On this page13
- Is PR different for AI companies than for other startups?
- Pressure 1: Technical claims that outsiders can't check
- Pressure 2: Safety and misuse questions from day one
- Pressure 3: Regulation that is still being written
- Pressure 4: A category where everyone sounds the same
- Pressure 5: Buyers, investors and AI search all read the coverage
- The AI comms exposure scorecard
- When an AI company doesn't need PR yet
- FAQ
- Do AI startups need PR before they raise funding?
- Is PR for AI companies mostly about crisis management?
- Should AI companies talk about regulation publicly?
- What outlets matter most for AI companies?
AI companies need PR because they carry pressures most startups don't: the public is uneasy about the technology, every capability claim gets checked by skeptical reporters, regulators are actively writing rules, safety questions arrive before the product is even out, and the category is so crowded that "AI-powered" means nothing on its own. Good communications handles all five at once. It explains what the product really does, earns credibility from independent outlets, and gets the company ready for the hard questions before they're asked in public.
The irony is easy to see. These companies have the best writing tools in the world, built in-house. If producing words were the hard part, they'd need comms less than anyone. They need it more, and the reasons are structural.
Is PR different for AI companies than for other startups?
Yes, in degree more than in method. Any startup needs a clear story, credible coverage and a plan for bad news. An AI company needs those things under more scrutiny, with less public goodwill to start from, and with claims that are harder for outsiders to verify.
A SaaS tool for invoices doesn't get asked whether it's safe for society. An AI agent product might get that question in its first interview. That shifts where comms time goes: less on getting noticed, more on being believed.
The audiences multiply too. A typical early-stage startup talks to customers and investors. An AI company also has researchers who will pick apart its methods, policymakers who may quote it, safety advocates who will test its claims, and journalists who cover AI as a society story rather than a tech story. Each group reads the same announcement differently, and someone has to think about all of them before it goes out.
Pressure 1: Technical claims that outsiders can't check
AI companies talk in benchmarks, parameter counts, accuracy rates and evaluation scores. Most readers can't verify any of it, and reporters know that some companies pick the flattering test and skip the rest.
So comms has two jobs. First, make sure every number the company publishes is defensible, with the method stated. Second, translate it into a claim a non-specialist can follow without distortion. I've seen the same problem in crypto for years.
Most crypto companies don't have a product problem, but they have an explanation problem. Shilika Jain on X, 19 Jun 2026
AI has the explanation problem in a sharper form, because a wrong simplification can read as an overclaim. I go deeper on how reporters treat these numbers in AI benchmark claims and journalists.
Pressure 2: Safety and misuse questions from day one
Beyond the product itself, safety comes up fast in AI interviews. The usual set of questions looks like this:
- what happens when the model is wrong, and who is responsible for the result
- how the company stops misuse by bad actors
- what data the model was trained on, and with whose permission
- what a human checks before an output reaches a customer
Each of these deserves a written answer before the first interview, not an improvised one during it.
These aren't gotcha questions. They're fair, and a founder who fumbles them in an interview hands the reporter the more interesting story. Comms work here is mostly preparation: a written position on each likely question, agreed with the technical and legal teams, rehearsed until the founder can answer in plain language without overpromising. My notes on building that into coverage rather than defending against it are in responsible AI PR and the safety narrative.
When something does go wrong, like a model producing a harmful or false output that goes viral, the response window is short. I keep that playbook separate, in the 72-hour AI hallucination crisis plan.
Pressure 3: Regulation that is still being written
The EU's AI Act and a growing set of national rules mean AI companies are operating while the rules are still being finalised. That creates a comms task most startups never face: explaining your position on policy before you're forced to.
In practice that means deciding early what your company believes about regulation, saying it consistently, and making sure product announcements don't accidentally contradict it. A launch that promises "fully autonomous" decisions can sit badly next to a policy statement about human oversight. Someone has to read both and catch that.
Transparency pays off here over time. My read from watching crypto go through its own regulatory fights is that companies who explained themselves early, in plain language, were better placed once rules arrived than the ones who stayed quiet and hoped. Regulated or about-to-be-regulated industries reward companies that were clear before they had to be.
