C3.ai (AI) Q1 2025 Earnings Call Transcript

C3.ai (AI -1.88%)
Q1 2025 Earnings Call
Sep 04, 2024, 5:00 p.m. ET

Contents:

• Prepared Remarks
• Questions and Answers
• Call Participants

Prepared Remarks:

Operator

Good day, and thank you for standing by. Welcome to the C3 AI’s first quarter fiscal year 2025 conference call. At this time, all participants are in a listen-only mode. After the speakers’ presentation, there will be a question-and-answer session.

[Operator instructions] Please be advised that today’s conference is being recorded. I would now like to hand the conference over to your speaker for today, Amit Berry, you may begin.

Amit Berry — Investor Relations

Good afternoon, and welcome to C3 AI’s earnings call for the first quarter of fiscal year 2025, which ended on July 31st, 2024. My name is Amit Berry, and I lead investor relations at C3 AI. With me on the call today are Tom Siebel, chairman and chief executive officer; Ed Abbo, executive vice president and chief technology officer; and Hitesh Lath, chief financial officer. After the market closed today, we issued a press release with details regarding our first quarter results, as well as the 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 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 provide, may or may not continue to provide this additional detail in the future. And with that, let me turn the call over to Tom.

Tom Siebel — Chairman and Chief Executive Officer

Thank you, Amit. Good afternoon, everyone, and thank you for joining our call today. We are off to a solid start for fiscal year ’25. In Q1, we exceeded all expectations for revenue, cash flow, and profitability.

This quarter marked our sixth consecutive quarter of accelerating revenue growth, reflecting our high levels of customer satisfaction and increasing demand for enterprise AI applications. Our year-over-year revenue growth has accelerated from 11% in Q1 ’24 to 17% in Q2, 18% in Q3, 20% in Q4 and 21% in Q1 year-over-year revenue growth in Q1 of fiscal year ’25. Total revenue for the quarter was $87.2 million, exceeding analyst expectations. Subscription revenue was $73.5 million and increased 20% from a year ago.

Our non-GAAP gross profit was $60.9 million representing a 70% gross margin. Our GAAP operating loss was $72.6 million. Our non-GAAP operating loss was $16.6 million and substantially better than our guidance for a loss of $22 million to $30 million. Our non-GAAP net loss per share was $0.05.

Our net cash provided by operating activities was $8 million, and we generated free cash flow of $7.1 million in the quarter, both substantially exceed market expectations. We ended the quarter with over $760 million in cash, cash equivalents, and investments. I’ll note that this is the 15th consecutive quarter as a public company in which we have met or exceeded our revenue guidance. In the first quarter, the company closed 71 agreements, including 72 new pilots marking a 117% year-over-year increase in our pilot count.

We entered into new agreements with GSK, Eletrobras, Valero, Swift, SmithRx, Sanofi, the U.S. Intelligence Community, the U.S. Department of Defense, Dolce & Gabbana, Ingersoll Rand, and others. Additionally, we significantly expanded our footprint across state and local government.

In Q1, the company signed 25 agreements with state and local governments with municipal, county, and state agencies in Texas, California, New Jersey, Georgia, Washington, and Connecticut, Virginia, Rhode Island, Maine, New Mexico, and Florida. State and local government is a large and underserved market that we’re rapidly penetrating. Our solutions increase efficiency while maintaining the highest standards for accuracy, transparency, and security. They drive substantial cost savings and the combined benefits result in improved public services and improved customer experience.

In short, C3 AI is enabling government agencies to do more with less, ultimately benefiting the public. To quote from the Assessor of Riverside County, and I quote, “We set the bar high for C3 AI and they delivered with over 90% model accuracy in our property valuations. This technology is letting our staff do the mundane tasks faster and easier so they can concentrate on the very complicated properties. And our employees are starting to see the fruits of this effort translating into better customer service.

