C3.ai Inc

NYSE:AI

Earnings Call Analysis

C3 AI Targets Growth Amidst Challenges

C3 AI reported a 17% year-over-year increase in total revenue, reaching $73.2 million in Q2. North American revenue surged by 28%, while EMEA declined by 11%. Subscription revenue grew 12% to $66.4 million, 91% of the total, with a gross margin of 56% GAAP and 69% non-GAAP. GAAP net loss was $0.59 per share, non-GAAP net loss $0.13 per share. With $762.3 million in cash, the focus is on expanding C3 generative AI, which negatively impacted margins but promises substantial future returns. Organizational changes aim to remedy poor sales execution in Europe. Q3 is projected to garner $74-$78 million in revenue, and the company is on track for Q4 positive cash flow and full-year fiscal '25.

Growth and Strategic Shifts Amid Market Challenges

The narrative of the quarter is one of continued growth coupled with strategic pivots in response to market forces. Revenue rose 17% year-over-year to $73.2 million, a notable acceleration from the previous quarter's 11% growth, and new customer engagement counts soared by 81% to 404. While North America boasted a 28% revenue increase, EMEA struggled with an 11% decline. A shift from subscription to consumption-based pricing, aimed at easing acquisition and scaling for customers, is well underway, yet it's faced headwinds with lengthier sales cycles due to new AI governance processes within companies, creating a bottleneck. Aggressive investments in generative AI reflect the company's commitment to this burgeoning field, with hopes of leveraging their extensive ecosystem of partnerships and diversified industry engagements to tap into significant future growth.

Product Innovation and Market Reception

The company launched 62 agreements, with 36 being generative AI pilots, marking a 270% year-over-year increase. The pilots have spanned numerous industries, exhibiting the company's cross-sector appeal. In particular, generative AI has become the company's fast-track product, drawing immense interest and expanding the company's addressable market significantly. Market predictions paint generative AI as a potential trillion-dollar industry, and the surge of interest is reflected in the company's generative AI qualified pipeline, which grew 55% sequentially in the second quarter. However, a pivot is not without its difficulties; the shift to consumption-based pricing has led to lower average selling prices and decreased Remaining Performance Obligations (RPO), indicative of the transitional growing pains.

Investments Driving Future Growth

The company's strategic choice to heavily invest in generative AI speaks to the perceived enormity of the opportunity. With a substantial cash balance, increased investments are directed towards lead generation, branding, market awareness, and customer success. These moves are consistent with their broader mission to enhance customer satisfaction and expand their market reach ambitiously. While these investments have led to negative cash flow in the short term, there is a strong belief that positive cash flow in Q4 of FY '24 and positive cash flow plus non-GAAP profitability in FY '25 are achievable targets, painting a picture of a company willing to weather short-term costs for long-term market positioning.

Financial Health and Guidance

Financially, the company is on solid ground, with $762.3 million in cash and investments. They've endured a 27.3% year-over-year decline in GAAP RPO, attributed to the transition to a consumption-based model. Nevertheless, the current RPO increased by 3.5% compared to last year. The guidance for the next quarter forecasts revenue between $74 million to $78 million, with an expected non-GAAP loss from operations ranging between $40 million and $46 million. Looking ahead, positive cash flow is anticipated in Q4 FY '24 and the full year of FY '25, with the latter half of FY '25 also set to bring non-GAAP profitability. Despite some volatility in financial KPIs during this transition phase, the growth trajectory appears to align with strategic investments and recalibrations.

Earnings Call Transcript 2024-Q2

[Operator]

Good day, and thank you for standing by. Welcome to the C3 AI's Second Quarter Fiscal Year '24 Conference Call. [Operator Instructions] Please be advised that today's call is being recorded. I would now like to turn the conference over to your host, Mr. Amit Berry. Please begin.

[Amit Berry, executive]

Good afternoon, and welcome to C3 AI's earnings call for the second quarter of fiscal year 2024, which ended on October 31, 2023. My name is Amit Berry, and I lead Investor Relations at C3 AI.

With me on the call today is Tom Siebel, Chairman and Chief Executive Officer; and Juho Parkkinen, Chief Financial Officer. After the market closed today, we issued a press release with details regarding our second quarter results as well as a supplemental to our results. Both of which can be accessed through the Investor Relations section of our website at ir.c3.ai. This call is being webcast, and a replay will be available on our IR website following the conclusion of the call.

During today's call, we will make statements related to our business that may be considered forward-looking under federal securities laws. These statements reflect our views only as of today and should not be considered representative of our views as of any subsequent date. We disclaim any obligation to update any forward-looking statements or outlook.

