AI is Eating Software: What Founders and VCs Must Know

In our earlier piece, "VC deal flow awash with AI startups", we highlighted AI's positive impact on the world of venture in 1Q24. Now, with a further 2 quarters of market data, it is clear that AI will be the largest segment of startup investment in 2024.

The surge in AI deal-making is bucking the trend in an otherwise still gloomy VC funding environment. And the reason? Generative AI adoption in the enterprise is taking off. Some companies are already realising $100Ms in efficiency gains.

The short-term opportunity is so big that in the current land grab, startups we had barely heard of just a few years ago are already vying with the big tech companies for early market leadership.

Sarah Tavel, General Partner at leading VC Benchmark Capital, in a recent interview, says we have to start changing the mental model of startups. For decades the industry has seen application software as a productivity improvement tool. But what AI enables is not just a productivity enhancement but "a tool that actually does the work". In other words, the workflow is not enhanced, it is replaced.

As AI disrupts whole industries, VCs are being hit with unprecedented levels of AI deal flow. Following a wave of Foundation Model funding over the past 2-3 years, we now have thousands of startups jostling for position in the application space. Even though the opportunities seem almost limitless, some early application areas are already getting very busy.

Things are moving so fast that founders and investors alike are struggling to assess the competitive landscape before jumping into the race. Confident market positioning, a robust tech stack, plus innovative go-to-market and business model strategies are all now essential.

To separate the wheat from the chaff, VCs are seeking startups that are finding exciting areas of white space not already being fought over or potentially coming under the purview of the big foundation model players like OpenAI.

Today we review the scale of the AI investment surge, where the money is going, the impact on the traditional cloud software sector, and key areas of emerging opportunity.

Investment surge

First, to appreciate the scale of what's happening in AI, let's look at the latest figures.
Digging into the recent CB Insights State of AI Q3'24 Report, the big headlines are:

• Deal Value. Global AI funding was $16.8B for 3Q24 meaning that VC funding year to date hit $55.4B, surpassing the whole of 2023 ($54.2B).
  
  
• Deal Count. Global AI deal count rose 24% QoQ to reach 1,245 in Q3’24 - its highest quarterly level since peaking in Q1’22. This bucked the trend in overall venture deals (-10% QoQ), signalling that investor interest in AI remains strong despite continued cooling in venture markets generally.
  
  
• Deal Sizes. The average AI deal size is $23.5M in 2024 so far - up 28% vs. $18.4M in 2023. This upward trend has been influenced by a rise in $1B+ deals, with AI startups attracting 9 such deals in 2024 so far versus 4 in the whole of 2023. Given the significant proportion of Seed and early-stage deals in the mix (72%) median deal sizes provide a more reliable trend to follow, and these were $3.8M YTD up from $3.5M in 2023.
  
  
• Geography. The US continued to lead global regions in AI funding and deals in Q3’24. US-based AI startups drew over two-thirds (68%) of global AI funding ($11.4B) and 45% of global AI deals in Q3. By comparison, Europe at $2.8B, represented 17% of global AI investment and at 279 deals represented 22% of the global total.
  
  
• Investor type. In terms of deal share in Q3, the top 5 categories were as follows: VC represented the largest portion at 31%, followed by Corporates & CVCs at 18%, 'other' at 18%, and Angels at 12%. This 'other' category incorporates a diverse array of private investment vehicles.
  
  
• Median deal size by investor type is also interesting: For VC funds this is $8.5M YTD whereas CVC is tracking much higher at $15M. Corporates are playing a major role in funding the AI surge.

Setting aside the aberration of the extreme highs of VC investment during 2021 and 2022, most industry observers are comparing 2024 to the steady 10-year growth trend leading up to 2020. Assuming software investment in 2024 hits the $79B forecast, this remarkable growth (65%) from 2020 ($48B) will largely be attributable (c.40 percentage points) to the explosion in GenAI funding, according to an analysis by Accel.