Overall, we are seeing incredible results with C3 AI.” The proven benefits of C3 AI local government suite, combined with our partner-supported and concentrated sales strategy resulted in an accelerated sales cycle within the sector. The growth was fueled by a highly, collaborative joint sales and marketing campaign with C3 AI and Google Cloud to promote the C3 AI state and local government suite, including C3 AI property appraisal and C3 Generative AI for public benefits. Through these efforts, we saw high adoption with state and local government closing 24 agreements in the quarter. Let me give you a feel for the speed of these sales cycles.

In Q1, we closed an agreement with a county in the Northwestern United States. County decision-makers got introduced to C3 AI at an industry conference. And within 24 hours, we were in contract negotiations. Just 12 hours later, we were in contract for C3 AI property appraisal.

Another example is with a county in the Southeast. This customer attended our Annual Users Group Conference, C3 Transform in March of 2024. Then four weeks later, we held an executive briefing for the county leadership. And now after three months of contract discussion, the county has signed a seven-figure, five-year subscription deal for C3 AI property appraisal.

Our state and local business has grown more than 500% year over year, and we are excited about the traction, the potential for expansion, and the customer advocacy for C3 AI. As we now take these public sector solutions to market in Europe, the addressable market more than doubles. Turning to the C3 AI federal business. This sector continues to experience substantial sustained momentum, representing over 30% of our bookings for the quarter.

We entered in new expansion agreements with the United States Air Force, the U.S. Navy, U.S. Marine Corps, and the U.S. Intelligence Community among others.

These agencies trust C3 AI to provide secure and innovative applications that help them modernize. The U.S. Marine Corps and C3 AI continued the successful collaboration to digitally transform the branch’s legacy software systems. The Marine Corps is using the C3 AI Defense and Intelligence suite to improve the efficiency of personnel management systems by accelerating critical processes and time-to-decision support.

This work with C3 AI is backed by Manpower IT Systems Modernization program and aligns with the Marine Corps multiyear roadmap and goals. C3 AI’s customer base continues to expand, both within and across industries, while maintaining exceptional levels of customer satisfaction by our continued focus on delivering measurable, significant enterprise value. At Eletrobras, the largest power generation transmission company in Latin America, we partnered to enhance their grid resiliency and availability. Brazil’s grid is among the world’s most complex due to its diverse generation profile, variability, expansive service territory, and challenging regulatory environment.

With C3 AI, Eletrobras can effectively and efficiently process and analyze real-time data servicing low-latency AI insights to mitigate network disturbances. Nucor Corporation is seeing significant success in improving manufacturing outcomes with the C3 AI Supply Chain suite. This deployment includes three distinct C3 AI applications, C3 AI Demand Forecasting, C3 AI Inventory Optimization, and C3 AI Production Schedule Optimization, working together to support and optimize daily decision-making across multiple facilities. As we enter Q2, we are focused on expanding sales capacity, expanding in North America, expanding in Europe, and expanding in the public sector.

Our partner network continues to generate opportunities and open new deal flow. We had a very active first quarter in alliances, working closely with our partners to close new agreements. Net-net, 72% of our total agreements were closed with and through our partner ecosystem. This was an increase of 155% year over year and 82% quarter over quarter.

Our partner-supported bookings grew 94% year over year and our activity levels with our partners that include AWS, Booz Allen, Google Cloud, and Microsoft continue to increase substantially. In the first quarter, we closed 40 agreements with Google Cloud. This is an increase of 300% year over year. This growth was largely driven by the joint campaign between C3 AI and Google Cloud which I just discussed earlier, focused on the public sector.

C3 AI continues to be an attractive partner for the hyperscalers as our 90 enterprise AI applications rapidly drive substantial workload in their compute and storage clouds while adding immediate value to our joint customers. As you can see from our supplemental deck, our bookings continue to be increasingly diverse. Our generative AI business is surprisingly diverse with many candidly, unanticipated use cases across the board in a wide range of industries. In addition, our total non-Baker Hughes revenue grew 37% year over year.

Now I’ll hand it over to Ed for an update on our products and generative AI. Ed?

