Business
How the AI Boom Is Changing San Francisco

On a sunny day in San Francisco, along the city’s waterfront, families dived into the wacky world of artificial intelligence inside the Exploratorium museum.
Visitors made shadow puppets for AI to identify, used AI to generate songs, asked chatbots questions and faced off with AI in a game in which players tried to draw images that only humans would recognize. A giant robot hand moved around and people peered into a video game chip.
They jotted down their hopes and worries about AI on cards displayed in the museum. Hope: AI will cure cancer. Worry: People will rely on AI to the point they can’t think for themselves.
“It sort of breaks down those guardrails, those big walls that people have put up around AI, and allows them to have a conversation with somebody else,” said Doug Thistlewolf, who manages exhibit development at the Exploratorium.
Art. Office space. Billboards. Protests. The AI craze has intensified in San Francisco, spreading through work and social life in what some have described as a new gold rush. The AI boom, coupled with the election of new Mayor Daniel Lurie, has also infused the city with optimism — tinged with anxiety. Some worry about the city’s high cost of living, and whether AI will replace workers as tech layoffs continue.
For years, Silicon Valley has been at the center of innovation with some of the world’s valuable tech companies such as Meta, Google, Apple and Nvidia locating their massive headquarters south of San Francisco. AI’s rise, though, has shone a bright spotlight on San Francisco , home to multibillion-dollar companies such as OpenAI, Scale AI, Anthropic, Perplexity and Databricks.
AI has long played a big role in consumer technology, helping to recommend social media posts, translate languages and power virtual assistants. But the popularity of OpenAI’s ChatGPT — a chatbot that can generate text, images and code — set off a fierce race to propel technology that touches industries from media to healthcare.
Companies are battling it out for talent, offering lucrative compensation to recruit top researchers and leaders, while investments in AI companies have surged.
In the first half of 2025, venture capital funding for AI companies in the San Francisco Metro area surpassed $29 billion — more than double the amount during the same period in 2022, data from PitchBook shows. As of Aug. 5 , VC deals for AI startups in the area, which includes San Francisco, Oakland and Fremont, made up 46.6 percent of funding for U.S. AI companies this year.
Exactly how this frenzy will shape the future of San Francisco, home to cable cars and robotaxis, remains to be seen. Ask ChatGPT what SF will look like in 10 years and it generates an image of the city’s skyline with futuristic architecture and flying saucers next to the Golden Gate Bridge.
AI has been a “bright spot” in the city’s economy, helping San Francisco to recover after retailers, office workers and some companies such as X (formerly Twitter) left the downtown area during and after the pandemic as remote work picked up.
“The economic impact is [AI companies] take more office space, they pay more taxes, they hire more people,” said Ted Egan, chief economist of the city and county of San Francisco.
Over the past five years, AI-related companies have leased more than 5 million square feet of San Francisco office space and the amount is projected to grow, according to CBRE, a real estate service and investment firm. The city’s office vacancy rate of 35.8 percent in the first quarter would be cut in half if these companies take up 16 million square feet of office space by 2030.
San Francisco resident Vijay Karunamurthy has seen the city’s boom and bust cycles unfold over the last 25 years while working at startups and tech giants such as Google and Apple.
In 2000, when he moved from Chicago to San Francisco for an engineering job at a data startup, he saw major business such as Pets.com collapse during the dot-com crash. Fueled by social media’s popularity, the city’s tech sector came roaring back only to take a hit during the COVID-19 pandemic.
Now the city is ascending yet again. Ambitious entrepreneurs, old and new, are advancing powerful artificial intelligence tools that could transform lives.
“That amount of energy being concentrated in San Francisco has just been huge for the city,” said Karunamurthy, 46, the former field chief technology officer at Scale AI, a data-labeling startup. “It means every single night there’s AI events, and if you go to a coffee shop, you’ll run into people working on AI.”
Still, there are plenty of AI skeptics. In late July, outside of OpenAI’s headquarters in Mission Bay, a small group of protesters including a person dressed up as a robot held up signs that said “AI will kill us all” and “AI steals your work to steal your jobs.”
Generative AI’s ubiquity has forced educators to rethink what and how they teach students in the classrooms.
Arno Puder, professor and chair of San Francisco State University’s computer science department, said generative AI represents a historic “paradigm shift.”
The longtime San Francisco resident is equally excited, but also a little scared, about how it will affect labor. Over the last two years, he’s seen student enrollment in computer science at the university drop amid tech layoffs and generative AI’s rise. As coding assistants reshape computer science jobs, the university launched a new undergraduate certificate in generative AI for the fall of 2026.
“Generative AI is a different beast,” Puder said. “That does make me worry a little bit, but if you ask me for a prediction on what services or what the world’s going to look like in a few years from now, I don’t know.”
AI’s rise has inspired the creation of new spaces throughout San Francisco where people can discuss technology’s benefits and risks.
Thistlewolf said creating the AI exhibit at the Exploratorium involved talking to workers and researchers from tech companies and universities. The exhibit, which runs through mid-September, took roughly a year and half to develop.
Backed by Anthropic, the San Francisco company that developed the AI chatbot Claude, the exhibit aims to educate people about AI but doesn’t shy away from the debate surrounding technology.
