claims specific to the Aurora Driver. This continued advancement underscores the progress we have made on final validation in preparation for commercial launch. As we said when we introduced the ARM, approximately 95% is related most directly to claims specific to the Aurora Driver, and this is a significant achievement.

While we will continue to collect evidence throughout the year, we expect final validation and closure of the remaining safety case claims to be completed later this year with our anticipated launch platform. A large portion of the safety case work is ensuring we have properly defined, validated and verified the features that make up the Aurora Driver. I’m going to take a few moments to outline how we do this work. On Page 9 of the presentation, we lay out this process. When we were initially developing the road driver, we defined how the system should behave. As an example, the Aurora Driver is designed to yield to and, of course, most importantly, avoid collisions with pedestrians. Given that requirement, we developed an initial set of tests to help us develop the algorithm.

We also labeled examples of the desired behaviors and use that data to train our machine learning models to enable the Aurora Driver to execute an appropriate duty of care in similar scenarios. Once the future passes these initial tests, we begin to have confidence that the Aurora Driver is capable of operating safely on the road. But it’s important that we invest the energy to refine and validate the performance of the future, which are critical steps in closing our safety case. To support our validation and refinement efforts, we wrote detectors that can scan through approximately 100,000 miles of expert human driving to automatically extract data and support validation. We analyze this data to ensure that we’re covering common everyday experiences and interesting and challenging parts of the interaction space.

As an aside, many of you have heard of reinforcement learning from human feedback or RLHF, it’s a critical enabler of the advancements in large language models. Our approach to using data from our human expert drivers to refine the performance of the machine learned elements of the Aurora Driver system takes a similar approach. Our human-driven data can be automatically transformed into test. We then supplement these tests with additional synthetic tests by varying parameters, for example, with pedestrians in different locations or moving at different speeds to complete our test coverage. Finally, we develop a small number of tests that we run end-to-end with a physical truck and test track to ground our simulations in reality. We exercised this full process to validate the driverless capabilities showcased at our Analyst and Investor Day and attendee saw the effectiveness of this development process firsthand.

As we measure our progress towards commercial launch, we look at indicators for safety and usefulness. A key metric we use to assess the Aurora Driver’s performance or usefulness is the autonomy performance indicator or API. This indicator penalizes the use of on-site support, which will be the most expensive support provided. With the achievement of an aggregate API of 99% last quarter, we are now focused on driving up the percentage of commercial loads that do not require any on-site support, which we refer to as 100% API loads. As a reminder, we do not anticipate aggregate API will ever reach 100% even at launch because certain situations like flat tires will always require on-site support. However, we do believe the percentage of 100% API loads will be a strong indicator of our progress toward commercial launch.

During the first quarter, 75% of the commercial loads in the launch lane had 100% API, reflecting a 13-point improvement from the prior quarter and meaningful progress toward our commercial launch expectation of roughly 90%. With the recent introduction of intermodal trailers into our pilot operations, we’re now including these loads in the API measure, underscoring our increasing readiness for expansion beyond 53-foot drive-ins following our planned commercial launch. The increasing confidence in our technology and progress is accelerating our demand building efforts. We have now secured multiyear contractual commitments on volume and pricing from multiple customers with a mechanism to transition to driverless operations, and we are in active negotiation with additional customers.

As we prepare for commercial launch, we continue to autonomously haul freight for all of our pilot customers, including FedEx, Werner, Schneider, Bespak, Uber Freight and others. We’re now scheduling about 120 commercial loads per week or triple the commercial volume we were executing a year ago. For the rest of the year, we’re focusing on finalizing contractual commitments through 2025 and increasing load capacity strategically to support operational readiness and customer expansion. Cumulative to date, through the end of April, we have autonomously delivered under the supervision of vehicle operators, 5,450 loads, driving approximately 1.5 million commercial miles with nearly 100% on-time performance for our pilot customers. Moving to the regulatory environment.

Under existing law and regulation, autonomous vehicles can be deployed in the vast majority of states, including our Texas launch market. Texas does not currently require additional regulatory steps and is in an ideal state for launch of the Aurora Driver given its high freight volumes and advanced transportation infrastructure. We’re also continuing to see steady advancement of autonomous vehicle legislation across the United States. Since our fourth quarter business review, South Dakota and Kentucky have furthered this momentum by enacting autonomous vehicle legislation into law. Earning Public Trust is also vital in a safety critical industry and requires a locally focused effort centered on transparent engagement. Earlier today, we hosted our first community event at Palmer high school in Texas, where we shared the benefits of our technology and the economic opportunities Aurora’s bringing to the region.

