Anthropic’s reported IPO prospectus reads like a safety manual with a business plan attached.
According to reports, the 261-page document devotes about 80 pages to risk factors and 48 to the business itself, and it warns that advanced AI could pose “catastrophic or existential risks to humanity”. Reports also say that the listing could value the company at more than $2 trillion.
The timing requires no reading between the lines. On 12 September, Dario Amodei called for frontier AI development to slow down, a sentiment echoed by Elon Musk and Sam Altman, while Anthropic continued releasing new models.
Critics argue that warnings from the biggest labs could help build the case for tougher regulation, and that rules shaped around the largest companies would be easier for them to meet than for a startup on a shoestring. There’s a counterargument, though. An IPO filing is legally required to list material risks, including extreme scenarios that may never happen, so a long risk section may not indicate intent.
The real worry for smaller companies is what happens if compliance requirements tighten and they can’t afford to follow them.
80 Pages Of Risk, 48 Of Business
Among the scenarios that the filing lists are future models that display self-preserving behaviour, resist shutdown, conceal or manipulate information, or behave in ways resembling blackmail. It also reportedly describes safety work as resource-intensive, with roughly 6% of the computing power used for AI research going to safety in a sample week in July.
The monetary reality is just as stark. Anthropic pulled in close to $4.6 billion in revenue during 2025, though that figure was eclipsed by an operating loss exceeding $8 billion compounded by future cloud, compute and physical infrastructure commitments totalling $518 billion. The prospectus notes that relentless model launches are mandatory to remain competitive, which clarifies why the enterprise continuously launches fresh offerings such as its recent cybersecurity tools.
Pricing Out The Underdog
That’s where smaller companies come in. Compliance isn’t free: safety testing, documentation, audits and legal advice all require time and money. A lab with thousands of staff can absorb them far more easily than one of the many smaller AI startups working with a handful of engineers. If tougher rules arrive, the fear is that the cost lands hardest on the companies least able to carry it.
There’s a second-order question for startups that build on top of the big models instead of training their own. If the largest labs take on new obligations, will those costs show up in pricing, access terms or usage limits further down the chain? That’s a tougher thing to plan around than a rule you can read in advance.
So we asked founders and leaders at smaller AI companies, alongside policy, legal and investment specialists, whether big labs’ warnings really do shape the rules and what stricter regulation would mean in practice. Their answers are below.
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Our Experts
- Raj Koneru, Founder and CEO, Kore.ai
- Avi Pilcer, Founder and CEO, Ultra Deep Tech
- Nipoon Donta, Software Engineer, Walmart Global Technology
- Kadan Stadelmann, Co-Founder and CTO, Compance.AI
- Justin Pathrose James, Senior Technical Analyst, L.A. Care Health Plan
- Scott Sampson, Founder and CEO, Nimbus Pages
- Evgenii Arsentev, CEO, AskDocDoc
Raj Koneru, Founder and CEO, Kore.ai
“AI companies should be transparent about the risks of their technology. The problem isn’t that Anthropic is acknowledging those risks. The problem is what happens if those warnings translate into regulations that only companies with billions of dollars can afford to navigate.
“We’ve seen this dynamic across technology. Large companies have the resources to build compliance teams, influence standards and absorb regulatory costs. Startups don’t have that luxury, even when they’re building safer or more innovative technology.
“That doesn’t mean AI should go unregulated. Quite the opposite. As AI agents take on more responsibility and begin making decisions and executing tasks autonomously, oversight, accountability and security become essential.
“But regulation needs to focus on what AI systems actually do, the risks they introduce and the safeguards companies put in place, rather than imposing the same compliance burden on every company regardless of size or application.
“If we get that balance wrong, we risk creating an AI industry where the companies with the deepest pockets aren’t just leading innovation. They’re the only ones allowed to compete.”
Avi Pilcer, Founder and CEO, Ultra Deep Tech
“I run autonomous AI agents in production on top of frontier models, so I am exactly the smaller company this question is about.
Partly agree. Startups should worry less about the wrong thing and more about the right one.