San Francisco resident Martha Chesley, 77, came to the exhibit with her grandchildren. Living in San Francisco for 50 years, Chesley sees potential benefits from AI companies coming to the city.
“If it brings people and money, it’s good for the city because right now we have a lot of closed storefronts,” she said. “Maybe there would be more money also for housing being built.”
Throughout the city, AI startups are broadcasting their mission loudly on billboards and ads displayed at bus stops and train stations. Messages include “Stop Hiring Humans. To Write Cold Emails” and “Droids ship software while you touch grass.”
AI ads could also be spotted in the Mission district, a neighborhood deeply rooted in Latino culture and history. The area, filled with popular taquerias, colorful murals and a park with a view of the downtown skyline, has struggled with homelessness like other parts of the city.
At a bus stop on 16th Street, an ad from AI startup Outset struck a positive tone: “Listen to humans. Don’t replace them.”
Founded in downtown San Francisco in 2022, Outset created an AI interviewer so researchers could quickly gather feedback from more people to better understand customer needs and improve products.
The company’s 36-year-old chief executive, Aaron Cannon , said before the rise of ChatGPT, he and his co-founder experimented with AI systems that can generate and understand human language and saw its potential.
“I don’t think either of us could have told you it was going to absolutely take over the world,” he said. The San Francisco resident said the city’s talent pool also makes it an attractive location for startups. He declined to disclose its finances but said the company, which employs 15 and counts Microsoft among its clients, is “growing fast.”
Throughout San Francisco, founders and real estate companies have dubbed certain areas as AI hubs.
Hayes Valley, a neighborhood with Victorian houses, boutique shops and trendy restaurants, bears the nickname ” Cerebral Valley,” a nod to the hacker houses and AI communities that popped up in the area.
Jamestown, a real estate and investment company, markets the Northern Waterfront an emerging AI hub after leasing more than 43,000 square feet of office space to AI companies. Some of the startups work on AI loan servicing or AI-powered lip syncing technology.
Located near public transportation, water and greenery, the fresh air and serene nature of the area has attracted AI entrepreneurs that want to collaborate in person, said Michael Phillips, principal and chairman of Jamestown .
“If you’re working on these fast to market, highly competitive products,” he said, “you really need to be together.”
©2025 Los Angeles Times. Visit latimes.com. Distributed by Tribune Content Agency, LLC.
Business
AI business 'wake-up call': teach workers or miss out – The Canberra Times

AI business ‘wake-up call’: teach workers or miss out The Canberra Times
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C3 AI Announces Fiscal First Quarter 2026 Financial Results
C3.ai, Inc. (“C3 AI,” “C3,” or the “Company”) (NYSE: AI), the Enterprise AI application software company, today announced financial results for its fiscal first quarter ended July 31, 2025. These results are consistent with the preliminary financial results the Company announced on August 8, 2025.
Fiscal First Quarter 2026 Financial Highlights
- Revenue: Total revenue for the quarter was $70.3 million.
- Subscription Revenue: Subscription revenue for the quarter was $60.3 million. Subscription revenue constituted 86% of total revenue for the quarter.
- Subscription and Prioritized Engineering Services Revenue Combined: Subscription and prioritized engineering services revenue combined was $69.0 million, constituting 98% of total revenue for the quarter.
- Gross Profit: GAAP gross profit for the quarter was $26.4 million, representing a 38% gross margin. Non-GAAP gross profit for the quarter was $36.3 million, representing a 52% non-GAAP gross margin.
- Net Loss per Share: GAAP net loss per share was $(0.86). Non-GAAP net loss per share was $(0.37).
- Cash Balance: $711.9 million in cash, cash equivalents, and marketable securities.
“The good news is we have completely restructured the sales and services organization, including new and highly experienced leadership across the board to ensure a return to accelerating growth and increased customer success at C3 AI, and even better, we have appointed an exceptionally talented new CEO to take the company to the next level and realize the full potential of the business. The bad news is that financial performance in Q1 was completely unacceptable. Having given this a lot of thought, I attribute this to two factors. One: it is clear that in the short term, the reorganization with new sales and services leadership had a disruptive effect. Two: as we have previously announced, I have had a number of unanticipated health issues. Unfortunately, this prevented me from participating in the sales process as actively as I have in the past. With the benefit of hindsight, it is apparent that my active participation in the sales process may have had a greater impact than I previously thought. That being said, as we enter Q2, we have new leadership in place, a restructuring of the sales and services organization completed, an extraordinarily large market opportunity, a superlative product offering, and exceptional levels of customer satisfaction, and I am confident the company is positioned to accelerate going forward,” said Thomas M. Siebel, Founder and Chairman, C3 AI.
Business Highlights
During the quarter, C3 AI restructured its global sales and services organization with the addition of new sales leaders across all business units, including a new Chief Commercial Officer, General Manager of EMEA, new senior leadership in North America, the U.S. Federal business, the C3 AI Alliances program, and the new C3 AI Strategic Integrator Program that offers the opportunity for a new and expanding OEM line of business. In addition, sales and services have been combined, again under new leadership, to provide a more seamless, high-touch customer experience with a consistent focus on realizing significant economic benefit rapidly from each C3 AI customer engagement.