These statements are subject to a variety of risks and uncertainties that could cause actual results to differ materially from expectations. For a further discussion of the material risks and other important factors that could affect our actual results, please refer to our filings with the SEC. All figures will be discussed on a non-GAAP basis unless otherwise noted. Also during the course of today's call, we will refer to certain non-GAAP financial measures. A reconciliation of GAAP to non-GAAP measures is included in our press release.

Finally, at times in our prepared remarks, in response to your questions, we may discuss metrics that are incremental to our usual presentation to give greater insight into the dynamics of our business or our quarterly results. Please be advised that we may or may not continue to provide this additional detail in the future.

And with that, let me turn the call over to Tom.

[Thomas Siebel, executive]

Thank you, Amit. Good afternoon, everyone, and thank you for joining our call today. Results. Bottom line, we continue to accelerate our revenue growth and our customer engagement count and continue to gain traction with C3 generative AI and our enterprise AI applications in the second quarter. Total revenue for the second quarter was $73.2 million, an increase of 17% compared to $62.4 million 1 year ago, and accelerating from an 11% increase in the first quarter.

The total number of customer engagements was 404, an increase of 81% compared to 223 last quarter. North American revenue of $61.2 million increased 28% year-over-year, while EMEA revenue of $10.6 million decreased 11% year-over-year, and federal revenue increased 100% year-over-year. Subscription revenue for the quarter was $66.4 million, constituted 91% of total revenue and increasing 12% from a year ago. GAAP gross profit for the quarter was $41.1 million, representing a 56% gross margin.

Our non-GAAP gross profit for the quarter was $50.4 million, representing a 69% non-GAAP gross margin. Our GAAP net loss per share was -- the loss was $0.59, and non-GAAP net loss per share was $0.13. We ended the quarter with $762.3 million in cash, cash equivalents and investments. C3 AI's partner ecosystem continues to drive significant growth. In Q2, the company closed 40 agreements through our partner network. Including AWS, Booz Allen, Baker Hughes, Google Cloud and Microsoft. The qualified opportunity pipeline with partners has increased by 75% in the past year.

We've signed new and expanded agreements with Nucor Corporation, Roche, Con Edison, Hewlett Packard Enterprise, GSK formerly SmithKline, the United States Navy, the Administration for Children & Families, a division of Health & Human Services, Indorama and First Bank amongst others. Over the past several months, C3 AI has helped Nucor, the largest steel producer in the United States to better optimize caster production schedules specifically to improve production levels and reduced cost levels in the steel casting process.

C3 AI is now helping Nucor scale this across several additional mills. In Q2, C3 AI also kicked off 2 new additional use cases at Nucor, tackling process optimization and demand forecasting, and we also completed a C3 generative AI pilot. Targeting operational health and safety. GSK formally GlaxoSmithKline, is now using C3 AI supply chain suite to increase efficiency in its supply chain, using AI to optimize yield and improve demand forecasting processes.

Con Edison, a C3 customer since 2017 continues to expand its use of the C3 AI applications. Most recently, by adding C3 generative AI. Con Ed is using C3 generative AI to help workers quickly find answers to questions and analysis related to smart meters, service levels and infrastructure data. In the second quarter, Con Edison completed 2 pilots of C3 generative AI, which have now converted to production.

We also continue to expand our footprint in state and local governments with particular interest in C3 AI law enforcement from San Mateo County, California. And C3 AI residential property appraisal from Stark County, Ohio and Charlotte County, Florida. Our federal business continues to show significant strength with bookings up 187% year-over-year. We closed new and expanded deals with the United States Navy, the intelligence community, Joint Staff J8, the Defense Logistics Agency, and the Administration for Children & Families

We've talked many times about our success. Our successes in helping them monetize or to modernize -- sorry, the Department of Defense and we're proud now to say that our products are helping civilian government agencies as well. This quarter, we began work with the Administration for Children & Families, a division of the U.S. Department of Health & Human Services. The agreement with C3 AI was part of their first order under a $90 million purchase -- blanket purchase agreement. And this part of ACF's work involves helping unaccompanied children who across the U.S. border find temporary shelter and permanent homes.

Our platform will be used in complex modeling and predictive analytics at ACF to help them keep track of the number of unaccompanied children in the agencies care, staffing needs and determine how long these children are with their case managers amongst other tasks.

Our C3 AI continues to leverage its extensive commercial supply chain experience in the federal government and is now applying this experience in the defense sector with the C3 AI contested logistics application for Transcom and for DLA.

