Thank you for being one of the first 16,095 members and supporting PeerSignal research! Welcome back to my almost-weekly newsletter where I share data and examples to help you study B2B sales and marketing.

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Quick PeerSignal update: We added new features to our AI Jobs tracker 🎉.

• Quick links to company career pages
• Headcount growth signals
• More AI companies

In case you haven't been following Artificial Intelligence (AI) news, here's our 60-second recap on how it's impacting the tech world:

VCs are buying into AI.

• 24% of our AI index received funding rounds in the last 12 months.
• Six companies have reached unicorn status in generative AI alone. Jasper, Stability AI and OpenAI – all $1B+ valuations, all $100M rounds in the last 6 months.
• True disruptors creating new Large Language Models (like OpenAI) are getting billions. On average, AI companies tracked in our index received $190.6M in funding ($63M is the median). Salesforce invested $250M in generative AI. Meta's pushing the Metaverse aside for gen AI, now its single largest investment.

SaaS founders are buying into AI.

• 52% of our SaaS index is integrating AI in some way, either through integrations or core offering.
• According to the NYT, so are 23% of Y combinator startups.

The public is buying into AI.

• OpenAI acquired 1M ChatGPT users in one week and 100M active users in two months. The AI giant is projected to 100X revenues in two years, $10M to $200M to $1B.
• Search volume for “AI” has been up and to the right since early last year. ChatGPT’s launch in November shot it into the zeitgeist overnight.

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Is it time for tech workers buy into AI?

In this issue, we look into AI market growth through the lens of recent hiring trends. Here's my AI growth trends summary on LinkedIn.

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AI company org structure and hiring trends

71% of the AI companies we track are hiring. While numbers vary by size, funding, and more, that averages out to 14 open positions per company, 3,523 total open jobs across just 258 companies.

Still an immature market and technology, R&D makes up the vast majority of current employees (39%) and open roles at an AI company. While the engineering ratios are more extreme than greater B2B SaaS, it follows the same general patterns – engineering always ranks number one and sales and biz dev (BDRs) typically claim the next two spots. Then product followed by CS and marketing (split). HR/recruiting, finance and admin make up the smallest slivers of the pie.

Of course, product-led is core to many AI companies with 41% of our index promoting a free offer (trial or free plan). But PLG doesn’t mean no sales or marketing. Product marketing, demand gen, and marketing leadership positions were the most in-demand marketing roles among AI companies.

Current AI company hiring trends reflect their current org strategy.

That breakdown looks similar to B2B SaaS as a whole over the past few months. So we peeked under the hoods of the top 10 AI companies with the highest valuations to see which functions are trending.

Hiring insights from top 10 AI companies

1. Fad or foreshadowing? AI introduces titles we’ve never seen before.

Runway is hiring an AI content specialist. While researching AI companies, I was also shown an ad promising $300K+ jobs for AI prompt engineers (no degree required).

2. Hiring demand skews heavily toward R&D roles.

Very few open marketing roles and almost no finance, CS, and HR roles open in this small sample size. Sales comes in waves depending on stage. The few looking for sales are looking for an entire sales team at once.

3. This engineering skill wanted: machine learning

Unlike the average B2B SaaS companies, AI org job listings often include machine learning engineers. Research scientists and data analysts also came up frequently.

What to consider when evaluating AI companies

54% of our AI Index has increased headcount YoY, 23% have grown MoM. However, even AI isn’t immune to tech layoffs. Where there’s hype, there's irresponsible spending.

The biggest challenge for tech workers seeking employment right now is not finding a job, but finding a well-paying, flexible job with a company that’s still growing. That was an easier task in 2021, when every tech startup looked to be on the rise.

After all, the AI game can get expensive. You’re challenging Google, Meta, Microsoft, IBM, Salesforce — nearly every established tech company. The estimated cost to run ChatGPT is $100K per day. Mike Volpi, an investor at Index Ventures who sits on the board of the AI start-up Cohere, says startups need at least $500M to develop a large language model, the technology behind ChatGPT.

How do you choose the right AI company and avoid the bandwagon companies destined for burnout? A few factors to consider before assuming all AI startups are moon-bound:

• Funding: How much runway do you have? Is the vision realistic given the funding?
• TAM: Is there a big enough market for your specific AI use case? How many competitors?
• Experience: Do the founders or core team have experience in AI? (big edge when talent pool is shallow)
• Product-market fit: Has the company seen early traction? Is user behavior and revenue becoming predictable?
• GTM: What’s the business model? Have they proven prowess in PLG?

Next week, we dive deeper into the GTM models and tactics inside AI companies. Stay tuned.

Have more questions or feedback? Reply or join the conversation on LinkedIn.

I read all replies.

Best,

Adam & Camille

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