- In Q1, the Company closed 46 agreements, including 28 initial production deployment agreements.
- The Company entered new and expanded agreements with HII, Newport News Shipbuilding, Signature Aviation, Lawrence Livermore National Laboratory, Gypsum Management & Supply (GMS), Nucor Corporation, Koch, Qemetica, Quest Diagnostics, Curtiss-Wright, Driscoll’s, the U.S. Army, the Missile Defense Agency, the U.S. Navy, and the U.S. Intelligence Community, among others.
- The Company expanded its footprint across State and Local Government, closing eight agreements across New Jersey, Indiana, New Mexico, Washington, and California.
C3 AI Strategic Integrator Program
- C3 AI launched the C3 AI Strategic Integrator Program (SIP) , an OEM initiative that enables partners to license the C3 Agentic AI Platform to rapidly build and commercialize Enterprise AI applications. The new SIP program is being met with enthusiastic reception by many system integrators and U.S. Federal service providers.
- Introduced in Q1, SIP offers the opportunity for C3 AI to develop a substantial network of third parties utilizing the C3 Agentic AI Platform to design and develop industry- and domain-specific Enterprise AI applications that they will market to their customers. The open architecture of the C3 Agentic AI Platform enables C3 AI to operate as an OEM and allows partners to take advantage of all the Company’s existing investments in data aggregation, data ontologies, and machine learning capabilities built over more than a decade, avoiding vendor lock-in. We believe this presents an enormous opportunity for growth, and it is a channel in which we will be investing substantially in the years to come.
Partner Network
- In Q1, the Company closed 40 agreements through its partner network.
- The joint 12-month qualified opportunity pipeline with partners increased by 54% year-over-year.
- C3 AI and Microsoft jointly closed 24 agreements, with customer wins across manufacturing and the public sector. Strong customer traction and expanded deal activity contributed to a 140% year-over-year increase in qualified pipeline.
- C3 AI and McKinsey & Company advanced their strategic alliance, jointly closing a new strategic customer agreement and driving momentum through QuantumBlack engineer trainings, C3 AI Accelerator sessions, and executive roundtables.
Customer Success
- Nucor Corporation , North America’s largest steel manufacturer and recycler, expanded its commitment with C3 AI in a multi-year partnership to build an enterprise-wide AI program across its steel mills, steel products, and raw materials operations. Initial deployments of the C3 AI Supply Chain Suite — C3 AI Demand Forecasting, C3 AI Inventory Optimization, and C3 AI Production Schedule Optimization, among others — running on the C3 Agentic AI Platform are live across multiple facilities, supporting and optimizing day-to-day planning, inventory, and scheduling decisions. Building on this success, Nucor is extending C3 AI to additional plants and use cases, including agentic AI, with a continued focus on throughput and working-capital efficiency across the value chain.
- Qemetica , a global leading chemicals company, partnered with C3 AI to launch its first enterprise-scale AI program. The initial production deployment in the Salt business unit applied the C3 AI Reliability application to increase production yield. Building on this success, Qemetica is scaling the predictive maintenance solution for up to 100 manufacturing assets across multiple use cases, marking the start of a broader AI transformation across the company.
Federal Business
- In Q1, the Company closed 12 agreements across the Federal sector, accounting for 28% of total bookings.
- The Company entered into new and expansion agreements with HII, Newport News Shipbuilding, the U.S. Department of Defense, the U.S. Army, the U.S. Intelligence Community, the U.S. Air Force, the U.S. Marine Corps, the U.S. Navy, and the Missile Defense Agency, among others.
- HII , America’s largest military shipbuilder, is expanding its partnership with C3 AI to accelerate shipbuilding throughput at its Ingalls and Newport News Shipbuilding divisions. The collaboration applies Enterprise AI across planning, operations, supply chain, and labor allocation to modernize production and strengthen U.S. Navy fleet readiness. Initial deployments at Ingalls demonstrated significant reduction in the extraordinary complex shipbuilding timelines, and these AI capabilities will now scale across HII shipyards.
- The U.S. Army Rapid Capabilities and Critical Technologies Office is deploying a contested logistics application built on the C3 Agentic AI Platform to support frontline vehicles operating in high-risk environments. The system integrates with the Army’s Human Machine Interface Formation platforms, using agentic and generative AI to predict part shortages, forecast fuel consumption, and project ammunition requirements. By centralizing logistics data and delivering real-time forecasts, the application enhances sustainment, readiness, and decision speed for Army formations in contested operations.
C3 Generative AI
- The Company closed nine agreements for C3 Generative AI, including six initial production deployment agreements, with Nucor, Peacock, Koch, the University of Southern California Shoah Foundation, Subsea7, and the U.S. Intelligence Community, among others.
- Filtration Group , one of the world’s leading filtration and separation science businesses, deployed C3 Generative AI within a business unit to accelerate and streamline its request-for-quotes response process. The C3 Generative AI e-mail agent automatically generates detailed, tailored drafts that reflect each customer’s request and requirements in minutes, reducing turnaround time, increasing capacity, and creating millions of dollars in recurring annual value.
