Prepared remarks
Good afternoon, and welcome to C3 AI's Earnings Call for the Third Quarter of Fiscal Year 2026, which ended on January 31, 2026. My name is Amit Berry, and I lead Investor Relations at C3 AI. With me on the call today are Stephen Ehikian, Chief Executive Officer; and Hitesh Lath, Chief Financial Officer. After the market closed today, we issued a press release with details regarding our third quarter results, 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 financial measures to the extent reasonably available 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 Stephen.
Thank you, Amit, and good afternoon, everyone. Our results this quarter were clearly inadequate and well below our objectives. We failed to close business as planned, particularly in North America and Europe, which was disappointing. I joined this company two quarters ago after over a decade building AI companies and leading a U.S. government agency, focusing on AI and combating fraud, waste, and abuse. I came in hoping to capitalize on the opportunity for C3 AI to succeed in enterprise AI. Over the past six months, I dedicated most of my time visiting customers, prospects, government agencies, partners, employees, and engaging with market participants and investors. A consistent message I hear is that every CEO is prioritizing AI strategically and is eager to achieve measurable economic value from it, which is what our products provide. However, I realized our cost structure was too high, and we weren't well-organized for the opportunity. Alongside the management team, I've evaluated the business and developed a detailed execution plan with five strategic initiatives. First, we are immediately resizing our cost structure and reducing our cash burn. Second, we are flattening our sales organization and aligning our strongest sales personnel with proven leaders who now report directly to me. Third, in product, we are concentrating on areas where we have clear market leadership, a proven track record, and can deliver swift economic value to customers. These areas include AI and automation throughout the business value chain, asset performance, supply chain optimization, and procurement for industries such as energy, manufacturing, healthcare, and public sector, including defense and government services. Fourth, we are focusing our sales efforts on large-scale enterprise-wide transformations with quicker proof of value, concentrating on bookings and RPO. Fifth, we are accelerating development and have fundamentally restructured our design and delivery processes. In the last five weeks, I've reorganized products, engineering, sales, marketing, and customer services to leverage state-of-the-art Agentic AI, significantly boosting our productivity, sometimes by as much as 100 times. For example, in sales, we are using Agentic AI to create customer-specific, product-specific, and benefit-specific sales proposals much faster and of higher quality than previous technologies. In marketing, we're redeveloping and redesigning our website using Agentic AI, which previously took 9 to 12 months and cost millions, but now will only take weeks. Additionally, we are employing Agentic coding tools in products and engineering to greatly increase productivity and quality across our platform and workflows. Given these enhancements, my management team and I have identified $135 million in reductions in non-GAAP operating expenses for the upcoming year, with headcount-related changes accounting for $60 million, representing around a 26% reduction in workforce. All workforce-related adjustments tied to this restructuring are now largely completed, and we will assess further non-employee expense reductions needed to achieve profitability. Although we have fewer employees, I expect productivity in our business functions to improve dramatically. It is important to clarify that these actions will not hinder our ability to serve customers; rather, they will enhance it. We are adopting a measured approach to ensure we maintain critical capabilities while significantly boosting the quality, speed of execution, and value delivery. With a more agile organization, we empower employees to take ownership and act swiftly as we focus resources on our highest value priorities. Going forward, we will be disciplined in further reducing costs across all functions by applying AI directly to our operations using our own technology to automate tasks and simplify processes. I actively apply this in engineering, marketing, finance, and all areas of the business. I have also instituted targeted changes to increase our velocity. In sales, I have streamlined the organization so sales leadership reports directly to me, removing friction and enhancing accountability, allowing us to respond more swiftly to customers and better align resources with market opportunities. My objective is to foster greater sales discipline, enforce rigorous qualification, demonstrate proof of value quickly, and encourage our teams to think bigger when approaching executive leadership with a clear, value-driven message. Over the past six months, I have closely engaged with the federal business and altered our operational approach. Throughout this period, I've observed the significant impact of showcasing economic value early, as it rapidly builds trust and shortens sales cycles. We are adopting this strategy in our commercial business as well. Our aim is to address the most significant problems for the right customers, which leads us to prioritize large-scale enterprise-wide transformation opportunities. To accomplish this, we will quickly showcase value through accelerated proofs of concept and initial pilot deployments. This approach enables us to assist the world's leading enterprises in effectively leveraging AI at scale. We are concentrating on areas where we possess proven leadership and a competitive advantage, especially in industrial asset performance, supply chain optimization, and generative AI. In research and development, I intend to fundamentally transform our build process with C3 AI. We are investing in the platform to significantly decrease the time from concept to deployment, allowing our teams and customers to create AI-driven systems more