C3.ai NYSE: AI reported first-quarter fiscal 2027 revenue of $52.4 million, above its prior guidance, as the enterprise AI software company said its restructuring efforts, federal-sector momentum and product focus helped improve operating efficiency.
The quarter ended July 31, 2026. Chairman and Chief Executive Officer Tom Siebel, who said he returned to the CEO role three months earlier with a mandate to turn around the business, characterized the company’s prior challenges as execution-related rather than stemming from its technology, market opportunity or balance sheet.
“One quarter into the turnaround, I believe the company is on track,” Siebel said. He said the company restructured its sales, product and services organizations, reset its cost structure and established clearer ownership, deadlines and weekly operating reviews.
Revenue, bookings and profitability measures
Chief Financial Officer Hitesh Lath said subscription revenue totaled $49.2 million, or 94% of total revenue. Professional services revenue was $3.2 million, including $1.8 million from prioritized engineering services. Combined subscription and prioritized engineering services revenue was $50.9 million, representing 97% of total revenue.
Siebel said bookings grew 73% during the quarter, while federal bookings increased 138% year over year. The company closed 22 enterprise agreements, including agreements with Heidelberg Materials, Johnson & Johnson, Ford Motor Company, Seaspan, Holcim, the U.S. Department of Defense, the Defense Logistics Agency and the U.S. Department of Agriculture.
- Non-GAAP gross profit was $26.1 million.
- Non-GAAP gross margin improved sequentially to 50% from 37% in the prior quarter.
- Non-GAAP operating loss was $36.2 million, $8.3 million better than the midpoint of guidance.
- Non-GAAP net loss was $30.7 million, or $0.20 per share.
- Free cash flow was positive $2.1 million, compared with negative $34.3 million a year earlier and negative $54.8 million in the prior quarter.
Lath attributed the improvement in gross margin primarily to cost-reduction actions. He said free cash flow benefited from lower quarterly cash expenses and strong collections. The company ended the quarter with $651.1 million in cash equivalents and marketable securities.
Restructuring and cost reductions
The company said its restructuring is nearly complete and is expected to produce about $135 million in annualized cost savings across the business. The program includes an approximately 40% reduction in headcount across organizations, as well as lower non-employee expenses.
Non-GAAP expenses totaled $88.5 million, down nearly $40 million from $128.1 million in the year-ago quarter and down more than $17 million from the preceding quarter, Lath said. Some of the savings are expected to be fully realized beginning in the second half of fiscal 2027.
The company expects non-GAAP gross margin to moderate to the mid-40% range next quarter as it selectively invests in a forward-deployed engineering organization. Siebel said C3 AI has maintained forward-deployed engineers for years and plans to increase near-term investment to help existing customers achieve their desired deployment outcomes.
He added that the company expects its C3 Code product to mitigate the need for such engineering resources over the medium and long term.
Product strategy and federal opportunity
Siebel said C3 AI is concentrating its offerings around its agentic AI stack, including the C3 Agentic AI Platform, C3 Generative AI, C3 AI Studio and C3 Code. He described C3 AI Studio as a control plane for developing and operating large-scale enterprise AI applications, while C3 Code is intended to create enterprise AI applications from natural-language prompts.
According to Siebel, C3 Code can aggregate data, build ontologies and pipelines, develop machine-learning models, design a user interface and deliver a working application without manual coding. He said the product remains in the early stages of marketing, but early users have responded favorably.
Siebel also said the company’s strategy is shifting from selling large enterprise AI applications built on its platform toward making application components available for reassembly on demand through the platform or C3 Code.
In the federal market, Siebel said the company sees opportunity both in greenfield projects and in replacing incumbent providers. He cited dissatisfaction among some customers with an unnamed incumbent’s products and business practices, while also pointing to government spending on AI-related technologies in intelligence and defense sectors.
Outlook
For the second quarter of fiscal 2027, C3 AI forecast revenue of $51 million to $55 million and a non-GAAP loss from operations of $34.5 million to $42.5 million.
For the full fiscal year, the company guided for revenue of $210 million to $240 million and a non-GAAP operating loss of $123 million to $155 million. Lath said the company expects free cash flow for the remainder of fiscal 2027 to broadly align with its non-GAAP operating-loss guidance range.
Siebel said his primary focus is on establishing consistent quarter-over-quarter revenue growth beginning in the third quarter, generating free cash flow from operations and reaching non-GAAP profitability. “We’re not going to ask the market to underwrite a story,” he said. “Our plan is to deliver results quarter over quarter and let those results speak for themselves.”
About C3.ai (NYSE:AI)
C3.ai, Inc is a leading enterprise software provider focused on delivering scalable artificial intelligence (AI) and Internet of Things (IoT) solutions to large organizations. The company's core offering, the C3 AI Suite, is a comprehensive, model-driven platform that unifies data ingestion, model development, and application deployment. Through its suite of tools, C3.ai enables customers to accelerate digital transformation initiatives by applying advanced machine learning, predictive analytics, and AI-driven insights across a broad range of business functions.
The C3 AI Suite provides a low-code environment for data scientists and application developers to rapidly design, test, and deploy enterprise-scale AI applications.
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