- The Company further differentiated C3 Generative AI from other agentic market offerings by introducing agentic data extraction. C3 Generative AI now automatically extracts, structures, and validates data from unstructured formats — including presentations, PDFs, and spreadsheets — so organizations can analyze enterprise information previously locked in documents. At a global biopharmaceutical company, this capability streamlined the extraction and consolidation of experimental study reports, lowering costs while improving researcher access to high-quality, validated data.
- In contrast to a recent industry report that shows that only 5% of LLM pilots are successful, the majority of C3 Generative AI deployments are delivering compelling measurable economic benefit. For example, preliminary economic benefits that C3 AI customers are realizing from C3 Generative AI include: 20% increase in employee productivity; 80% reduction in inspection planning time; 14% reduction in average call center handling time; 85% reduction in procurement contract review time; and 90% labor savings in archive analysis.
Statement About Appointment of New Chief Executive Officer
“I am extremely pleased to announce the appointment of Stephen Ehikian as Chief Executive Officer of C3 AI, effective September 1, 2025. Stephen’s wealth of experience in both the private and public sectors, and domain expertise in all things AI, make him ideally suited to drive growth and realize the full potential of the C3 AI technology platform and portfolio,” said Thomas M. Siebel, Founder and Chairman, C3 AI.
As the Company previously announced, Mr. Siebel will remain engaged at C3 AI — now in the role of Executive Chairman — to assist Mr. Ehikian as necessary and focus on important partner and strategic customer relationships, with a continued eye on product strategy and direction.
Financial Outlook:
The Company’s guidance includes GAAP and non-GAAP financial measures.
The following table summarizes C3 AI’s guidance for the second quarter of fiscal 2026:
(in millions) |
Second Quarter Fiscal 2026 Guidance |
Total revenue |
$72.0 – $80.0 |
Non-GAAP loss from operations |
$(49.5) – $(57.5) |
Given the appointment of a new Chief Executive Officer and the recent restructuring of the sales and services organizations, the Company is withdrawing its previous full-year fiscal 2026 guidance. The Company will provide guidance for the third quarter of fiscal 2026 and full-year fiscal 2026 when it announces its financial results for the second quarter of fiscal 2026.
A reconciliation of non-GAAP guidance measures to corresponding GAAP measures is not available on a forward-looking basis without unreasonable effort due to the uncertainty regarding, and the potential variability of, expenses that may be incurred in the future. Stock-based compensation expense-related charges, including employer payroll tax-related items on employee stock transactions, are impacted by the timing of employee stock transactions, the future fair market value of our common stock, and our future hiring and retention needs, all of which are difficult to predict and subject to constant change. We have provided a reconciliation of GAAP to non-GAAP financial measures in the financial statement tables for our historical non-GAAP results included in this press release. Our fiscal year ends April 30, and numbers are rounded for presentation purposes.
Conference Call Details
Investor Presentation Details
An investor presentation providing additional information and analysis can be found at our investor relations page at ir.c3.ai .
Statement Regarding Use of Non-GAAP Financial Measures
The Company reports the following non-GAAP financial measures, which have not been prepared in accordance with generally accepted accounting principles in the United States (“GAAP”), in addition to, and not as a substitute for, or superior to, financial measures calculated in accordance with GAAP.
- Non-GAAP gross profit, non-GAAP gross margin, non-GAAP loss from operations, and non-GAAP net loss per share. Our non-GAAP gross profit, non-GAAP gross margin, non-GAAP loss from operations, and non-GAAP net loss per share exclude the effect of stock-based compensation expense-related charges and employer payroll tax expense related to employee stock-based compensation. We believe the presentation of operating results that exclude these non-cash items provides useful supplemental information to investors and facilitates the analysis of our operating results and comparison of operating results across reporting periods.
- Free cash flow . We believe free cash flow, a non-GAAP financial measure, is useful in evaluating liquidity and provides information to management and investors about our ability to fund future operating needs and strategic initiatives. We calculate free cash flow as net cash (used in) provided by operating activities less purchases of property and equipment and capitalized software development costs. This non-GAAP financial measure may be different than similarly titled measures used by other companies. Additionally, the utility of free cash flow is further limited as it does not represent the total increase or decrease in our cash balances for a given period.
We use these non-GAAP financial measures internally for financial and operational decision-making purposes and as a means to evaluate period-to-period comparisons. Non-GAAP financial measures are not meant to be considered in isolation or as a substitute for comparable GAAP financial measures and should be read only in conjunction with our condensed consolidated financial statements prepared in accordance with GAAP. Our presentation of non-GAAP financial measures may not be comparable to similar measures used by other companies. We encourage investors to carefully consider our results under GAAP, as well as our supplemental non-GAAP information and the reconciliation between these presentations, to more fully understand our business. Please see the tables included at the end of this release for the reconciliation of GAAP to non-GAAP financial measures.
Other Information
Professional Services Revenue
Our professional services revenue includes service fees and prioritized engineering services. Service fees include revenue from services such as consulting, training, and paid implementation services.