Ed Abbo — Executive Vice President, Chief Technology Officer

Thank you, Tom. Let me first recap where C3 AI fits in the AI tech stack. Starting at the bottom, the four layers include silicon, cloud infrastructure, foundation models. And at the top, harnessing all this innovation to deliver business value to our AI applications.

This is where C3 AI plays with prebuilt AI applications that can be deployed very quickly. In contrast, the offerings you’re seeing in the AI software market today fall into two distinct categories. First, legacy software companies that are scrambling to keep up with AI. To try to stay relevant, these companies are rebranding their 20th-century software stacks with AI on the box.

The technical depth to rewrite their software to take advantage of a modern, scalable AI tech stack is simply insurmountable. For them, AI is just a bolt-on constrained to a small fraction of the enterprise data managed by their legacy software. Second, we see a few more modern software companies that were designed primarily for data integration, data management, or data engineering not claiming to be enterprise AI platforms to build and operate AI applications. Basing an enterprise AI application plan on these incomplete tech stacks requires customers to undertake significant, protracted software development projects where minimal customer value is realized.

This is clearly reflected in the customer satisfaction scores of these vendors. The C3 AI platform is unique in that it was a clean sheet design, providing all the services necessary and sufficient to design, develop, provision, and operate real-world enterprise AI solutions. This provides users with rich workflow-enabled AI applications operating on an application platform with advanced data fusion and governance and scalable AI/ML operations capabilities. We leverage all layers of the AI tech stack, silicon cloud infrastructure services, and foundation models.

The C3 AI platform was purpose-built and hardened over 15 years to rapidly deliver robust customer AI applications. Now let me take a moment to unpack what we mean by prebuilt applications as this is a key differentiator for C3 AI. As a customer, if you buy a prebuilt application, you don’t need to define what the application does, design and develop the ontology, the business logic, the AI or GenAI model pipelines, or the user interface. We’ve done all that.

C3 AI prebuilt applications are tried, tested, and proven in the market, so the application can be rapidly configured to the customer data sources. AI/ML models tuned to customers’ data and the user interface tuned for the customer. This allows customers to quickly configure, deploy, onboard and train users, scale out their enterprise, and rapidly realize enterprise value. Let me give you an example.

Holcim, which is a large global building solutions manufacturer scaled out C3 AI reliability, our prebuilt AI-based predictive maintenance application to most of its plants in just eight months after a successful pilot. The application monitors several hundred critical plant assets such as vertical roller mills and ball mills to accurately predict potential problems well in advance of failure. It does so by continuously ingesting data from over 9,500 sensors and other systems and analyzes those data using 850 machine learning models. The C3I reliability application allows Holcim to avoid significant operational disruptions and high-cost remediations.

Today, we have prebuilt AI applications with turnkey ontologies that address entire value chains across industry verticals. These applications don’t operate in silos. They’re designed and built to work in concert, all running on the C3 AI platform. Each new application can deploy faster than the last, thanks to the ability to reuse data integrations, ontologies, AI/ML pipelines, workflows, and user interface components.

And as more C3 AI applications are deployed, enterprises accrue business benefits faster and the pace of their AI transformation accelerates. We also offer a suite of prebuilt and extensible C3 Generative AI applications that can be used as stand-alone solutions or deployed alongside other C3 AI applications. This quarter, we deployed C3 generative AI for industrial asset inspections at a large manufacturer. This application unifies data across unstructured inspection reports and structured data on asset performance, such as risk reports, corrosion analysis, work orders, etc., which makes these data easily and quickly accessible to plant operators.

Some of these inspection reports include scans of handwritten text and engineering diagrams that are over 50 years old. Using this application, the company has been able to streamline the day-to-day work of inspectors, reduce costly operational mistakes and risk, and accelerate their turnaround efforts and time. In Q1, we launched C3 Generative AI for government programs, which has an immense potential for federal, state, or local government agencies by eliminating service delays, reducing wait times, enhancing the effectiveness of contact centers, and improving the citizen experience. We’ve already signed a pilot with a state on the U.S.