We look forward to engaging with additional communities along the I-45 corridor in preparation for our commercial launch. Looking further ahead, we believe Aurora is the only company positioned to commercialize autonomous trucking at scale. We have established OEM and Tier 1 partnerships with Volvo Trucks, PACCAR and Continental that are unmatched in the industry and support a freight ecosystem with aligned incentives to drive growth for years to come. As we’ve said before, we believe deep integration with OEMs and suppliers is absolutely critical to bringing a safe and commercially viable driverless trucking product to market at scale. Our goal is to operate at significant scale and build a valuable business for the long term. That’s why we’ve partnered with Volvo Trucks and PACCAR.

We’re working together to design autonomy enabled trucks with the redundant components necessary for safe driverless operations and importantly, with plans to manufacture these platforms at scale. We also have a long-term exclusive partnership with Continental to jointly develop, manufacture and service future generations of the Aurora Driver hardware. This partnership gives us a path to deploy autonomous trucks at scale with a cost structure in place intended to support our long-term profitability. We also recently engaged Fabrinet for the manufacturing assembly of our next-generation Aurora Driver hardware kit, which we plan to introduce in 2025 to support our initial scaling ambitions before Continental start of production. This kit brings exciting performance gains.

And importantly, we expect it to drive a step function reduction in our hardware costs, which is a critical element on our path to scale and self-funding. I can’t be prouder of the tremendous progress we’re making while maintaining safety as our North Star. We will continue to work responsibly and purposefully to ready our technology for commercial launch and longer-term deployment at scale. Our path has never been clearer, and we are convinced that Aurora is going to create immense value for society, our partners, our customers and, of course, our shareholders. With that, I’ll now pass it over to Dave, who will review our financial results.

David Maday: Thank you, Chris. Let’s discuss our financial results. We have provided a summary on Page 12 of the slide deck for reference. During the first quarter of 2024, we continue to demonstrate strong fiscal discipline while executing toward our planned commercial launch. First quarter 2024 operating expenses, including stock-based compensation, totaled $193 million. Excluding stock-based compensation, operating expenses were $157 million. Within operating expenses, our R&D expenses, excluding stock-based compensation, totaled $135 million. This amount reflects $565,000 in pilot revenue, which nearly doubled year-over-year and which we continue to record as a contra R&D expense. SG&A expenses, excluding stock-based compensation, were $22 million.

We used approximately $150 million in operating cash during the first quarter of 2024. Note, this included approximately $9 million in prepayments for hardware components to support commercial launch. Capital expenditures totaled $8 million. The total cash spend was below our target, reflecting our continued commitment to fiscal prudence. In 2024, we continue to expect quarterly cash use of $175 million to $185 million on average, which reflects an increase in capital expenditures relative to 2023 as we prepare for commercial launch. Similar to the second quarter of 2023, we expect second quarter 2024 cash spend to be above this range due to the payments associated with our 2023 annual incentive compensation program. We ended the first quarter with a very strong balance sheet, including $1.2 billion in cash and short-term and long-term investments.

Given efficiencies we found in the business that have translated to tangible and recurring cost savings, we now expect this liquidity to support our planned commercial launch and fund our operations into the fourth quarter of 2025. With that, we’ll now open the call to Q&A.

Q&A Session

Operator: [Operator Instructions] Our first question comes from the line of George Gianarikas with Canaccord Genuity.

George Gianarikas: I’d like to ask a regulatory question. There’s an increasingly vociferous debate around the merits of full neural network approach versus a hybrid approach to autonomy. And I think it’s safe to say that you endorse more of a hybrid approach. Now do you think that your approach lends itself to more transparency for regulators? Have you experienced any regulators going under the hood and maybe scrutinizing some of your code and the models that you’re using? And do you think that’s going to potentially become a necessary part of the regulatory mandate…

Christopher Urmson: Yes. Thank you, George. Great question. As you’re probably aware, as you laid out, we are very much taking a hybrid approach here. And we — it’s kind of AI first, but it’s very much incorporates ideas from kind of both the modern machine learning world and also some of the earlier ideas in artificial intelligence that we can bring to bear here. For us, I think your observation is spot on that as we think about engaging with regulators, the burden of being able to help explain to them why the system is behaving the way it is and importantly, at some point in the future, why you fixed an issue or how you fix an issue and that you have confidence that those dress, I think will be very difficult. And the way to think about this is I don’t need to learn that the vehicle shouldn’t drive off the road, right, that we have the ability to express that explicitly.

And that allows us to much more readily convince ourselves and ultimately, others who care like our partners and regulators that we’re actually meeting that objective. And similarly, there are examples of scenarios like vehicles driving the wrong way down the freeway, where you may not actually have enough data support to learn a pure AI long for that. And we kind of know what the right behavior should be. And so by being explicit and encoding that where appropriate, it allows us to get the best of both, right? We get to lean into all the wonderful powers of modern AI. — while also reducing the risk of hallucinations by be able to make strong statements about what will and won’t happen on the road and by managing computation in places where there are more efficient ways to implement an algorithm.