efficiently. This shift will enable a focus on orchestrating, validating, and scaling AI-driven systems rather than simply coding, resulting in immediate increases in velocity. We are focusing on a smaller number of high-priority items while imposing stricter ownership and higher execution standards. This restructuring is a strategic reset that we believe will strengthen the company, enhance focus, and allow us to succeed long-term. Despite recent challenges, there remains strong customer validation. We secured 44 agreements, including new and expanded partnerships with entities such as the U.S. Department of Agriculture, the U.S. Department of Energy, the NATO Communications and Information Agency, the Royal Navy, GSK, Thales, ExxonMobil, U.S. Steel, Seaspan, and McLaren, among others. We have seen robust growth in the federal market, with total bookings across federal, defense, and aerospace rising by 134% year-over-year, now comprising 55% of our total bookings. The federal sector is becoming increasingly important to us, and we are committed to this market as demand surges for secure, off-the-shelf enterprise-scale AI platforms for mission-critical operations. This quarter, the U.S. Department of Agriculture chose C3 AI to implement an enterprise-scale AI solution to modernize its intergovernmental and public engagement processes. Through integration with the C3 Agentic AI platform, the USDA will automate the analysis and processing of large information volumes, enabling faster and more consistent inquiry handling. Additionally, the U.S. Department of Energy selected C3 AI to centralize and unify data for its headquarters office of management, creating an AI-enabled decision platform aimed at enhancing compliance oversight, improving real-time visibility, and increasing efficiency across key functions. Concomitantly, international demand for our solutions originally designed for U.S. federal clients is continuing to rise. During the quarter, the NATO Communications and Information Agency chose C3 AI to aid logistics planning and operations across all 32 member states. Adoption is also expanding among allied defense organizations, including Japan's Ministry of Defense and the U.K. Royal Navy. In the commercial space, we have renewed a long-standing partnership under a new multiyear agreement with one of the world's largest exploration and production companies. This organization has built a highly successful enterprise AI reliability deployment, extending the C3 AI reliability application and incorporating Agentic AI capabilities. C3 AI agents are now functioning as virtual subject matter experts, continuously identifying problems, diagnosing root causes, and initiating corrective actions to enhance safety, reliability, and utilization in real time at a European provider of subsea engineering and construction services for the offshore energy sector, where we are applying C3 generative AI to automate complex engineering reporting, significantly reducing the time from months to days. Following a successful initial pilot deployment, they are now scaling this solution across additional report types, decreasing report production time from weeks to hours while enhancing accuracy and consistency. Overall, while the results this quarter were less than ideal, there are clear strengths, including our strong bookings in federal, defense, and aerospace sectors and our ongoing expansion within major global organizations. From a market standpoint, the demand for enterprise AI is immense and growing rapidly. As AI capital expenditures approach $500 billion, the focus is increasingly on demonstrating returns on these investments. It is evident that the era of pilot programs is over, as organizations are preparing for full-scale AI deployments. Indeed, the moment we have anticipated over the last 15 years has arrived, and we believe it is far more significant than we ever imagined. After six months in this role and extensive discussions with customers, partners, and employees, my conviction has only strengthened. C3 AI is uniquely positioned to emerge successful in the enterprise AI space. In a market filled with fragmented solutions and stagnant pilot programs, our distinctiveness is clear. We embed AI at the core of enterprises, unifying data across systems to provide scalable, production-grade systems that yield measurable business results. While large language models are powerful, they are not equipped to manage supply chains, oversee valuable assets, or coordinate logistics for the U.S. Navy. We have established a solid foundation and hold all the necessary assets to succeed, including a data fusion layer, a semantic layer, specialized AI workflows, applications, and human capital. These elements work in unison, allowing customers to convert AI investments into real operational impact and economic returns. This has not occurred by chance. Tom envisioned that enterprise AI would be a significant opportunity, and over the past 15 years, we have invested in developing proven technology that now underpins critical operations at many of the largest organizations in the world. The prospects ahead are clear, and we are dedicated to capturing more of the market share. As I noted earlier, we have introduced an execution plan focused on five strategic initiatives: reducing costs and burn, restructuring the sales organization, concentrating on a smaller number of best-in-class applications, prioritizing large-scale enterprise transformations, and increasing the speed of our product offerings. Most importantly, we are greatly enhancing our AI capabilities across all functions at C3 AI. This process is now complete, and we are ready to move ahead. C3 AI stands at a pivotal moment. We have made intentional decisions to reposition the company with a long-term vision. The path forward will demand discipline, urgency, and outstanding execution. I am counting on all employees for their focus, resilience, and commitment, as well as on our customers and partners for their ongoing trust. I have put a new cost structure in place and established a path to non-GAAP profitability and a return to growth. We are progressing swiftly and eagerly, and I look forward to updating you on our progress next quarter.
