Also, if you are pessimistic about the stock, why not just get out (if you haven’t already)?

Curious on why you are investing (or still waiting)?

Literally AI ticker and stock hasn’t moved up in the recent AI frenzy. Compared to PLTR and other Ai stocks this one is sitting idle.

I hold 200 shares at a loss right now. Is this thing going to do something?

I am strongly considering investing in C3.AI, but I have some questions and comments on how the company is run. Ive watched all their videos, read their financial statements and learned about the founder. Yes, C3AI is unprofitable but are improving every quarter.

1. Why is C3AI shorted so much, when it has zero debt and ~750m worth of equity on the balance sheet?

2. What are the motivations of the founder and operator Thomas Siebel at age 75 being worth billions? He could be laying on a small private island with a mansion, his own yacht, sports car collections, sipping drinks and eating at Michelin restaurants every day.

3. Since knowledge of AI and computers, which Tom has 40+ years of experience, what will happen when he is impaired? Who is the successor and are they equally capable and driven to run the company? There might be a big key man risk here, especially because of the age.

4. Why does the CEO have to be compensated $ 31.7 million on an unprofitable company losing 70m per quarter?

Likewise the CTO makes $30m and the VP makes the same. I am sorry but 30m a year for a backup Vice President on a loss making company?

At least the CFO only makes 4m. If everone were making 4-5m the company could save 75m per year just on three positions. The best plan is to have a relatively modest salary and a big stock option plan similar to Elon Musk which incentives the operators to align with investors, which is organic growth and lean business.

If the Senior team does not cut its compensation plan, they will have to dilute shareholders in the future.

Which stock do you think will grow 100, 200, or 300 fold like NVidia did? I'm considering maybe Pony AI, C3.ai, and Baidu. What are your thoughts? Any other possible companies?

Do you think the future is in Driverless Vehicles? AI? Electric vehicles? Renewable energy? If so, which companies seem to have the best chance of growing like NVidia did?

Some other options are Soundhound, Li Auto, Rivian, Innodata, Alibaba, UiPath, Sensata, Aurora Innovation, Kodiak Robotics, Lucid Motors, Evgo, Blink Charging, Supermicro Computer, Unusual Machines, Microstrategy, iRobot, NIO, Stellantis, Formfactor, WeRide, Camtek, IonQ, Rubrik, Juniper, Monolithic, Cloudflare, Gartner, Datadog, Fortinet, Palantir, Accenture.

I noticed on the website there are 3-4 different offerings and was curious on which was is the biggest driver.

Also what is the business challenge that C3 AI is solving for companies?

Why has C3.ai's stock been consistently dropping recently, even though their recent earnings reports have been strong? I recall their stock price was nearly $50 after their recent reports.then decline！ Can someone explain this?

What is it like working at C3.ai? Would love to get specifics on what it's like working on the customer engineering team (i.e., solutions engineer).

Seeing brutal reviews on Glassdoor, but it would be nice to get more specific examples.

You all need to vote right now withhold your vote for the directors and vote against their compensation. In my opinion you should vote for the independent auditor so that the people reading the votes know you are specifically targeting them.

I just finished watching the recent Salesforce and Oracle keynotes, and honestly, I felt both disappointed and confirmed in my earlier thoughts. Disappointed because all I saw were more “AI agent builders” sitting on top of legacy systems — interesting demos, but not the kind of technology that can truly transform an enterprise. And confirmed, because it reminded me that C3.ai remains the only company with a proven, integrated, end-to-end AI platform built for mission-critical operations at scale. I wanted to explain why I think that matters, and what really separates a real enterprise AI platform from the AI toys we keep seeing everywhere.

Applying AI in the enterprise is not as simple as building a chatbot, an “agent,” or wrapping a large language model around a business system. To make AI work at industrial scale, an enterprise needs much more: a unified data and model architecture, lifecycle management, governance and security, real-time integration with hundreds of systems, continuous retraining and drift monitoring, high-availability operations, and the ability to deploy mission-critical applications that can actually run a business. It takes a foundation that brings together data integration, machine learning, business logic orchestration, domain expertise, and large-scale operational resilience — all working as one coherent platform. Anything less than that is not enterprise AI. It is a toy.

That is exactly the difference between what the industry giants are now releasing and what C3.ai has been building quietly and relentlessly since 2009. The new announcements from Salesforce, Oracle, Google, and Microsoft — exciting as they sound — are nothing more than incremental add-ons to legacy stacks. They offer “agent builders” and “AI copilots” that can execute small tasks or automate predefined workflows. These products sit on top of old architectures designed decades ago for CRM, ERP, or cloud hosting. They lack the deep abstractions and integrated services required to design, build, deploy, and manage predictive, prescriptive, and adaptive enterprise applications at scale. They are extensions, not transformations.

C3.ai, by contrast, is not adding AI to something old — it is AI, by design. It was founded as a pure AI play before the world even spoke of generative models. Its platform was architected from the ground up to ingest vast, messy enterprise data from hundreds of sources, unify it into a model-driven abstraction, and make it usable for building predictive applications in manufacturing, energy, defense, financial services, and beyond. Every line of code, every abstraction layer, and every automation pipeline in the C3.ai platform was built with one goal: operationalize AI across an enterprise, not in one use case, but in hundreds, with consistency, reliability, and speed.