East Coast and look forward to supporting public sector agencies across the board. It’s important to understand that the C3 generative AI applications are unique in the market. We provide the ability to interact with omnimodal data that is structured sensor data, databases, unstructured documents, images, embedded tables, leverage any LLM available in the market. For example, GPT 4.0, Gemini, Claude, Llama, Mistral, to name a few, and multiple specialized LLMs in the same application, offering full source traceability for both structured and unstructured data and granular enterprise access controls.

We also provide tools to enable data scientists to tune system responses for high accuracy in production with minimal hallucination, perform chain of thought, reasoning, author and execute mathematical functions, offer state-of-the-art LLM guardrails and protections, and orchestrate and chain together AI agents to perform high-value tasks, for example, to initiate workflows or write summaries. We provide out-of-the-box pipelines to synthesize results across AI agents, automatically detect and surface consistencies in underlying data, capture engine logs for auditability and traceability, provide tools for our customers, developers, and data scientists to configure their own custom generative AI pipelines, and offer fine-tuning services for embedding models and LLMs. C3 generative AI is also unique in its enterprise-grade support for operating in highly secure air gap environments. This is a prerequisite for defense intelligence and financial services customers.

I’ll now turn it over to Hitesh to cover the financials.

Hitesh Lath — Chief Financial Officer

Thank you, Ed. I will now provide a recap of our financial results and additional color on our business. All figures are non-GAAP unless otherwise noted. As Tom mentioned, total revenue for the quarter increased 21% year over year to $87.2 million.

Subscription revenue increased 20% year over year to $73.5 million, representing 84% of total revenue. As a reminder, our subscription revenue is comprised primarily of software licenses, Software as a Service offering, standard SEO support services, pilots and trials of our C3 AI applications or generative AI, and consumption-based pricing for which revenue is recognized over time. Our subscription revenue also includes revenue from software licenses for which ongoing maintenance and support is not required. And in accordance with ASC 606, the revenue is recognized when the license is made available to the customer.

Professional services revenue was $13.7 million. This represents 16% of total revenue in the first quarter of fiscal ’25 as compared to 15% of total revenue in the first quarter of fiscal ’24. We expect the professional services revenue to generally stay within 10% to 20% of total revenue for fiscal ’25. Gross profit for the quarter was $60.9 million and gross margin was 70%.

Gross margin for professional services remained high at over 90%. operating loss for the quarter was $16.6 million. Our operating loss was better than guidance due to continued focus on expense management. Our net cash provided by operating activities was $8 million.

Free cash flow for the quarter was positive $7.1 million. We were able to generate positive free cash flow during the quarter because of continued focus on cash management. We continue to be very well capitalized and closed the quarter with $762.5 million in cash, cash equivalents, and marketable securities, an increase of $12.2 million compared to Q4. At the end of Q1, our accounts receivable balance was $140.1 million, including unbilled receivables of $81.5 million.

Total allowance for bad debt remains de minimis at less than $400,000, and we do not have concerns regarding collections. The general health of our accounts receivable remains strong. During the first quarter, we signed 52 pilots, 117% increase from last year and up 53% from last quarter. At quarter end, we had cumulatively signed 224 pilots, of which 191 are still active.

This means they are either in their original three- to six-month term or extended for some duration or converted to a subscription or consumption contract or are currently being negotiated for conversion to subscription or consumption contracts. We continue to expect short-term pressure on our gross margins due to higher mix of pilots, which carry a greater cost of revenue during the pilot phase of the customer life cycle. We also expect short-term pressure on our operating margin due to additional investments we are making in our business, including in our sales force, research and development, and marketing spend. As we continue to make significant investments in the business, we expect to be free cash flow negative for Q2 and Q3 but remain on track to be free cash flow positive for Q4 and also for the full fiscal year ’25.

Now I’ll move on to our guidance for the next quarter. Our revenue guidance for Q2 is going to be $88.6 million to $93.6 million. We are maintaining our previous guidance of $370 million to $395 million for fiscal ’25. This implies a year-over-year growth rate of 19% to 27%, making C3 AI one of the fastest-growing companies in the software public company universe.