During the quarter, C3 AI converted 2 defense logistics agency pilots in the follow-on projects for the Department of Defense. The first project delivers common operating picture of the supply chain for DoD and enables leaders at multiple echelons to see in near real time, their global Class 9 supply posture. The application unifies disparate supply data and provides the defense logistics agency, the ability to identify supply chain inefficiencies forecast, parts consumption and parts shortage and conduct impact assessments and put into place mitigation plans.

The second project supports DLA's energy directory, leveraging C3 AI's commercial expertise in the oil and gas sector. The C3 AI's contested logistics application modernizes and streamlines global fuel distribution for the Department of Defense. Users can see global fuel inventories anticipate fuel consumption, identify supply network risks and create distribution and transportation plans to prevent disruption and assure supply. These applications promise to significantly impact the efficiency of the Department of Defense Logistic enterprise and improve readiness.

Our partnership with AWS deepened with an expanded strategic collaboration agreement in the quarter, okay? And the availability of our new no-code self-service generative AI applications, C3 generative AI now available on the AWS marketplace. I think we announced that last week. This new application allows customers -- users of all technical levels to begin using generative AI within minutes of signing up. And this application, C3 generative AI is now available to you on the AWS marketplace under a 14-day free trial. So I encourage you to take a look at it for those of you who are interested.

Under the expanded collaboration agreement with AWS, we're focusing on offering advanced generative AI solutions, combined with what they're doing in Bedrock, okay, and other initiatives for enterprises and for AI applications for customers in multiple verticals, including manufacturing, power and utilities, consumer packaged goods, state and local government and the federal government.

C3 AI and AWS' joint qualified pipeline has more than doubled year-over-year with heightened interest in the C3 generative AI suite. In Q2, C3 has been recognized multiple times for its innovation in the AI space. We've been named to the Fortune 50 AI Innovators list and the list goes on and on. So I'm not going to bore you with that. We do get recognized all the time.

Pilot growth, this is important. In Q2, we closed 62 agreements, including 36 pilots and trials. Our new pilot count is up 270% from a year ago. Notably, 20 of these were generative AI pilots, 150% increase from Q1. With the lower entry price points of our pilots, we are more easily able to land new accounts. With our pilots, we are engaging customers across a diverse set of industries in this quarter. Our pilots came from manufacturing federal, defense, aerospace, pharmaceuticals and other industries. Now we did see sales headwinds in the quarter. Okay.

While the interest in AI applications and especially generative AI is growing substantially, we're also seeing, in many cases, lengthening decision cycles. Virtually every company, okay, in the last 3 to 6 months has created a new AI governance function as part of its decision-making process. These AI governance functions assess and approve those AI applications that will be allowed to be installed in the enterprise. This has candidly added a step to the decision process in AI. You might have heard it here first, okay, but you will be hearing this from every AI vendor, okay, in the next few quarters. Take it to the bank.

It has simply -- it has added a step of the process. It is -- and it is lengthening the normal sales cycle. So it's in -- so this -- this provided a sales headwind in the quarter. Okay. And while the increased scrutiny lengthens the sales process, we believe that this is a healthy process to ensure that companies are adopting safe and appropriate AI solutions. So we're all for it, okay. And did it move revenue a little bit a click below the center of the range? Yes, it did, okay. But get over it. The world is a better place, people are making very careful well-informed decisions. They have their best people on it, and we will all be happier for this in the long run.

So it did -- that dynamic did provide an unexpected headwind to our Q2 sales revenue performance. In addition, our sales execution in Europe was candidly unacceptable. Okay. And since then, we've taken -- we've been through our planning meetings and we've taken appropriate organizational steps to immediately improve sales execution in Europe.

Now let's take a look at -- if this is the big story, this is the top line, okay. And really what this whole story has been about for the last 6 to 7 quarters has been from the transition from subscription-based pricing to consumption-based pricing.

And before we switch to consumption-based pricing, you will recall the company was growing at a quite a rapid growth rate, like I think, 7 quarters ago, order of 38% year-over-year growth rate. So we were definitely in the top quartile. And we announced the transition to consumption-based pricing that we believe would be and has become the standard in the industry. Okay, the consumption-based pricing is based upon per virtual CPU or virtual GPU hour, similar to the pricing at Snowflake, Google Cloud, AWS, Microsoft, Azure et cetera. Prior to this, we were doing large enterprise subscription deals of $1 million, $5 million, $20 million, $50 million.

And it was a good business. That being said, the downside of that model was lumpiness in bookings, lengthy sales cycles and low levels of revenue predictability. We believe the transition from a primarily subscription-based pricing model to an assumption-based price remodel brought us into line with what we believe are today, the industry standard cloud pricing standards. Making it easier and less costly for new customers to acquire our solutions and then increase their spending as their usage and adoption increase.