George Gianarikas: And maybe as a nonrelated follow-up, how does the topsy-turvy macro environment impact your ability to finalize contractual agreements with customers in 2025? Is it a positive or a negative as you kind of look to solidify your business to next year?

Christopher Urmson: Dave, do you want to speak to that?

David Maday: Yes, sure. Thanks, George. I appreciate the question. I think — as we continue to work with our partners, one of the things that we’ve continued to focus on is just being patient and working with them and understanding the challenges that they’re facing, right? And so I agree, it’s been a little bit bumpy and the macro environment has a lot of challenges for the traditional industry. I think all of our partners view us as a partner that can help address some of the challenges and provide a long-term credible solution that makes a more efficient transportation system. And then with that, as we continue to work with our customers, we found it actually pretty productive. We’ve been able to work with our customers.

We’re in the process of completing contracts for all of them. But it’s good to actually go through challenging times so that we’ve kind of addressed and learned and understand how we’re going to operate during those times as well as like during like the best optimal scenario overall. So I think in short, it hasn’t hurt us at all. And it goes with the learning approach of adoption of a new technology that’s really going to make a system more efficient in the long run. So I think it’s been pretty helpful overall.

Christopher Urmson: And the thing I’d add to that is the engagements we have with our partners are strategic in nature that these are all folks who’ve been in the industry understand there’s a cyclic nature to freight to the industry. And they recognize that we’re not going to solve their next week problem but that we are going to have a potentially transformational benefit to their business over the longer term. And so we’re seeing continued engagement and continued constructive conversations. And we’ve been able to get the contracts in place for — that we expect we need towards 2025.

Operator: Next question comes from the line of Mark Delaney with Goldman Sachs.

Mark Delaney: First, just hoping to better understand what you think are the biggest hurdles left before the commercial launch at year-end, including truck OEM partner readiness and expanding the autonomous readiness measure beyond the 95% level from mid-April.

Christopher Urmson: Yes. I would say it’s the same set of things that we talked about in February. So we need to continue the work in refining the oral driver and completing the validation of that. The team is increasingly focused on things beyond initial commercial launch. And so we’re excited about that. Second, we need the regulatory environment and there we see very little risk given the enthusiasm, Texas demonstrating given the regulatory framework we have, both at a state and federal level. We need customers who are excited about the product. And again, we’re getting strong traction with them as well and are in a good position there. And then finally, as you point out, we need a vehicle platform that has the appropriate redundancies in it. And we continue to work on a daily basis with our OEM partners and are making good progress there as well. So we continue to anticipate being ready to be launching at the end of this year.

Mark Delaney: And then second question, probably more for Dave was on free cash flow. And it came in well below the $175 million to $185 million quarterly cash use guidance, which I understand is an average for the year. But when we look at where it came in for 1Q and also contemplated some of the financial control you spoke about in your prepared remarks, I’m hoping to better understand if you think there’s the potential for free cash flow to be a bit better than what you’d previously expected for the year?

David Maday: Yes. Thanks, Mark. Appreciate that. And yes, the team really has demonstrated outstanding fiscal prudence in this regard. And so our objective is really to be on the low end of the range. But I think there are some uncertainties out there that we continue to want to protect for. We did do some prepayments, which traditionally, you wouldn’t do, but we wanted to protect supply — there may be some more of those. We anticipate some more of those in the second quarter that we’re also going to do. So I think we’re not ready to change any guidance on that. But obviously, we’re targeting towards the low end of the range.

Operator: [Operator Instructions] Our next question comes from the line of David Vernon with Bernstein.

David Vernon: So Dave, when I look at the exhibit label the war driver indicative roadmap to scale. Should I be thinking that the path to gross profit sort of line that ends in 2026 is dependent or independent of some of the product capabilities listed below? I’m just trying to determine, is there like Event risk, if you don’t scale to the fund bill to hit into past the gross profit or whether these are sort of independent time lines that just lay out in the same in the 2026 time frame.

David Maday: Well, I think they’re somewhat interrelated, but they’re not completely dependent. So when you think about gross margin, that’s ensuring that for every load that we deliver, right, in every mile that we drive, we’re able to do it in a cost-effective manner relative to the price that we’re getting paid. And so we think some of the controllable levers in that area are related to driving down the hardware costs, improving the ratio of remote assist operators to trucks and, of course, continuing to reduce any potential reliance on on-site support. So when I think about those, they feel very much focused in on things that are going to drive the early gross margin. When I look at the scaling out to the Sun Belt, I think there’s — that’s the element that really drives us towards the bottom line free cash flow positive, where we’re really generating a quantum of money that is really significant and then allows us to start self-funding some of our activities.