Our guidance for non-GAAP loss from operations for Q2 is $26.7 million to $34.7 million. We are maintaining our previous guidance of $95 million to $125 million for fiscal ’25. Now I’d like to turn the call back over to Tom.

Tom Siebel — Chairman and Chief Executive Officer

Thanks, Hitesh. Let me address path to profitability. Our cost of goods sold is substantially less than our cost of generating revenue. And as such, C3 AI is a structurally profitable business.

Our year-over-year revenue growth in Q1 was 21% and accelerating. Our year-over-year expense growth rate was 12%. In the coming years, we expect our revenue to generally grow at a greater rate than our expense growth rate. It follows that non-GAAP profitability is now simply a function of scale.

While we continue to invest in market share, we believe our revenue growth rates would generally exceed our expense growth rates. The expense and revenue lines will converge, crossing over to consistent non-GAAP profitability. At this time, we expect to be cash flow positive in Q4 fiscal year ’25 and for the entire year of fiscal year ’25. Now let’s talk about kind of the general area of the — I want to talk about the general enterprise AI market, and I want to talk about customer success in C3 AI.

We really are partners to our customers, often on speed dial, engaging with them multiple times a day to make them successful and self-sufficient. We’re not working from home, we are out there on the site with our customers every day, every week. We sit shoulder to shoulder, and we get into the details of their business to make sure that everything is running smoothly as it relates to their enterprise AI applications. We hold weekly executive reviews to track progress at the highest levels.

This proactive, boots-on-the-ground approach is what drives the customer satisfaction reflected in our Net Promoter Scores. This commitment to close hands-on collaboration is demonstrated in our partnership with Shell. Shell has over 100 C3 AI applications in development and deployment for everything from asset integrity to production optimization. We started working with Shell initially on predictive maintenance back in 2018.

And now, they monitor over 15,000 pieces of equipment with C3 AI. They estimate that this program alone generates this whole C3 AI program that they have written large that they call Shell AI has generated annual benefit to shell of $2 billion. And we’re not done. We continue to collaborate expanding into new use cases, including some service reservoir management and oil condition monitoring.

These applications, we expect to be all scaled out across multiple assets. This approach is also evident in our work with Con Edison. We began our partnership with Con Ed in 2017, initially focusing on the advanced metering infrastructure project. This is a project that enhances the operational efficiency, public safety, and customer satisfaction of their smart grid infrastructure, and it continues to scale.

Annual cost reduction uncovered is over $45 million. The project is exceeding expectations with a projected benefit of more than $3.2 billion over 20 years, $500 million more than originally projected. Now Con Edison is deploying generative AI for meter management and asset mapping, which addresses billing discrepancies and reduces mismappings on the electric grid and reduces cost and increases customer satisfaction. Customer success is at the core of why we built this company.

Now let’s take a moment here and think back OK? For those of you who’ve been around, OK, for a few decades, and they’ve got in touch with what’s going on with people. C3 AI is the original enterprise AI company, hard stop, OK? We began C3 AI in January of 2009, think about that, with the vision to develop a software platform and enterprise applications that allow organizations to exploit, what we believe, would be the computing platform of the future. And that included elastic cloud computing, the Internet of Things, big data, and predictive analytics. And we did this during the depth of the AI winter.

This was well before the advent of the GPU, before Azure existed, before GCP existed and when AWS was nascent. We invested into thousands of person-years in over a decade, OK, building the C3 AI platform, the first reference platform architecture for enterprise AI hard stop at the first, OK? And today, now over 90 C3 AI enterprise applications address the value chains of energy, government, defense, manufacturing, financial services, agribusiness, pharma, and others. We deploy these applications today in Europe, Asia, South America, North America, OK, and in governments around the world. Now 15 years later, the Elastic Cloud, the Internet of Things, big data, and predictive analytics have become ubiquitous.