We anticipated and announced when we made that transition, it would have a short to medium negative effect on revenue growth, a long-term drag on RPO as the sales price was significantly reduced and the contracts often lack a time-certain multi-period commitment. We believe when we made the announcement that the consumption-based pricing model would increase the number of customers, okay, and increase the total amount of system consumption, returning -- resulting in a return to increased revenue growth, increased customer growth, decreased average selling price and decreased RPO over time.

Now while we are still in the process of working through -- completely through this transition to the new pricing model, the preliminary empirical results that we are seeing evidenced by year-over-year growth rates appear to be proving out exactly as expected and exactly as we predicted. Since the transition revenue growth initially decreased, then it flattened, okay.

And now it is increasing as the consumption-based pricing model take effect -- takes effect. Average selling prices decreased, RPO has decreased, customer engagement has increased substantially. If we look back over the last, say, 1, 2, 3, 4 quarters, 4 quarters ago, our revenue growth was negative 4% and then 0%. The last quarter, it was 11%, now it's 17%. Bookings growth, 71% year-over-year. I'm sorry, bookings growth 100% year-over-year. The new contract growth of 148% year-over-year, okay. Pilot growth, 50% quarter-over-quarter, 170% year-over-year. So this is basically the beginning, the middle and the end of this story, okay.

We announced 6, 7 quarters ago, a transition to our consumption-based pricing. We predicted that revenue would decline and then flatten and then increase, and we are now seeing these increases that we predicted. So now let's talk about generative AI. Generative AI simply changes everything. okay. I believe that it more than doubles the size of our addressable market overnight. We've all seen the predictions from Bloomberg that predicts this is 100 -- this is in excess of $1 trillion, $1.3 trillion market by 2032. Goldman Sachs predicts that this could increase corporate profits by 30% in the next decade. And the generative AI alone could raise the global GDP by 7%. People, this is a big deal. It is difficult to overestimate the levels of interest that we're seeing in the category of generative AI.

Now by combining our multibillion dollar, say, 14-year investment in the C3 AI platform, with the recent developments in large language models and retrieval augmented generation, C3 AI is unique in the market and that we are able to solve the disqualifying hobgoblin that are preventing the adoption of generative AI, okay, in government, in defense, in intelligence, in the private sector. What are those hobgoblin.

Those are the facts that the answers that come out of these large language models are stochastic. They're random. They're not traceable. We have this hallucination problem, which is extraordinarily problematic. We have research, none of our data access controls yet, be it DoD or Bank of America are enforced. We have these problems with LLM cause data exfiltration, LLM cause cyber threats and IP liability. In addition, all the solutions that are out there, almost all those solutions, I would say, with the exception of AWS, Bedrock, tend to be LLM specific.

And I don't think anybody wants to be a LLM, hook their wagon on to any given LLM today with all the innovation that's going on in the market. and to be dependent on any LLM provider that could make some announcement on Friday and be gone on Monday. See OpenAI for details. So this LLM agnostic is firstly, the bottom line is our solution in the market addresses every one of those hobgoblin that prevent the installation of generative AI in the enterprise.

So this is really unique and it took 14 years and $2 billion worth of software engineering for us to be ready for this. This is why we could solve it. So while the rest of the world is playing catch-up. How about multi-modal. I mean we're completely nail multi-modal. We've been doing it for 14 years. Multi-modal, what does this mean? Rather than all these LLM solutions basically handle text, we handle text, we have telemetry. We handle images. We handle signals. There we handle enterprise data, we handle the structure data. We handle unstructured data.

So we are unique in the market, and the result is quite exciting. So while the rest of the world is playing catch-up and we have scores of start-ups with three guys, four girls and two cats in an apartment in San Francisco, being they're getting $1 billion funding and multibillion dollar market valuation, see pitch book for details. We have I don't know how many customers, we have [ through order ] of 1,000 employees. I don't know how many countries, and we're delivering these solutions today. And -- so while the rest of the world is playing catch-up, we're working closely with our customers and new customers to install high value generative AI solutions that rapidly realize value to their organization.

We believe that our strategic decision to invest in generative AI could address our addressable market opportunity. Our suite of 28, now I think 29 generative AI products wins on reliability, flexibility, adaptability, accuracy and security, all of the same qualities that are inherent in our enterprise AI platform. Our vision to expand our customer base is working. The idea, and this is very much idea about the work that we're doing on the AWS marketplace is to go from 8 customers to 80 customers to 8,000 customers to 80,000 customers.