Prioritized engineering services are undertaken when a customer requests that we accelerate the design, development, and delivery of software features and functions that are planned in our future product roadmap. When we agree to this, we negotiate an agreed upon fee to accelerate the development of the software. When the software feature is delivered, it becomes integrated to our core product offering, is available to all subscribers of the underlying software product, and enhances the operation of that product going forward. Such prioritized engineering services result in production-level computer software – compiled code that enhances the functionality of our production products – which is available for our customers to use over the life of their software licenses. Per Accounting Standards Codification (ASC) 606, Prioritized engineering services revenue is recognized as professional services over the period in which the software development is completed.
Total professional services revenue consists of:
|
Three Months Ended July 31, |
||||
|
|
2025 |
|
|
2024 |
|
(in thousands) |
||||
Prioritized engineering services |
$ |
8,663 |
|
$ |
10,649 |
Service fees |
|
1,297 |
|
|
3,108 |
Total professional services revenue |
$ |
9,960 |
|
$ |
13,757 |
Use of Forward-Looking Statements
This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. The words “anticipate,” “believe,” “continue,” “estimate,” “expect,” “intend,” “may,” “will” and similar expressions are intended to identify forward-looking statements, although not all forward-looking statements contain these words. Forward-looking statements in this press release include, but are not limited to, statements regarding our market leadership position, anticipated benefits from our partnerships, our financial outlook for the second quarter of fiscal 2026, our ability to accelerate going forward, our sales and customer opportunity pipeline including our industry diversification, the expected benefits of our offerings (including the potential benefits of our C3 Generative AI offerings), the role and responsibilities of Mr. Siebel, our expectations with respect to the transition of the chief executive officer role to Mr. Ehikian, the expected benefits of the recent restructuring of our sales and services organizations, the expectations for our C3 AI Strategic Integrator Program, and our business strategies, plans, and objectives for future operations. We have based these forward-looking statements largely on our current expectations and projections about future events and trends that we believe may affect our financial condition, results of operations, business strategy, short-term and long-term business operations and objectives, and financial needs. These forward-looking statements are subject to a number of risks and uncertainties, including our history of losses and ability to achieve and maintain profitability in the future, our historic dependence on a limited number of existing customers that account for a substantial portion of our revenue, our ability to attract new customers and retain existing customers, our ability to successfully transition the role of chief executive officer to Mr. Ehikian and integrate Mr. Ehikian into the C3 organization, the ability of our restructured global sales and services organization to achieve desired productivity levels in a reasonable period of time, market awareness and acceptance of enterprise AI solutions in general and our products in particular, the length and unpredictability of our sales cycles and the time and expense required for our sales efforts. Some of these risks are described in greater detail in our filings with the Securities and Exchange Commission, including our Annual Report on Form 10-K for the fiscal year ended April 30, 2025, and other filings and reports we make with the Securities and Exchange Commission from time to time, including our Quarterly Report on Form 10-Q that will be filed for the fiscal quarter ended July 31, 2025, although new and unanticipated risks may arise. The future events and trends discussed in this press release may not occur and actual results could differ materially and adversely from those anticipated or implied in the forward-looking statements. Although we believe that the expectations reflected in the forward-looking statements are reasonable, we cannot guarantee future results, levels of activity, performance, achievements, or events and circumstances reflected in the forward-looking statements will occur. Except to the extent required by law, we do not undertake to update any of these forward-looking statements after the date of this press release to conform these statements to actual results or revised expectations.
About C3.ai, Inc.
C3.ai, Inc. (NYSE:AI) is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise.
Source: C3.ai, Inc.
C3.AI, INC. CONDENSED CONSOLIDATED STATEMENTS OF OPERATIONS (In thousands, except per share data) (Unaudited) |