Enterprise AI is broadly recognized as one of the largest and fastest-growing markets in the history of enterprise software. It is a mandate for every corporate and government leader today to harness the power of enterprise AI, and C3 AI is extraordinarily well-positioned to serve this large and rapidly growing market demand. C3 AI is today one of the fastest-growing companies in the public software universe. And most importantly, in this current cacophony of AI market hype, C3 AI is achieving among the highest levels of customer satisfaction for value realized in the enterprise software world.

OK. I refer you to our earnings supplemental deck today, OK, where we’re showcasing, OK, C3 AI’s Net Promoter Scores, benchmarking C3 AI against other leading enterprise software companies, OK, many of which purport to be — almost all of which purport to be, OK, AI companies. And this report is published by a third party called Comparable. The bottom line is our enterprise software companies are the most satisfied in the software industry, consistently driving unmatched value from our solutions.

Achieving this level of customer satisfaction doesn’t just happen, it is the result of relentless dedication, unwavering commitment, a thorough understanding of our customer needs, superior software technology, and deep, deep expertise in enterprise AI, honed over many years of excellence. In the final analysis, customer value realized will be the only criteria that will determine the leader in enterprise AI and C3 AI is exactly on track. Now I’d like to turn this over to the operator to begin our QA session. Thank you all.

Questions & Answers:

Operator

Thank you. [Operator instructions] Please stand by while we compile the Q&A roster. Our first question comes from the line of Patrick Walravens with Citizens JMP. Your line is open.

Patrick Walravens — Analyst

Oh, great. Thank you very much and congratulations. Hey, Tom, can you start out by just sort of characterizing what the tone of business was like for you guys in Q1? And specifically, I’m looking at your deal band chart where you had 71 deals and the average TCV is 700. So, if you multiply those together, you get like almost $50 million, which is up a lot.

So, just if you could just comment on the tone of business, that would be great.

Tom Siebel — Chairman and Chief Executive Officer

Pat, it’s pretty wild out there. I mean, I would say, particularly with the advent of generative AI. I mean I think it’s very difficult for people who are assessing these companies to really understand the complexity of what’s going on in the AI market, OK, where we have different flavors of enterprise AI, we have these generative AI applications that go from very kind of small, low-priced use cases to very high priced, high-value use cases. And honestly, it’s difficult to model that.

I mean this is not a simple business. As we enter this kind of new world of AI, I mean, it’s really complex. And we can’t simply multiply, we did these many widgets this quarter, and we’re going to that many widgets in the next quarter. And this is the growth rate of widgets.

This is the gross margin. And therefore, this is what the — we continue to be just amazed by the broad range of applications that we’re finding for enterprise AI, and I would say in generative AI, many of which we just couldn’t have anticipated. I would say like public sector, we didn’t anticipate that, and we just fell into a gold mine there, OK? Law firms, medical diagnostics is just fascinating.

Patrick Walravens — Analyst

Awesome. And Hitesh, if I could ask a follow-up for you. I think people are probably wondering given how strong the bookings seem to be why the guidance didn’t go up. How did you think about that?

Hitesh Lath — Chief Financial Officer

You’re talking about the guidance for the Q2, revenue guidance.

Patrick Walravens — Analyst

No, for the year, you kept it the same.

Hitesh Lath — Chief Financial Officer

Yeah. That still represents 19% to 27% revenue growth. it still makes us one of the fastest-growing companies in this public software company universe.

Patrick Walravens — Analyst

OK. Thank you, guys.

Hitesh Lath — Chief Financial Officer

Thank you.

Operator

Please stand by for our next question. Our next question comes from the line of Timothy Horan with Oppenheimer. Your line is open.

Timothy Horan — Analyst

Thanks, guys. On the subscription revenue has been a little lumpy here. On professional services, I know, Tom, you basically just said it’s very difficult to model out. But can you give us some color on the trends? Like is this a good jump-off point for the rest of the year? And then maybe just on the expenses, where should we be modeling and the expenses increased almost in the next quarter or two? Thank you.