So what we're dealing now is kind of a new game with massive market leverage, and we are the first to market. And we -- so I think we have the opportunity here through our innovation, through our applications that will proliferate across the business. C3 generative AI has enabled us to land high-caliber new customers and expand agreements with the current customers. The surge of interest led to our C3 generative AI qualified pipeline increasing new opportunities, increasing 55% sequentially quarter-over-quarter in the second quarter, representing the most rapid acceleration of all our product offerings.

We expect this momentum to grow as we continue to innovate and build the increasingly exciting products. Our November announcement of the self-service C3 generative AI on the AWS marketplace plays a big part in this story, potentially expanding our addressable customer pool and our user base exponentially. This new application allows users of all technical levels to enroll in the application and begin productively using generative AI in minutes. Again, this product is available today on the AWS marketplace, should you have interest.

As I introduced last quarter, we made a well-considered decision to seize the immediate and candidly staggering market opportunity that we see in generative AI. As such, we are making and increasing a sizable and timely investment in application development, model engineering, lead generation, branding and market awareness to seize market share in generative AI as rapidly as possible. This will put short-term downward pressure on free cash flow and profitability.

Closing thoughts. The generative AI opportunity is staggering. We believe that it is in the best interest of our shareholders to further accelerate our investment in generative AI, deepening our investments in lead generation, branding market awareness and customer success. Given our substantial cash balance, we believe it is a strategic imperative to invest further in the generative AI opportunity at this time.

Separately, now with the release of our platform version of our 8.3 product line, which is really quite remarkable in terms of the benefits that it brings to our customers and the increase in performance that it brings to our customers we have decided to further invest in our customer base to accelerate their upgrade from Version 7 to version 8.3, which we believe will further increase our customer satisfaction levels that are already quite high.

We continue -- that being said, we continue to expect positive cash flow in Q4. And while we're not giving fiscal year '25 guidance yet, we continue to expect positive cash flow for full year -- fiscal year '25. C3 AI remains focused. We are 1 of the few AI software pure plays that have established relationships, a tried test and proven technology platform add reputational equity to capitalize on this generative AI market opportunity.

I'll turn the call over to Juho Parkkinen , our Chief Financial Officer, to talk more about our financial performance and provide guidance for the remainder of the fiscal year. Juho?

[Juho Parkkinen, executive]

Thank you, Tom. I will now provide a recap of our Q2 financial results and some additional color on our consumption-based revenue model, which we introduced 5 quarters ago. Then I'll discuss factors that will drive our financials in the back half of the year. All figures are non-GAAP on as otherwise noted.

Total revenue for the second quarter increased 17.3% year-over-year to $73.2 million. Subscription revenue increased to 11.7% year-over-year to $66.4 million and represented 90.7% of total revenue. Professional services revenue was $6.8 million and represented 9.3% of total revenue. Gross profit for the second quarter was $50.4 million, and gross margin was 68.8%, and as a reminder, we continue to expect short-term pressure on our gross margins due to a higher mix of packets, which carry a greater cost of revenue during the pilot phase of the customer life cycle.

Operating loss for the quarter was negative $25 million compared to our guidance range of negative $27 million to negative $40 million. The improvement in operating loss versus guidance was driven by timing and amounts of the generative AI-regated investments we made to capture market share as well as our team's ongoing focus on disciplined expense management. At the end of Q2, our accounts receivable was $143.2 million, including unbilled receivables of $104.8 million The general health of our accounts receivable remains strong. Now turning to RPO and bookings.

Reflecting our transition to consumption-based contracts, we reported second quarter GAAP RPO of $303.6 million which is down 27.3% from last year and current GAAP RPO of $170.2 million, which is up 3.5% from last year. We continue to see positive trends in the diversity of our pilot bookings with 10 industry segments represented in Q2 pilots as compared to 8 in Q1. Free cash flow for the quarter was negative $55.1 million, we continue to be very well capitalized and closed the quarter with $762.3 million in cash, cash equivalents and marketable securities.

Now I'll provide an update on our consumption business model for the second quarter. During the quarter, we started 36 pockets, a 50% increase from last quarter. We are pleased to report that the actual vCPU consumption data that we're seeing from pilot activity has validated the assumptions we made when we transition to the consumption-based pricing model 5 quarters ago. Our pilot conversion rates are trending upwards or getting close to our target of 70%.

At quarter end, we had cumulatively signed 109 pilots, of which 103 are still active. This means they are still in their original 3- to 6-month term extended for 1 to 2 months, converted to consumption or a license contract or are currently being negotiated for a production license. Finally, our customer engagement count for the quarter was 404, an 81% increase from 223 a year ago.