That said, obviously, some element of the cost of benefits that we’re going to get have to be realized by driving sufficient number of trucks. And again, I think we run these in parallel, but it’s not dependent upon that. And so if we were slightly delayed on a particular area, that would impact our gross margin projections in the early years. We really think that you have to do both though, right? Like the focus is that our entire organization is structured to make sure that we can deliver the benefits of our self-driving technology safely, quickly and broadly. And broadly, is really critical to commercialize the business in B cell funding.

David Vernon: And is there any sort of range of miles driven that you can kind of project into that 26th time frame that gets you to that gross profit level?

David Maday: So the benchmark in the industry is roughly 100 to 125. And what we’ve said before is we think that we would be able to double that or roughly double that kind of percentage. So that would be the guidance I would give you.

David Vernon: But maybe as far as the business being sort of gross contribution positive, right, like generating some sort of gross profit. Like what kind of number that aggregate miles, does that imply? I don’t know if you can share that or not. I’m just trying to backward engineer kind of some of the economics here.

David Maday: Yes. I think if you’re looking at the aggregate — are you looking at the aggregate miles? Or are you looking at kind of€¦

David Vernon: Yeah like total margin to get you to gross profit total like trucks times the number of miles per truck.

David Maday: Yes, yes. So if you look — if you recall what we did at our Analyst Day, we had an expectation out there of about 125 million miles by the end of ’26 and that’s when we expect to get to gross profit positive. I will say, though, again, that the gross profit at a percent basis relative to what we’re trying to achieve, it’s not 100% mileage driven. So right, again, this is about us doing the things that we need to do relative to reducing any potential need for on-site support, increase in the remote operator ratio as well and then bringing in our hardware — [ Perseus ] second-generation arose, that’s being manufactured by Fabrinet. So if we were at like 100 million miles, we would still hit a gross profit positive target at that point. So they’re not completely dependent on each other.

Operator: And our next question comes from the line of Jeff Osborne with TD Cowen.

Jeffrey Osborne: Two quick ones, Dave, and I apologize for the background noise here. But I was wondering, can you elaborate more on the types of things that you would have to prepay heading into the commercial launch, what types of equipment that’s for? And then I think you mentioned incentive comp would tick up on a cash use for 2Q. Is there any way to dimension how much cash that would be? And then as we think about 3Q, that would be rolling off, I assume.

David Maday: Yes. So relative to the prepayments, it’s really some of the core components of our hardware set to make sure that we’ve got sufficient supply. There’s a lot of demand out there in the industry, and we want to just make sure that we lock ours down. So in some of our core components, we don’t announce exactly which ones they are, but it’s some of the core components that you would expect that are critical to our hardware set. And again, we’re very cautious in prepaying where we think that there is great potential out there, and there aren’t supply constraints when there’s significant demand for a limited supply, that’s when we want to protect ourselves. And then relative to the incentive comp, I can kind of refer to kind of like what the 2023 number was, and it’s roughly similar to that. And I believe the 2023 number was $49 million.

Operator: Our next question comes from the line of David Vernon with Bernstein.

David Vernon: I figured that would be cordial I have just asked my 2 and then see if I can pop back on. Just real quick, gave, the contra expense you’re booking for this quarter versus the quarter last year. Did that grow in a meaningful way? Or is it pretty constant? — you’re not booking as revenue year?

David Maday: Yes. The pilot revenue that we do is a contra expense was roughly equivalent. It was actually technically slightly down from last quarter, but that’s largely due to seasonality within the industry. We’re actually scheduling more loads this quarter. We did this for Q1 than we did at the end of Q4. So we schedule on average, 120 loads. And so what happens is the attainment of those is largely driven on our partners. And during Q1, they get a little bit less demand out there. So it was slightly lower, but not material. We expect the year to be — if you look at a year-over-year comp for Q1, we’re substantially above where we were before. And I think as Chris mentioned in his dialogue, it’s a substantial amount, and we expect to continue that momentum when you look at quarter-by-quarter compares. And so — but we do also expect that Q2 would continue on a growth pattern. Q1 is more of a seasonality issue.

David Vernon: Okay. So that growth and that recovery is embedded in your sort of imply — embedded in the guide of the cash flow being about $150 million a quarter, whatever it.

Christopher Urmson: Yes, 100%.

Operator: Thank you. We have reached the end of our question-and-answer session. And with that, this concludes today’s teleconference. You may disconnect your lines at this time. Thank you for your participation.