|||||||
|
Three Months Ended July 31, |
||||||
|
|
2025 |
|
|
|
2024 |
|
Revenue |
|
|
|
||||
Subscription |
$ |
60,301 |
|
|
$ |
73,456 |
|
Professional services |
|
9,960 |
|
|
|
13,757 |
|
Total revenue |
|
70,261 |
|
|
|
87,213 |
|
Cost of revenue |
|
|
|
||||
Subscription |
|
41,481 |
|
|
|
33,292 |
|
Professional services |
|
2,336 |
|
|
|
1,755 |
|
Total cost of revenue |
|
43,817 |
|
|
|
35,047 |
|
Gross profit |
|
26,444 |
|
|
|
52,166 |
|
Operating expenses |
|
|
|
||||
Sales and marketing |
|
62,513 |
|
|
|
52,125 |
|
Research and development |
|
64,651 |
|
|
|
52,927 |
|
General and administrative |
|
24,099 |
|
|
|
19,700 |
|
Total operating expenses |
|
151,263 |
|
|
|
124,752 |
|
Loss from operations |
|
(124,819 |
) |
|
|
(72,586 |
) |
Interest income |
|
8,218 |
|
|
|
10,003 |
|
Other income (expense), net |
|
132 |
|
|
|
28 |
|
Loss before provision for income taxes |
|
(116,469 |
) |
|
|
(62,555 |
) |
Provision for income taxes |
|
300 |
|
|
|
272 |
|
Net loss |
$ |
(116,769 |
) |
|
$ |
(62,827 |
) |
Net loss per share attributable to Class A and Class B common stockholders, basic and diluted |
$ |
(0.86 |
) |
|
$ |
(0.50 |
) |
Weighted-average shares used in computing net loss per share attributable to Class A and Class B common stockholders, basic and diluted |
|
135,375 |
|
|
|
124,979 |
|
C3.AI, INC. CONDENSED CONSOLIDATED BALANCE SHEETS (In thousands, except for share and per share data) (Unaudited) |
|||||||
|
July 31, 2025 |
|
April 30, 2025 |
||||
Assets |
|
|
|
||||
Current assets |
|
|
|
||||
Cash and cash equivalents |
$ |
80,941 |
|
|
$ |
164,358 |
|
Marketable securities |
|
630,957 |
|
|
|
578,330 |
|
Accounts receivable, net of allowance of $877 and $877 as of July 31, 2025 and April 30, 2025, respectively |
|
113,925 |
|
|
|
137,226 |
|
Prepaid expenses and other current assets |
|
25,290 |
|
|
|
24,338 |
|
Total current assets |
|
851,113 |
|
|
|
904,252 |
|
Property and equipment, net |
|
76,600 |
|
|
|
79,298 |
|
Goodwill |
|
625 |
|
|
|
625 |
|
Other assets, non-current |
|
40,401 |
|
|
|
41,707 |
|
Total assets |
$ |
968,739 |
|
|
$ |
1,025,882 |
|
Liabilities and stockholders’ equity |
|
|
|
||||
Current liabilities |
|
|
|
||||
Accounts payable |
$ |
12,084 |
|
|
$ |
15,160 |
|
Accrued compensation and employee benefits |
|
45,396 |
|
|
|
53,868 |
|
Deferred revenue, current |
|
28,948 |
|
|
|
36,561 |
|
Accrued and other current liabilities |
|
24,863 |
|
|
|
26,295 |
|
Total current liabilities |
|
111,291 |
|
|
|
131,884 |
|
Deferred revenue, non-current |
|
985 |
|
|
|
— |
|
Other long-term liabilities |
|
57,639 |
|
|
|
55,695 |
|
Total liabilities |
|
169,915 |
|
|
|
187,579 |
|
Commitments and contingencies |
|
|
|
||||
Stockholders’ equity |
|
|
|
||||
Class A common stock |
|
133 |
|
|
|
130 |
|
Class B common stock |
|
3 |
|
|
|
3 |
|
Additional paid-in capital |
|
2,294,166 |
|
|
|
2,216,284 |
|
Accumulated other comprehensive (loss) income |
|
(74 |
) |
|
|
521 |
|
Accumulated deficit |
|
(1,495,404 |
) |
|
|
(1,378,635 |
) |
Total stockholders’ equity |
|
798,824 |
|
|
|
838,303 |
|
Total liabilities and stockholders’ equity |
$ |
968,739 |
|
|
$ |
1,025,882 |
|
C3.AI, INC. CONDENSED CONSOLIDATED STATEMENTS OF CASH FLOWS (In thousands) (Unaudited) |
|||||||
|
Three Months Ended July 31, |
||||||
|
|
2025 |
|
|
|
2024 |
|
Cash flows from operating activities: |
|
|
|
||||
Net loss |
$ |
(116,769 |
) |
|
$ |
(62,827 |
) |
Adjustments to reconcile net loss to net cash (used in) provided by operating activities |
|
|
|
||||
Depreciation and amortization |
|
3,415 |
|
|
|
3,119 |
|
Non-cash operating lease cost |
|
88 |
|
|
|
85 |
|
Stock-based compensation expense |
|
64,775 |
|
|
|
54,683 |
|
Accretion of discounts on marketable securities |
|
(2,811 |
) |
|
|
(3,936 |
) |
Other |
|
262 |
|
|
|
98 |
|
Changes in operating assets and liabilities |
|
|
|
||||
Accounts receivable |
|
23,302 |
|
|
|
(10,037 |
) |
Prepaid expenses, other current assets and other assets |
|
(230 |
) |
|
|
1,604 |
|
Accounts payable |
|
(2,931 |
) |
|
|
20,033 |
|
Accrued compensation and employee benefits |
|
3,343 |
|
|
|
(1,755 |
) |
Operating lease liabilities |
|
2,187 |
|
|
|
(498 |
) |
Other liabilities |
|
(1,538 |
) |
|
|
6,138 |
|
Deferred revenue |
|
(6,628 |
) |
|
|
1,335 |
|
Net cash (used in) provided by operating activities |
|
(33,535 |
) |
|
|
8,042 |
|
Cash flows from investing activities: |
|
|
|
||||
Purchases of property and equipment |
|
(760 |
) |
|
|
(924 |
) |
Purchases of marketable securities |
|
(206,492 |
) |
|
|
(230,924 |
) |
Maturities and sales of marketable securities |
|
156,081 |
|
|
|
190,298 |
|
Net cash used in investing activities |
|
(51,171 |
) |
|
|
(41,550 |
) |
Cash flows from financing activities: |
|
|
|
||||
Taxes paid related to net share settlement of equity awards |
|
— |
|
|
|
(2,945 |
) |
Proceeds from exercise of Class A common stock options |
|
1,289 |
|
|
|
3,127 |
|
Net cash provided by financing activities |