Turning to guidance. As Tom mentioned, we expect Q3 revenue range from $74 million to $78 million, and non-GAAP loss from operations to range from negative $40 million to negative $46 million. We remain committed to delivering positive cash flow in Q4 FY '24 and for the full year of fiscal year '25 and non-GAAP profitability in the second half of fiscal '25. For the full fiscal year '24, we are maintaining our previous revenue guidance in the range of $295 million to $320 million. We are increasing our non-GAAP loss from operations guidance to a range of negative $115 million to negative $135 million.

I'd like to turn the call over to the operator to begin the Q&A session. Operator?

[Operator]

Our first question comes from the line of Timothy Horan of Oppenheimer.

[Timothy Horan, analyst]

Really appreciate the time. Can you give us a sense of what you're seeing with AI in terms of productivity improvements. And what is the major bottleneck that you think customers need to overcome to really start implementing services?

[Thomas Siebel, executive]

I'm sorry, the question related to Gen AI?.

[Timothy Horan, analyst]

Yes. Specifically on Gen AI, what type of productivity improvements do you think customers can see on specific applications? And what is the major bottleneck for them adopting Gen AI.

[Thomas Siebel, executive]

The major bottleneck as it relates to generative AI relates to the problems that are inherent in these large language models, and they're very real. I mean, as you know, if you ChatGPT or Google Bard, both of which are like excellent products, but the answers tend to be stochastic. So every time you ask a question, getting them to answer, the -- if it doesn't know the answer, it hallucinates. The data access controls are not in force. So the CEO and the person on the factory floor to get access to the same information.

Where Carnegie Mellon and others are now identifying huge cybersecurity risk that are associated with these large language models to corporations and government entities. We have IP liability problems that people are concerned about because these large language models are trained on and have access to all the data into the Internet.

This is like weather, the stock prices, what have you. Those -- somebody has the copyright to all those data, be it the weather company or Bloomberg, and they want to get money. So the quintals of the world are going to build big businesses litigating businesses issues in the next 10 years. We have -- so there's very real issues. The other issue relates to almost all the solutions that are being offered are LLM specific and in, say, December of 2023, to hook your wagon on any specific LLM is kind of crazy because next week, somebody is going to leave frocked by a factor of temps.

You need to be able to switch, you need to be LLM agnostic. So I think those are really the hobgoblin cybersecurity hallucination information security that are basically making it, so many organizations will not allow any Generative AI application to be installed. What's unique about the C3 AI solution is when you talk about this some other time or you can look it up on the Internet.

But by combining with the 14 years of work that we did with the C3 AI platform, we've addressed all those problems, cybersecurity, data security, hallucination, what have you. So I think that's the hobgoblin. That's what slows things down and people need to be satisfied to those issues resolved and if they're not resolved, and not being installed to some at any reasonable organization like General Motors or JPMorgan Chase or you name it.

Now as it relates to productivity increases, holy moly, they're going to be staggering, whether you're a lawyer, whether you're a realtor, whether you're a physician or whether you're running a paper machine or whether you're operating the inventory or the space command. I mean you -- if you do not have or not being supercharged by generative AI a year competition will be. And if they are, and you're not, they win, you lose, hard stock.

[Timothy Horan, analyst]

So specifically to your customers, what do you think the bottleneck is for adoption? If you have -- it sounds like you have all these problems pretty much resolved for them. What do you think they require at this point to really start adopting?

[Thomas Siebel, executive]

Well, we just -- our sales segments are pretty fast. Our sales cycles for generative AI has been close as 24 hours. And basically, our offering is, we'll bring the application live, in 1 or 2 months, if you like it for, I don't know, $0.25 million or something. And if you like it, keep it. So this has to do with people evaluating bond portfolios, people running paper machines, people running steel mills, the intelligence community, missile defense agency, others. So we just -- we -- many of them are existing C3 customers although increasingly, we will be serving 9 out of 10 will not be existing C3 customers.

But we have to address the concerns that identified. We seem to be able to address those. After that, we just bring the application live, we get it live in 4 to 8 weeks and if they like it, keep it and so it's a pretty short sales cycle for us, and you're seeing a very substantial increase in the pilots that we're deploying. You can expect -- we're expecting a pilot to production conversion rate of, it looks like about 70%. And -- so it does look like a big opportunity.

[Operator]

[Operator Instructions]

Our next question comes from the line of Mike Cikos of Needham.

[Michael Cikos, analyst]

I wanted to ask first about the subscription gross margins, and this probably goes back to Juho's prepared remarks, but it was good to see gross margins actually increased sequentially despite the increased pilot count. And I know that you guys are calling out the short-term pressure just based on the growing mix of pilots. And so -- can you help us think about like what was it that actually went better for you guys? Because I think we were expecting a little bit more degradation in the subscription gross margins versus how you guys -- how the quarter actually came through?