Pressure 4: A category where everyone sounds the same
Every product now says it's AI-powered. Reporters see dozens of pitches a week claiming to be the first, the fastest or the most accurate. The company that gets covered is the one with a sharper point of view about where the industry is going, not the longest feature list.
This is where founder profiling earns its cost. With GAIA, a decentralized AI company, the work was a steady cadence of founder interviews and commentary around one narrative, decentralized AI agents with node count as the proof point. That consistency built into a Forbes piece on AI agents and the agentic web, a Decrypt feature on GAIA's "living knowledge systems", and a run of podcasts. One clear thesis, repeated, beat a scattered set of announcements. The detail is on the GAIA case study.
Pressure 5: Buyers, investors and AI search all read the coverage
Enterprise buyers do diligence before they let an AI product near their data. Investors check what's been written. And increasingly, people ask ChatGPT or Perplexity which tool to use in a category, and those answers lean on sources the assistant has reason to trust: independent articles, interviews and expert roundups more than your own homepage.
That makes earned coverage a sales and visibility asset for AI companies, not just a vanity metric. It also means a single negative story can show up in AI answers long after the news cycle moves on. Every one of those readers is forming a view of the company from the outside.
if your company has a good external/internal communicator, you're half way ahead of your competitors. Shilika Jain on X, 29 Aug 2023
I wrote that about companies in general. For AI companies, where the buyer, the investor and the assistant answering a search query all rely on what's been said publicly, the head start is larger.
The AI comms exposure scorecard
To decide how much to invest in comms, score your company 0, 1 or 2 on each pressure. Be honest; this is for you.
| Pressure | 0 points | 1 point | 2 points |
|---|---|---|---|
| Technical claims | No public performance claims | Some benchmarks or accuracy figures | Claims are central to the pitch |
| Safety surface | Internal tooling only | Customer-facing outputs | Outputs affect health, money, legal or public info |
| Regulatory exposure | Little regulatory attention | Sector has emerging rules | Clearly in scope of AI-specific rules |
| Category crowding | Few direct competitors | Several similar products | Dozens of lookalikes |
| Buyer scrutiny | Self-serve consumers | SMB buyers | Enterprise or government procurement |
How I'd read the total:
- 0 to 3: a founder writing well, with occasional outside help on launches, is probably enough.
- 4 to 6: you need a consistent comms owner, even part-time, and prepared answers on safety and claims.
- 7 to 10: comms is a core function. You need a senior person in the room before announcements are written, not after.
The scorecard isn't science, and the thresholds are my judgment from the work rather than data. It's useful mainly because it forces the conversation about which pressures you actually face.
When an AI company doesn't need PR yet
Not every AI company needs a comms investment now. If you're pre-product with nothing to announce, PR spend mostly buys you attention you can't convert. If you sell a narrow internal tool to a handful of known customers through direct sales, coverage may matter less than case studies those customers will vouch for. And if the founder isn't willing to take hard questions in public, media work will be painful until that changes. For timing, my stage-by-stage framework for when to hire PR covers the trade-offs.
The cost of waiting too long is different, though. AI companies that only start comms after a public mistake end up introducing themselves through the worst story about them.
FAQ
Do AI startups need PR before they raise funding?
Not always, but some groundwork helps. A founder with a clear public point of view and a few credible pieces of coverage gives investors something to check. The funding announcement itself is usually the first big PR moment, so prepare for it a month or more ahead.
Is PR for AI companies mostly about crisis management?
No. Crisis readiness is part of it, but most of the work is explaining the product accurately and building a founder's credibility over time. Good preparation also makes crises smaller when they happen.
Should AI companies talk about regulation publicly?
If regulation will affect your product, yes, carefully and consistently. Silence leaves others to define your position. Agree the stance internally with legal first, then make sure product messaging doesn't contradict it.
What outlets matter most for AI companies?
It depends on the buyer. Business and tech press reach enterprise decision-makers, while trade and developer outlets reach technical evaluators. AI-native and crypto-native companies, like GAIA, also benefit from outlets such as Decrypt alongside tier-1 business coverage.
If your score landed above 4, book a 30-minute AI comms teardown or see how my AI startup PR service works.