|
1,289 |
|
|
|
182 |
|
Net decrease in cash, cash equivalents and restricted cash |
|
(83,417 |
) |
|
|
(33,326 |
) |
Cash, cash equivalents and restricted cash at beginning of period |
|
176,924 |
|
|
|
179,712 |
|
Cash, cash equivalents and restricted cash at end of period |
$ |
93,507 |
|
|
$ |
146,386 |
|
Cash and cash equivalents |
$ |
80,941 |
|
|
$ |
133,820 |
|
Restricted cash included in other assets, non-current |
|
12,566 |
|
|
|
12,566 |
|
Total cash, cash equivalents and restricted cash |
$ |
93,507 |
|
|
$ |
146,386 |
|
Supplemental disclosure of cash flow information—cash paid for income taxes |
$ |
452 |
|
|
$ |
292 |
|
Supplemental disclosures of non-cash investing and financing activities: |
|
|
|
||||
Purchases of property and equipment included in accounts payable and accrued liabilities |
$ |
201 |
|
|
$ |
301 |
|
Right-of-use assets obtained in exchange for lease obligations (including remeasurement of right-of-use assets and lease liabilities due to changes in the timing of receipt of lease incentives) |
$ |
(166 |
) |
|
$ |
1,345 |
|
Vesting of early exercised stock options |
$ |
5 |
|
|
$ |
105 |
|
C3.AI, INC. RECONCILIATION OF GAAP TO NON-GAAP FINANCIAL MEASURES (In thousands, except percentages) (Unaudited) |
|||||||
|
Three Months Ended July 31, |
||||||
|
|
2025 |
|
|
|
2024 |
|
Reconciliation of GAAP gross profit to non-GAAP gross profit: |
|
|
|
||||
Gross profit on a GAAP basis |
$ |
26,444 |
|
|
$ |
52,166 |
|
Stock-based compensation expense (1) |
|
9,290 |
|
|
|
8,408 |
|
Employer payroll tax expense related to employee stock-based compensation (2) |
|
586 |
|
|
|
356 |
|
Gross profit on a non-GAAP basis |
$ |
36,320 |
|
|
$ |
60,930 |
|
|
|
|
|
||||
Gross margin on a GAAP basis |
|
38 |
% |
|
|
60 |
% |
Gross margin on a non-GAAP basis |
|
52 |
% |
|
|
70 |
% |
|
|
|
|
||||
Reconciliation of GAAP loss from operations to non-GAAP loss from operations: |
|
|
|
||||
Loss from operations on a GAAP basis |
$ |
(124,819 |
) |
|
$ |
(72,586 |
) |
Stock-based compensation expense (1) |
|
64,775 |
|
|
|
54,683 |
|
Employer payroll tax expense related to employee stock-based compensation (2) |
|
2,220 |
|
|
|
1,272 |
|
Loss from operations on a non-GAAP basis |
$ |
(57,824 |
) |
|
$ |
(16,631 |
) |
|
|
|
|
||||
Reconciliation of GAAP net loss per share to non-GAAP net loss per share: |
|
|
|
||||
|
|
|
|
||||
Net loss on a GAAP basis |
$ |
(116,769 |
) |
|
$ |
(62,827 |
) |
Stock-based compensation expense (1) |
|
64,775 |
|
|
|
54,683 |
|
Employer payroll tax expense related to employee stock-based compensation (2) |
|
2,220 |
|
|
|
1,272 |
|
Net loss on a non-GAAP basis |
$ |
(49,774 |
) |
|
$ |
(6,872 |
) |
|
|
|
|
||||
GAAP net loss per share attributable to Class A and Class B common shareholders, basic and diluted |
$ |
(0.86 |
) |
|
$ |
(0.50 |
) |
Non-GAAP net loss per share attributable to Class A and Class B common shareholders, basic and diluted |
$ |
(0.37 |
) |
|
$ |
(0.05 |
) |
Weighted-average shares used in computing net loss per share attributable to Class A and Class B common stockholders, basic and diluted |
|
135,375 |
|
|
|
124,979 |
|
(1) |
Stock-based compensation expense for gross profit and gross margin includes costs of subscription and cost of professional services as follows. Stock-based compensation expense for loss from operations includes total stock-based compensation expense as follows: |
|
Three Months Ended July 31, |
||||
|
|
2025 |
|
|
2024 |
Cost of subscription |
$ |
8,622 |
|
$ |
7,694 |
Cost of professional services |
|
668 |
|
|
714 |
Sales and marketing |
|
24,181 |
|
|
18,833 |
Research and development |
|
19,323 |
|
|
18,431 |
General and administrative |
|
11,981 |
|
|
9,011 |
Total stock-based compensation expense |
$ |
64,775 |
|
$ |
54,683 |
(2) |
Employer payroll tax expense related to employee stock-based compensation for gross profit and gross margin includes costs of subscription and cost of professional services as follows. Employer payroll tax expense related to employee stock-based compensation for loss from operations includes total employer payroll tax expense related to employee stock-based compensation as follows: |
|
Three Months Ended July 31, |
||||
|
|
2025 |
|
|
2024 |
Cost of subscription |
$ |
550 |
|
$ |
326 |
Cost of professional services |
|
36 |
|
|
30 |
Sales and marketing |
|
674 |
|
|
472 |
Research and development |
|
793 |
|
|
364 |
General and administrative |
|
167 |
|
|
80 |
Total employer payroll tax expense |
$ |
2,220 |
|
$ |
1,272 |
Reconciliation of free cash flow to the GAAP measure of net cash (used in) provided by operating activities:
The following table below provides a reconciliation of free cash flow to the GAAP measure of net cash (used in) provided by operating activities for the periods presented:
|
Three Months Ended July 31, |
||||||
|
|
2025 |
|
|
|
2024 |
|
Net cash (used in) provided by operating activities |
$ |
(33,535 |
) |
|
$ |