[Juho Parkkinen, executive]

Thanks, Mike. This is Juho. So yes, in the big picture, as we announced 5 quarters ago, as we're seeing, we are expecting the gross margin degradation for the subscription to continue. Now in this particular quarter, we were very pleased to see some improvement on a sequential basis, but I think we would expect flattening to down again on the next quarter as the target count increases and is going to put pressure before the consumption amount start picking up and offsetting that.

[Michael Cikos, analyst]

Got it. And if I just shift down to OpEx for a second as well. I guess 2 quarters here. So first, I know that you guys are increasing the anticipated operating losses here. Last quarter, we had cited increased investment in like branding and lead gen and awareness, right? So can you help us think through where you guys are doubling down?

And then the second piece there, there was obviously that article that came out in Bloomberg, I think it was in mid- to late November citing head count costs -- head count cutting, I'm sorry. So can you just comment on the validity of the Bloomberg article just because I think people are trying to see if you did make those head count cuts, how much are we doubling down on these investments or if that had article proved to be false?

[Thomas Siebel, executive]

Mark, it's Tom. Doubling down. We're doubling down on data scientists. We're doubling down on large language model engineers, we're doubling down. A lot of it is going into engineering, but also candidly in lead generation. I mean there's an opportunity now as we move to these marketplaces to be dealing transactions in hundreds to thousands to tens of thousands of units rather than scores.

And that I can assure you is the plan that we have. As it relates to -- I'm not familiar with Bloomberg article that you talked about. It sounds like somebody mentioned something that we did some layoffs in the quarter. Mike, we do performance-related layoffs every quarter, okay?

And the -- so we -- I think last quarter, we had 42,000 job applicants. We -- how many people did we hire, Juho?

[Juho Parkkinen, executive]

Order of 100.

[Thomas Siebel, executive]

Order of 100. And these people, yes, they went to MAT. Yes, they worked at Bank of America. Yes, they went to Chicago GSB and they command an F18 squadron. And so we're constantly upgrading our human capital, and we move underperformers out regularly. So if somebody said that in a Bloomberg article -- I don't know what they said. What I told you is the truth.

[Operator]

Our next question comes from the line of Kingsley Crane of Canaccord Genuity.

[William Kingsley Crane, analyst]

I wanted to touch on the pilot program. You mentioned that you'd move to a lower entry price point for pilots. Could you give us a sense of the magnitude of that change and then has the minimum fee post pilot also changed? I'm curious what kind of upsell you're seeing upon conversion, if any?

[Thomas Siebel, executive]

Kingsley, it's Tom. I think the standard pilot that we have at Generative AI and the enterprise is like $250,000. But that being said, you can get the AWS -- Generative AI for AWS, which basically handles documents like every other LLM, it handles tax. It's not really multimodal, but that's free for 14 days. So that would be pretty available. Is there a question that he asked that I didn't answer?

[Juho Parkkinen, executive]

No, that's all I think.

[Michael Cikos, analyst]

Okay. Yes. That's helpful. And I just want to touch on OpEx as well. So I think it makes sense that you want to invest more in both LLM engineers and lead gen and it looks like that's particularly hitting harder in Q4 of this year. But as we think about fiscal '25, it seems like some of the nature of those investments would naturally continue as you scale in this large opportunities. So is it about timing in this year? Or are you expecting those to continue next year?

[Thomas Siebel, executive]

Well, Kingsley, I expect them to continue next year. But if you look at the guidance that we gave you in terms -- about 6 quarters ago, what we see is the consumption over the first 12 quarters in terms of CPU seconds per new customer. We just did an analysis of -- I don't know, about 30 customers or 12 customers and those data that we predicted, I think 6 or 7 quarters ago and provided you, it's uncanny and how accurate it is. It's basically plus or minus 10%.

And so if you look, as these things kick in, in quarter 5, 6, 7 and 8, the consumption numbers get pretty big. So you can expect for that we don't really need to cut back on the investments to get to the point of cash positive and non-GAAP profitable. So the top line kind of takes care of that.

[Operator]

Our next question comes from the line of Sanjit Singh of Morgan Stanley.

[Unknown Analyst]

Great. This is [ Theon ] for Sanjit. Tom, maybe starting with you. I mean, with a couple of quarters of the consumption model now under your belt, clearly, you're seeing a lot of sort of quantity of deals and pilots. Is there any way that you can frame or give us a sense of the quality of those customers that went with the consumption model early on. I guess any sort of scale in terms of spending or growth profile that they're hitting now that you can kind of shed up some light and give us the quality piece where you've given us, I think, a lot on kind of the quantity piece of those yields? And then for you or maybe.