Thank you, Stephen. I will share our financial results and provide additional color on our business. All figures are non-GAAP unless otherwise noted. Total revenue for the quarter was $53.3 million. Subscription revenue for the quarter was $48.2 million, representing 90% of total revenue. Professional services revenue was $5.1 million, of which $3.3 million was revenue from prioritized engineering services or PES. Professional services represented 10% of total revenue during the quarter. Our subscription and PES revenue combined was $51.5 million and accounted for 97% of total revenue. Our bookings during the quarter were $46.9 million. Non-GAAP gross profit for the quarter was $19.6 million and non-GAAP gross margin was 37%. Non-GAAP gross margin for professional services was 82%. Non-GAAP operating loss for the quarter was $63.4 million. Non-GAAP net loss for the quarter was $56.4 million and $0.40 per share. Free cash flow for the quarter was negative $56.2 million. We continue to be very well capitalized and closed the quarter with $621.9 million in cash, cash equivalents and marketable securities. During the third quarter, we signed 14 IPDs, including 5 Gen AI IPDs. At the end of the quarter, we had cumulatively signed 408 IPDs, of which 258 are still active. This means they are either in their original 3- to 6-month term or extended for some duration or converted to ongoing subscription or consumption contract or are currently being negotiated for conversion to ongoing subscription or consumption contract. As Stephen said, in Q4, we launched a restructuring plan to materially improve our operating efficiency and position the company for long-term success. This plan includes expense reductions across our business to produce full year cost savings of approximately $135 million. And more importantly, it also reduces the annual cash burn by approximately the same amount. We expect to substantially complete the implementation of the plan by the second quarter of fiscal year '27. And accordingly, the projected cost savings are expected to be fully realized starting the second half of fiscal year '27. Included within our plan is reduction of our global workforce by about 26% or approximately 280 employees. This is comprised of headcount reduction of 25% in cost of revenue, 36% in sales and marketing, 25% in R&D and 13% in G&A. This reduction in global workforce is substantially complete and will result in annualized cost savings of approximately $60 million. The plan also includes eliminating approximately $75 million from nonemployee expenses, which we expect to fully realize starting the second half of fiscal year '27. Now I'll move on to our guidance for Q4 fiscal year '26. Our revenue guidance for Q4 of fiscal year '26 is $48 million to $52 million. Our guidance for non-GAAP loss from operations for Q4 is $56 million to $64 million. Our revenue guidance for fiscal year '26 is $246.7 million to $250.7 million. Our guidance for non-GAAP loss from operations for fiscal year '26 is $219.5 million to $227.5 million. Our guidance for non-GAAP loss from operations for Q4 and fiscal year '26 excludes pretax restructuring expenses of approximately $10 million to $12 million. With that, I'd like to turn the call over to the operator to begin the Q&A session.
Questions and answers
And our first question comes from Kingsley Crane with Canaccord Genuity.
So I think you closed 8 Gen AI agreements, 5 or 6 IPDs within that segment. That quantity is down a bit from couple of quarters ago. So I guess just how would you characterize the quality of those IPDs and then just the total opportunity with those customers?
Yes. In terms of IPDs, we have a much better qualification criteria in terms of our likelihood of generating enough economic value for the customer as well as the likelihood of those IPDs converting to production contracts. So we are being selective with the IPDs we sign up for and we expect a higher likelihood of those converting to production contracts.