Tom Siebel — Chairman and Chief Executive Officer

Let me address subscription versus services under ASC 606, it’s a little complex. Certain things that used to be called software and now are called services under the new guidance, and we comply with what the guidance is. That being said, we’ve guided that our services revenue would be 10% to 20% of revenue in any given quarter. Our services revenue was 16% in this quarter.

And so, we’re well within our guidance there. Before we kind of bemoan the fact the services were a little higher than they expected to be, let’s remember what services margins are at C3 AI. While our software certification margins are quite high 66%, OK, our services margin, everybody, you’ll recall, is in excess of 90%. So, services is a pretty darn good business.

And while we continue to be focused, I mean, we’re a licensing company, OK? We’re not one of these services companies pretending to be a software company. They’re one or two of them out there, OK? We’re not that bad, but we continue to be — but it will continue — for the next year or two, you can expect our services to bounce around in the 10% to 20%. It will probably average about 15%. But remember, our services margins are greater than 90%.

I think 93% is that the number I got. So, it’s good work if you can get it.

Timothy Horan — Analyst

So, was there any reclassification this quarter or one-time items or should the midpoint of 15% is kind of a good run rate going forward?

Hitesh Lath — Chief Financial Officer

No, no reclassification.

Timothy Horan — Analyst

OK. Great. And expense line items, anything to focus on the next quarter or two where we should see a pickup?

Hitesh Lath — Chief Financial Officer

Yeah. So, in terms of our expenses, we plan to continue to make investments in our sales force, R&D, as well as marketing efforts.

Timothy Horan — Analyst

OK. Great. Pretty much across the board. And just lastly, any change in the competitive dynamics out there? I mean who do you run up against most these days?

Tom Siebel — Chairman and Chief Executive Officer

This is Tom. Well, Ed, what is the competitive environment? You’re closer to it than I.

Ed Abbo — Executive Vice President, Chief Technology Officer

Yeah. I think the default or de facto competition is the information technology, the IT organization, the CIO trying to build these applications themselves. And those are our best prospects is ones that have tried to do data science and then scale that up across a large enterprise, typically figure out how difficult that is without the right data and AI platform. So, that is the de facto competition in the market for us.

Tom Siebel — Chairman and Chief Executive Officer

And those are just prospects a couple of years down the road because they all come crashing down across these — we have the CIO with 10,000 people in Bangalore, trying to build this thing out of piece/parts from hyperscalers, and invariably comes crashing down around him. And so, they’re just — we just put them in the pipeline two or three years down the road and they come back.

Ed Abbo — Executive Vice President, Chief Technology Officer

That’s right. Thank you.

Timothy Horan — Analyst

Thanks, guys.

Operator

Thank you. Please stand by for our next question. Our next question comes from the line of Mike Latimore with Northland Capital Markets. Your line is open.

Michael Latimore — Analyst

Hi, great. Thanks. The pilot growth was very strong sequentially year over year. Are the size of the pilots, the value of the pilots for standard and generative AI kind of as expected?

Tom Siebel — Chairman and Chief Executive Officer

The value of the pilots, the kind of the middle of the road, and I could be off here by 10% or 15%. But in the middle of the road pilot for enterprise AI application is $0.5 million, the middle of the road for a generative AI application is about $0.25 million. The value of the generative AI pilot usually takes three months to complete, enterprise AI pilot will take eight months to complete, OK? And then we go into contract negotiation and they go live. We’ve given guidance before that we expect about 70% of our pilots to convert to production contracts.

I think that’s about right. And honestly, the 30% that don’t convert — it’s not because many of these are enormously successful projects. It’s not because — they do not convert because the pilot wasn’t successful, they can’t convert because some genius CIO decides he’s going to try to build this himself out of some piece parts of a hyperscaler. And they’ll be back.

Michael Latimore — Analyst

Yeah. Got it. Got it. OK.