Could you just give us some color on the subscription revenue versus the services revenue this quarter? And then also maybe the partner impact and sort of what that looks like on a go-forward basis.

[Thomas Siebel, executive]

Sanjit (sic) [ Theon ], Okay. Regarding quality, I think there's only 2 ways to look at pilot quality. It's going to be what's the conversion rate, okay? And what's -- and what are they going to consume. Based upon our best guess at this time, based on looking at every path we have out there, going to look at what actually has converted and what we think we will convert. We think our guesstimate that we gave you 6 or 7 quarters ago, 70% is about right. So there's one indication of quality.

The other indication of quality is how many CPU seconds are they consuming? Okay, over -- as you go from quarter 0 to quarter 12. And it's tracking right in line. I mean it varies a little bit from 1 quarter to another, but it's basically right in line with what we told you. The quality is pretty high. Now that being said, as we move now to mass markets and start dealing with hundreds of thousands of people just either kind of ordering this online and playing with it, you're going to expect that conversion rate from that level of pilot to be I would say, I mean, the quality there will be much lower.

And I think we need to measure quality by conversion rate and concession levels. A lot of those people will try it for 5 minutes and drop off. And that's just the way that it is with 3 stuff. Now the rest of the question, I think, goes to you.

[Juho Parkkinen, executive]

Yes, right. So your second part about subscription versus services. So we were 9.3 -- 9.2% professional services, this period, which is a little bit lighter than our expected long-term model of 10% to 20% on professional services. We continue to expect that we will be at that range on a go-forward basis. And then I think you were asking about how we feel about the partners in a go-forward basis. And partners are hugely important for us, and we continue to believe that they're the key part of our go-to-market approach going forward.

[Operator]

It looks like we have time for one last question. Our last question will be from Pat Walravens of JMP Security.

[Owen Hobbs, analyst]

This is Owen Hobbs, on for Pat. I guess first one for Tom. What would you say are the top 1 or 2 federal use cases for Generative AI that you're seeing with those new -- those 5 new federal degenerative AI deals this quarter?

[Thomas Siebel, executive]

Our largest federal use case, as you know, is predictive maintenance to the United States Air Force, okay? This was chosen by the Chief of Staff and we now are doing that, this is the Panda system which is the only AI system of record that we're aware of in all of DoD. So this is a system record for the Air Force for predictive maintenance for all assets.

So far, we have loaded the data, I believe, from 22 weapon systems. F-15, F-16, F-18, F-35, KC-135 F-22, et cetera, into unified federated image. This is 100 terabytes of day, okay? Some of it is maintenance data, sorting data, inventory data, flight data, flight history, telemetry and one aircraft like B-50 each B1 bomber has 42,000 sensors on it, admitting telemetry, and I'm not sure what hertz cycles but pretty fast. So this is a stack of data, okay? I will be there on Monday, that is by next Monday. I will be in Washington, D.C., showing the list to our customers with a Generative AI front end. So think about this as a Mosaic browser front end where a general officer can ask any question about -- and this a 100-terabyte production system.

This is one of the largest production enterprise AI applications in existence, okay? And that person will be able to ask on Monday. Be able to ask any question that you could ask of the weapon system, for example, where craft are operative at Travis Air Force base now? What is my cost of operating the B-1 bottler program in the last year, okay? What is the -- as it relates to F-35, where are my largest part shortages. And rather than going through some cold war era, menu-based SAP or even Cboe, I don't want to take shots at SAP enterprise information system user interface that it constantly can looks like your Bloomberg terminal, okay, which is -- I have one I might guess it's unusable. The -- it'll just be a Mosaic browser, you could ask any questions and get the answer related to any one of these weapon systems in the United States Air Force. I guess their production data. And we will show it on Monday, on Tuesday, on Wednesday, and I am telling you we expect some light bulbs to flash.

[Owen Hobbs, analyst]

And if I could sneak one last one in for you Juho. Can you please explain the dynamics between the increase in accounts receivable from last quarter to this quarter despite revenues kind of staying flattish?

[Juho Parkkinen, executive]

Well, accounts receivable is timing of invoicing. So obviously, when we drop an invoice, it shows up in the accounts receivable. So it's just timing of invoicing.

[Thomas Siebel, executive]

Ladies and gentlemen, I think we're at end of program. We appreciate your time and your attention. And thank you very much, and we look forward to talking with you next quarter, standby, it does appear to be a game on in the AI industry at global scale, and I can assure you we are very much in the game. So, thank you all, and we're signing off.

[Operator]

Thank you. Ladies and gentlemen, this does conclude today's conference. Thank you all for participating, and have a good night. You may now disconnect.