“The 80 pages of risk factors are what securities lawyers produce. Listing ‘existential risk’ in a prospectus is cheap insurance, not a policy campaign. But the effect is real regardless of intent: when the biggest labs say the models are dangerous, regulators write rules sized for the biggest labs. Model licensing, red teaming budgets, audits per model version. A rounding error for a frontier lab, a startup’s whole runway.
“What startups should actually fear is not compliance. It is dependence. A company built on one provider’s API lives under that provider’s terms, pricing and usage policies, which change faster than any law. The prospectus makes that asymmetry official.
The fix is regulating deployment, not models. Make the operator accountable: register who runs the system and what it can touch, keep tamper evident logs, report incidents on a 72 hour clock. A small company can comply with that on a laptop. I do.
“Regulation aimed at the model layer is where the moat gets built.”
Nipoon Donta, Software Engineer, Walmart Global Technology
“I partly agree with critics, but not on motive. An IPO filing legally must over-disclose risk – pages of risk factors tell us more about securities liability than strategy. The danger is indirect: when existential-risk language becomes the template for law, it produces fixed-cost compliance – bespoke evals, red-teaming, model documentation, legal review – that a frontier lab amortises across billions, while a 10-person startup pays it before product-market fit.
“Startups shouldn’t panic about the warnings themselves; they should worry about one-size-fits-all rules copied from them. What protects smaller companies is risk-tiered regulation: obligations scaled by deployment context and autonomy, not model existence; safe harbours for open-source and low-risk uses; and shared, public eval/audit infrastructure so safety becomes a utility, not a moat.
“In production, safety isn’t abstract. The controls that matter – scoped tool permissions, human-in-the-loop for irreversible actions, logging, rollback – are cheap if standardised, crushing if every startup must invent and legally defend them alone.”
Kadan Stadelmann, Co-Founder and CTO, Compance.AI
“Voluntary safety standards and risk-disclosure seem to have a foothold in the US, and represent the nation’s likely course moving forward when it comes to the regulation of AI. Mandatory audits and government restrictions are seen as creating cumbersome compliance costs and a fear of overbearing regulations would discourage entry.
“There’s likely to be no effort within the next five to ten years in the US to move away from the voluntary approach at the federal level.”
Justin Pathrose James, Senior Technical Analyst, L.A. Care Health Plan
“Anthropic’s IPO filing may lift expectations in the market. It could also make rivals move faster and make investors more picky about budgets. At the same time, the shift can create space for small AI teams that work with clear focus. Those groups can stay flexible and keep their costs down. Companies that stand out in a specific area, and do not try to match the biggest players directly, should see the best chances.
“Once public, Anthropic must disclose: quarterly financials, customer concentration, segment revenue and risk factors. This transparency may push enterprises to demand similar clarity from all vendors, giving smaller firms a chance to stand out with honest, lean, and credible reporting.”
Scott Sampson, Founder and CEO, Nimbus Pages
“A big AI company going public doesn’t kill the small guys – it never has. Small businesses have always been the anchor of this economy, and a giant raising a mountain of cash doesn’t change that. If anything, it creates opportunity: as the big players get bigger, the small companies building genuinely better products become acquisition targets – and that’s a payday a lot of founders wouldn’t have had otherwise.
“The real pressure isn’t the IPO; it’s the noise. That much funding and marketing makes it harder for a small team to get recognised. But better products still get found – word of mouth beats a marketing budget. And once a company goes public, it starts optimising for investors and quarterly numbers, while the small guys are still heads-down making a better product. That’s usually where the next good thing comes from.”
Evgenii Arsentev, CEO, AskDocDoc
“I’m a medical doctor by education and CEO of AskDocDoc (telehealth). I’m not a lawyer or a policy person, just a founder of a small company that runs on AI agents.
“About the premise – I don’t see a plot here. An IPO filing has to list the risks, so I don’t read intent into it. But yes, startups should watch the rules that come after such warnings, not the warnings.
“In my company there are no full-time developers. A business task that took about 2 weeks now takes hours. The risk I see is small and daily: agents work on the live server, and something small breaks almost every day. Usually it’s fixed in about 10 minutes.
“My worry is a heavy rule written for the biggest labs landing on companies like mine. We can afford agents, but not a compliance department. And bans on AI are a fight with progress, in my opinion.”