8,042 |
|
Less: |
|
|
|
||||
Purchases of property and equipment |
|
(760 |
) |
|
|
(924 |
) |
Free cash flow |
$ |
(34,295 |
) |
|
$ |
7,118 |
|
Net cash used in investing activities |
$ |
(51,171 |
) |
|
$ |
(41,550 |
) |
Net cash provided by financing activities |
$ |
1,289 |
|
|
$ |
182 |
|
View source version on businesswire.com: https://www.businesswire.com/news/home/20250903161507/en/
Business
Salesforce CEO Says Company Axed 4,000 Support Jobs Because of Agentic AI

Salesforce CEO Marc Benioff has become the latest Big Tech leader to note that the company he leads has shed jobs because of the impact of artificial intelligence.
On an entrepreneurship-focused podcast called the Logan Bartlett Show, Benioff said late last week that Salesforce has managed to cut 4,000 customer support roles after making itself “customer zero” for its agentic AI capabilities.
“I was able to rebalance my headcount on my support. I’ve reduced it from 9,000 heads to about 5,000, because I need less heads,” Benioff said.
AI agents are designed to handle tasks with little input from humans and are beginning to pop up across business functions inside enterprises. Benioff said Salesforce has already started to integrate agents across the organization. Customer support is but one function where workflows have been impacted.
“If we were having this conversation a year ago, and you were calling Salesforce, there would be 9,000 people that you would be interacting with globally on our service cloud, and they would be managing, creating, reading, updating, deleting data,” he said. “Now all of a sudden here we are a year later, and the million and a half conversations that are happening…have now bifurcated. Fifty percent are with agents; 50 percent are with humans.”
Benioff said that after he “rebalanced [Salesforce’s] support headcount,” he determined that he may be able to add different jobs inside other functions, particularly sales.
“I can now put those heads into sales, so I’ve increased my distribution capacity, and now I’m also making sure that I have much more efficiency and productivity in my lead generation and in the ability to actually work with customers that are contacting me,” he said on the podcast.
That penchant for a better sales pipeline has been echoed throughout many of Benioff’s public statements in recent months. On the podcast, he noted that, during his tenure as CEO, Salesforce has failed to return more than 100 million calls; he expects Salesforce’s current team, paired with its agentic fleet, can now return any call it receives.
In Benioff’s eyes, the productivity upgrades AI has enabled to date are only the start of his aspirations. He said the jobs of the future will be significantly impacted by AI’s continued proliferation.
“This is really the beginning of every part of the company having this kind of agentic augmentation. It’s a force multiplier. It’s a synergistic effect between me and the agents,” he said, noting earlier in the conversation that he is “on a mission to make Salesforce an agentic enterprise.”
Benioff said this summer that AI handles as much as half of the work that goes on inside Salesforce today.
Benioff told Bartlett that the emerging reality is that companies will need to put guardrails in place to simultaneously manage humans and agents. When Bartlett suggested that the concept of managing automated agents “feels a little dystopian,” Benioff countered, noting that Salesforce envisions the role of an “omnichannel supervisor that’s kind of helping those agents and those humans work together” continuing to rise inside the enterprise.
“I don’t think it’s dystopian at all,” he said. “I think that this is reality, at least for me.”
Salesforce is far from the first company to act on the changes AI have made to its business model, nor the first to state its belief that AI will impact jobs outlook in the coming years. Klarna and Microsoft have each cut thousands of jobs in an effort to go all-in on AI.
In June, Amazon CEO Andy Jassy said in a memo that he expects the continued rollout of AI systems to have a negative impact on the number of jobs available inside the company’s corporate workforce.
“As we roll out more generative AI and agents, it should change the way our work is done. We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs,” Jassy wrote in the memo.
Tobias Lütke, CEO of Shopify, has taken a similar stance—he indicated in a memo this year that AI usage will become part of employees’ performance reviews and noted that teams need to be able to justify why AI can’t do the work before hiring a human to do it.
“Before asking for more headcount and resources, teams must demonstrate why they cannot get what they want done using AI,” Lütke wrote at the time. “What would this area look like if autonomous AI agents were already part of the team? This question can lead to really fun discussions and projects.”
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