The market opportunity is immediate and we expect to seize it.
Tom Siebel’s C3.ai has been around the Artificial Intelligence game for far, far longer than the 2023 generative AI hype cycle. But that emerging tech is having an impact on the firm, both positive and negative it seems.
The company this week turned in a solid quarter – revenue of $72.4 million was up from $65.3 million a year ago, while a net loss of $64.4 million was reduced from $71.7 million for the comparable year ago period.
The firm also released 28 domain-specific generative AI models – $250,000 a piece – that target specific verticals, including aerospace, defense, manufacturing and healthcare among others, as well as some focused on business processes, such as sales and customer service. There is also a set of models targeted at some familiar enterprise providers, not least Oracle, Salesforce, SAP, ServiceNow and Workday.
Generative AI is a game-changer, said Siebel on the post-earnings analyst call:
We believe that the advent of generative AI may more than double the addressable market immediately available to C3.ai, and now with our new C3 Generative AI Suite of products out the door, you can expect that we will be investing in the coming quarters to promote, market and support these initiatives.
As for the new domain-specific offerings, buyers should look to providers with proven track records, he added:
Countless start-ups today are proposing companies based on generative AI for one industry niche or another, whether big doctors’ offices or insurance or automotive or pharmaceutical companies and what have you. They’re taking their pitches around the venture capitalists all up and down in Silicon Valley, and many are getting significant funding, in some cases with private market valuations in billions of dollars.
In each case, a handful of entrepreneurs propose to apply LLMs [Large Language Models] to develop market-specific, business process-specific, and application-specific LLM solutions. Well, C3.AI offers these solutions today and we offer them from a well-capitalized company with almost 1,000 seasoned professionals, partnered with a powerful market partner ecosystem and a global footprint.
Speculate to accumulate
Siebel observed that C3.ai closed eight generative AI deals in its most recent quarter and, importantly, can boast a qualified pipeline of 140 opportunities:
Over 140 to get out in less than six months. So putting in this perspective, our qualified pipeline of generative AI sales opportunities exceeds that of any other product in our product line that we’ve introduced and even all the products we’ve released in the last 14 years. This is big.
And here’s the negative rub, at least as far as the short termists on Wall Street are concerned – riding the generative wave is going to require increased investment and that put pressure on the C3.ai share price as Siebel announced:
After careful consideration with our leadership and our marketing partners, we have made the decision to invest in generative AI, to invest in lead generation, to invest in branding, to invest in market awareness, and to invest in market and customer success related to our generative AI solutions….while we still expect to be cash positive in Q4 this year and in fiscal year ’25, we will be investing in our generative AI solutions and at this time do not expect to be non-GAAP profitable in Q4, ’24.
Fighting talk
Away from the generative hype, C3.ai appears to be doing particularly well in the lucrative Federal Government market, citing the likes of the US Department of Defense (DoD), the Chief Digital and AI Officer (CDAO), the US Airforce, the US Marine Corps and the Defense Counterintelligence Security Agency. Siebel went into some detail about some of the work going on here:
Our business relationships with the Department of Defense are extensive and rapidly expanding. The DoD uses the C3.ai platform and C3.ai applications across many services, components, and combatant commands to realize significant improvement in readiness and decision advantage.
One example, beginning in 2017, we started to work for the US Air Force to improve the readiness and applied predictive maintenance for the E-3 Sentry, an aircraft that you probably know of as the AWACS. By fusing the handwritten maintenance notes with the flight logs and historical inventory, okay, and pilot logs, C3.AI readiness improved the Air Force’s legacy maintenance procedure substantially.
Following this initial project, the United States Air Force Rapid Sustainment Office selected C3.AI for additional readiness projects, an additional readiness project called Condition-Based Maintenance Plus, [CBM+], to apply similar analytics space predictive maintenance approaches to the B1 strategic bomber and other aircraft weapon systems. This configuration of C3.ai readiness for the United States Air Force called the Predictive Analytics and Decision Assistant or PANDA, went live into production and is now scaled out to over 16 Air Force aircraft weapon systems.
PANDA was subsequently selected as the system of record for all US Air Force predictive maintenance applications, he went on, noting that it is in fact the only such system of record for an AI application in the DoD that he’s aware of:
The goal of C3.ai PANDA is to realize up to a 25% increase in overall aircraft mission capability and when rolled out to all aircraft in the United States Air Force, this is budgeted to realize a $3 billion cost savings in maintenance and readiness.
Then there’s the firm’s work with the CDAO, the organization charged with selecting an AI system of record for the entire DoD. Siebel recalled:
We began working with them less than a year ago, initially to bring the C3.ai platform into production across a number of unclassified secret and top-secret enclaves as part of CDAO’s Advanta ecosystem, a centralized data repository for the entire Department of Defense.
Our first project showed how nodal analysis and contested logistics can radically improve when AI systems are applied to US Transportation Command or TRANSCOM data. This application took a simulation-based approach to provide options in response to global logistics disruptions.
We’re able to accelerate the time it takes to conduct this kind of nodal analysis from days to minutes. C3.AI has now been engaged less than a year later in a dozen projects through CDAO including contested logistics, strategic force readiness, supply chain visibility, commander’s dashboards, and combined joint all domain command and control.
My take
We are operating a disciplined business and we’re making this decision to invest in generative AI because we are confident that is in the best interests of our shareholders.
That’s not a message that is likely to appeal to a certain investor mindset, but if anyone knows how to play a long game in the enterprise tech space, it’s Tom Siebel. It’s hard to disagree with him – and believe me, I’ve got decades of practice at disagreeing with Tom Siebel! – when he says:
Even we could not have anticipated the size and growth rate of AI market that we now address. C3.ai has spent the last 14 years preparing for this opportunity and now the market is coming to us.