Other vendors today speak of “AI agents.” But an agent without a data model, without governance, without production lifecycle, without operational resilience, is not an enterprise solution — it is a demo. C3.ai’s platform, in contrast, is already powering mission-critical systems where predictive algorithms directly drive revenue, optimize supply chains, prevent fraud, and ensure safety. It supports entire organizations, with thousands of users, millions of models, and petabytes of streaming data, all orchestrated under one model-driven architecture that keeps them consistent and traceable. It is not a chatbot; it is a complete nervous system for the enterprise.

C3.ai’s advantage was earned through hard work and real deployments in the field. Since 2009, it has been collaborating with the largest industrial, financial, and government organizations on the planet. Each implementation added new models, new integrations, and new domain knowledge — all folded back into the platform as reusable, configurable components. That accumulated intelligence — industrial algorithms, reference data models, best practices, and performance optimization patterns — now forms a massive library of turnkey applications and industry templates. These can be deployed rapidly, sometimes in weeks, because they encapsulate years of field experience and hard-won expertise. No new entrant can replicate that overnight.

Meanwhile, the legacy vendors are still wrapping yesterday’s architectures in glossy AI wrappers. Salesforce calls it Agentforce; Oracle embeds “AI agents” into Fusion; Google rebrands its LLM workspace as Gemini Enterprise; Microsoft markets Azure AI Foundry as a place to “build agents.” Each of these systems relies on data and processes trapped inside old silos — CRM records, HR transactions, ERP ledgers — and each depends on the same monolithic backbone that was never designed for AI. They can generate text or summarize a record, but they cannot orchestrate real-time predictive operations across hundreds of systems or provide a governed, model-driven environment for cross-domain learning. They are fragments, not frameworks.

In the end, the difference between C3.ai and the rest of the market is architectural and philosophical. The others are bolting AI features onto old software. C3.ai built a new software substrate where AI is the foundation. That is why C3.ai can deploy a fully functional predictive maintenance, fraud detection, or supply chain optimization solution in months, not years. That is why its applications scale from a pilot to global operations without rewriting a line of code. That is why it remains the only company offering a unified enterprise AI platform — not an AI accessory.

Every technology revolution produces imitators that mistake the surface for the substance. In this new era of enterprise AI, those who offer “agent builders” are playing with the surface. The substance — the deep, integrated, predictive, production-ready intelligence that can actually run an enterprise — has already been built. It is called C3.ai.

I've noticed a lot of chatter about C3.ai and how some folks are quick to call it a scam because it's changed its name a couple of times. Let's break it down and keep it simple.

First off, changing a company's name isn't a bad thing. Remember when Apple was Apple Computers? They changed to Apple Inc. when they started doing more than just computers. It's the same story with C3.ai.

C3.ai was founded in 2009, a period when artificial intelligence (AI) was, for the most part, dormant. The true potential of AI was not widely recognized until the seminal moment in 2012 when the ImageNet competition showcased the capabilities of deep learning, thanks to the pioneering work of Ilya Sutskever and his professor, Geoffrey Hinton. At its inception, C3.ai was named C3 Energy, reflecting its initial focus on solving complex problems within the energy sector using predictive analytics. This focus wasn’t misplaced; it was strategic, laying the groundwork for what was to come.

As the company evolved, so did its technology and ambitions. The integration and interpretation of data from millions of sensors in real-time—a feat achievable through advanced AI and predictive analytics—signaled a shift towards the broader applications of its platform. This shift warranted a new identity: C3 IoT, emphasizing its expertise in harnessing the Internet of Things (IoT) for transformative purposes. Later on, they realized "IoT" made some people think they were all about making gadgets, which wasn't the case. They were using AI to make sense of massive amounts of data and help businesses. So, they landed on C3.ai, which is a perfect fit for what they do: using AI to tackle big challenges.

Saying C3.ai is not trustworthy because of a couple of name changes is missing the whole picture. It's like not seeing the forest for the trees. These changes show they're adapting and growing, which is exactly what you want in a tech company.

In a nutshell, C3.ai's journey from focusing on energy to becoming a leader in AI is a story of evolution and smart pivoting, not a red flag. It's a sign of a company that knows when to shift gears and head in a new direction to stay ahead.

So, let's not get caught up in superficial judgments. C3.ai is on to something big, and it's more than just a name.

I have an offer from capital one in Richmond VA, and offer from C3 AI in the Bay Area. C3 has about 30 k higher first year total comp because of RSUs, but it that’s because Capital One has much better signing bonus. After first year, the difference becomes about 60k TC difference.

C3 feels riskier and the Bay Area is obviously a lot more expensive. It also seems like C3 is worse for WLB. I was wondering about resume value between these two companies and which one would be better to take. Also if anybody has any idea on whether C3 equity is likely to grow long term, that would be a big factor since it’s a decent portion of the pay.

If anybody has any suggestions on which job you would take it would be appreciated.

Is anyone bullish on this stock? I’m reading differing opinions. A large group thinks it’s surging recently because of chatgpt only and is not a good long term hold. Their financials aren’t great right now but they’re new. Is this a short term or long term hold in your opinion. Or neither

$ai is getting close to the buy levels of early last year. Is there still enthusiasm for c3ai?