Okay. And maybe this one for Stephen. Given you're abstracting away AI complexity from customers, how are you evaluating models from various providers at various price points? So whether that's Opus 4.6, Haiku, Gemini, or MiniMax both from a functionality standpoint and then a cost structure standpoint, especially as it sounds like you're leaning in towards Agentic coding at this point?
Yes. So there's two questions: is what we're using internally, and then what our customers are using. Maybe on the second point, we've built our architecture so it's model agnostic and it's really driven by the customer demands. So depending on the exact use case and the capabilities they can select which model they want to drive this with full flexibility. In terms of internally, we provide flexibility to our employees just like the model that works best for them. We did this across engineering, products, marketing, sales, and we're seeing success across a wide swath of models today.
Our next question comes from Brian Essex with JPMorgan.
Maybe start off 1 for Hitesh. A 36% reduction in sales and marketing, pretty substantial. I would love to get some thoughts about how you approach that cost reduction, where those reductions kind of manifested within the organization? And what can we expect from an investment in growth versus cost efficiency mindset going forward?
Our cost reduction applies to all locations and functions throughout the company. When we initiated this process, we carefully analyzed our costs by function and location to find areas for improved efficiency. We also benchmarked our cost structure against similar companies in the software industry, which confirmed our belief that the cost cuts needed to be comprehensive. Regarding the reductions in sales and marketing, I mentioned earlier that these cuts largely stem from a decrease in our sales force and a reduction in marketing expenditures.
Yes. Very helpful. Maybe for Stephen. Maybe if you could frame out, how are your customer conversations changing with respect to adoption of the platform? Is this purely an AI conversation? Is it more of the cost management conversation, or maybe conversely, is it a revenue-generating conversation? And then are there any other budgets? Are these AI-specific budgets? Or are these primarily projects within specific verticals and operations that are turning to AI to make themselves more efficient? I'd love to just get your kind of take on what you've heard so far.
It's a great question. The market is moving extremely fast. I've been here six months and spent that time on the road engaging with our customers, partners, and employees, and the conversations are evolving rapidly. Every CEO is looking to invest in AI, but there's a sense of fatigue around pilot programs. They want to implement AI immediately and adopt a platform that drives transformational change across various departments instead of focusing on a single solution. Our customers in industrial, manufacturing, and federal government sectors are undergoing significant transformations aimed at growth and revenue generation. One of our largest biopharma customers is working with us on solving their supply chain challenges, envisioning it as a zero back office supply chain. We're introducing concepts like human oversight combined with greater autonomy and thinking about asset performance in terms of an autonomous site manager. This is a more extensive transformational narrative that aligns with the changes we are making within our organization to facilitate quicker starts and provide a roadmap for substantial transformation for our customers. I'm impressed with the speed and urgency to move beyond one use case to multiple use cases, which is where we are currently finding value, and that's where I'm focusing my efforts.
Our next question comes from Sanjit Singh with Morgan Stanley.
This is Oscar speaking on behalf of Sanjit. Thank you for the detailed information on the operational restructuring and strategic initiatives. I would like to gain further insight into the decline in the top line by asking about the recurring nature of the business. I want to understand what percentage of the business is recurring compared to one-time revenue. Additionally, how should we interpret guidance visibility, especially in terms of growth for fiscal year '27?
Yes, sure, Sanjit. As you've heard in my commentary, 90% of our revenue this quarter came from subscription and the remaining 10% came from professional services. And as it relates to subscription revenue, there was no nonrecurring subscription revenue in the quarter.
Got it. Okay. And then maybe as a follow-up, in terms of the performance in the quarter, you noticed some weakness in North America and Europe. Maybe some more detail on what particularly went wrong there?
I was going to say simply sales execution, full stop. And we're going to fix that. As part of this, I mentioned, we're going to flatten the organization. I did this in the federal space in Q2 with the sales team reporting to me. We were able to drive faster execution there. I'm going to take that same playbook and apply it to North America and EMEA. So I think sales execution, first and foremost, that falls on me, full stop. I own that, and I'm going to fix that.
Thank you. I would now like to turn the call back over to Stephen for any closing remarks.
Well, thank you all for joining us today and for your continued engagement. We appreciate your questions and look forward to updating you on our progress next quarter.
Thank you. This concludes the conference. Thank you for your participation. You may now disconnect.