So, no change in pricing or value, it sounds like on pilots. And then in terms of the second quarter guidance, the midpoint is about 24% revenue growth, which is a pretty big step up from the growth you had this quarter. And I think the biggest step-up in the last four quarters, I believe. But is the — what gives you confidence in that improvement? Is it these pilots you just landed? Or is it professional services growth or big deals getting deployed? Just what gives you confidence in that acceleration?

Tom Siebel — Chairman and Chief Executive Officer

Using kind of the best professional judgment we have, OK, the confidence we gave is what we think is going to happen. Now we’ve been public, I think, for 15 quarters, and we’ve been right 15 out of 15 quarters. And I know that many of you are trying to model this business if you can model it, you’re better than I because there is a lot of moving parts here. And I think the most — the best indicator of what we’re going to do is what we guide you to.

I mean, you could pretty much take to the bank for each of the last 15 quarters. We’ve been pretty spot on with that. So, right now, that’s what we think we’ll do. That’s our best professional judgment.

And you’re going to be sure we’re going to be working diligently to meet or exceed that.

Michael Latimore — Analyst

All right. Thanks.

Operator

Thank you. Ladies and gentlemen, we will take our last question from the line of Kingsley Crane with Canaccord. Your line is open.

Kingsley Crane — Canaccord Genuity — Analyst

Hi, thanks for taking the question. Forty agreements with GCP, that’s spectacular. Fifty-one agreements with the partner network overall. So, could you speak to the partner efforts outside of GCP? What’s working well? What would you like to improve? And then is the GCP partnership as dominant from a bookings contribution perspective as it is in deal frequency? Thanks.

Tom Siebel — Chairman and Chief Executive Officer

I’m not sure Kingsley, I don’t think I have the bookings contribution data here. So, I can’t correctly answer that one. I would say that the relationship with GCP is great. The relationship with AWS is great.

We’re doing a lot of good work with AWS, with Microsoft, Azure. And I mean, we’re great partners for these guys. I mean what we do when they partner with us, we get the application up fast, the customer gets value, I mean they don’t make money when companies are building applications using their platforms, they make money when people are running their other applications. So, we’re consuming CPU resources, we’re consuming GPU resources, we’re consuming storage.

And they’re all great partners, they’re great companies. They’re wonderful to work with, and it’s a privilege for us to be able to partner with them.

Kingsley Crane — Canaccord Genuity — Analyst

All right. OK. That’s very helpful. And then last one, just to clarify.

For the state and local agreements, were most of those pilots?

Tom Siebel — Chairman and Chief Executive Officer

They all kind of started as pilots. Yes, in other words, I’m not sure which number you’re referring to. Did we refer to how many pilots there were and how many converted in the quarter, we said this?

Hitesh Lath — Chief Financial Officer

No. We don’t talk about the conversions. We have the number for how many pilots closed in the quarter, 52 —

Tom Siebel — Chairman and Chief Executive Officer

Kingsley, they almost all began as pilots, OK? They all begin as pilots. They go from, let’s say, one to three months, and then the great majority of them convert to production.

Kingsley Crane — Canaccord Genuity — Analyst

Makes sense. Yes, understood in this context. All right. Congrats on the quarter.

Tom Siebel — Chairman and Chief Executive Officer

Thank you. Thank you, everybody. I think this is the end of our call. We really appreciate your attention.

This is quite an adventure. I think we’re breaking ground in enterprise AI. I know we’re breaking ground in enterprise AI. And I could just tell you, for those of you who have visited us or those of you who have a chance to visit, it’s so exciting and it’s just palpable.

And so, we’re going to continue to get after it, and we thank you for your time. We thank you for your attention, and wish you all a good day.

Operator

[Operator signoff]

Duration: 0 minutes

Call participants:

Amit Berry — Investor Relations

Tom Siebel — Chairman and Chief Executive Officer

Ed Abbo — Executive Vice President, Chief Technology Officer

Hitesh Lath — Chief Financial Officer

Patrick Walravens — Analyst

Timothy Horan — Analyst

Michael Latimore — Analyst

Mike Latimore — Analyst

Kingsley Crane — Canaccord Genuity — Analyst

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