Around $56B has been invested in GenAI companies since 2023, with the US/Europe split at 80/20. A large chunk of this funding upswing has been the result of mega rounds ($100M+) in the US. Foundation Models have scooped up most of the funding over this period. The full breakdown is as follows:

Foundation Models $37B (e.g. OpenAI, MistralAI, Anthropic)
Full Stack Apps $7.3B (e.g. Synthesia, Perplexity, Poolside)
Apps $6.4B (e.g. Harvey, Cursor, Leya)
Computing $3.8B (e.g. CoreWeave, groq, Lambda)
Tooling $2.1B (e.g. Scale, Vercel, Hugging Face)

AI is eating software

This surge in investment is providing a critical boost to otherwise very sluggish markets. The ramifications are being felt across every sector of the economy as AI replaces entire workflows. In such cases it is starting to replace 'conventional' software solutions and putting even further pressure on traditional enterprise software providers.

In Accel's EuropeScape report, AI Eating Software, Accel spells out how GenAI is fuelling both public and private market recovery.

On the public side, the NASDAQ keeps climbing higher, up 38% in the last 12 months and beating new all-time highs. This is even before the outcome of the US election was known. Out of the $8.4T of value created in the past year, $5.3T is coming from the six tech titans that are investing tens of billions into AI: Apple, Microsoft, Google, Meta, Amazon and Nvidia.

On the private side, the funding of AI and cloud companies is on the rise again, estimated to hit $79.2B by the end of 2024 after three consecutive years of decline.

And then the reality check for all others: "Outside of the AI world, the outlook isn’t as bright and the era of high software growth has been replaced by a focus on profitability."

This sobering counterweight is made against the backdrop of enterprise buyers continuing to consolidate budgets. Enterprise software spending remains under significant pressure. Corporates are still digesting huge spending from 2020-22 and macro uncertainties continue to slow down purchasing decisions. Meanwhile, IT budgets (down 17% at the median for non-AI spend) are shifting aggressively to AI (up 30%).

AI is reshaping almost all enterprise functions from sales and marketing, to design, software engineering, finance, HR and customer service, to name just a few. And AI is generating serious momentum in many industry verticals from Financial Services and Legal to Healthcare and BioTech, where applications can leverage company-specific data.

Everything appears choreographed

As we highlight above, the big established players - Microsoft, Google, Amazon, Meta - have been actively shaping the evolving AI landscape for years. The reason: AI is an enabler for both sustaining innovation as well as disruptive innovation. This means that it is strategically important to incumbents not just startups looking to create new markets.

And then there are the big new players, the Foundation Model companies, raising $10B's and already experiencing remarkable revenue growth. In many senses they are the architects of the GenAI era, whose roadmaps are closely guarded, and every public comment scrutinised in the hope that new white space can be found.

Sam Altman's grilling in a recent interview gave little away. He compares the current era of artificial intelligence (AI) not to the early days of the internet (as so many others have done) but to the transformative period following the invention of the transistor.

Just as the transistor revolutionised technology by enabling the development of computers and other electronic devices, providing the platform for ALL software created today, Altman says that AI is poised to revolutionise entire industries in a similar manner.

In addition to Altman's description of OpenAI's increasing focus on 'Agentic Automation', he set out the broad scope of where OpenAI would play in the next few years. In other words, areas where startups should stay away from to avoid being "steamrollered".

There is a very strong sense that territory is being marked out by all the big players looking to consolidate their positions. In a recent interview, VC Bill Gurley, GP at Benchmark Capital, commented on the role of the 'incumbents': "..this appears highly choreographed. The windows that open up huge doors for innovators and start-ups are usually not choreographed. You don't have the whole world saying, "Look, this is where we're going." And yet, here you do."

Finding the white space

Founders creating AI businesses must be cognisant of how the AI market is now playing out. The dynamics are quite unlike any tech boom that has gone before. Finding the next wave to ride in the hope that it is not about break on top of you as others pile in is one of the biggest startup challenges.

The big waves now building are numerous and are being monitored carefully by VCs such as Accel. Over the next year or so these waves will be enabled by:

• Broad access to GenAI APIs enabling new set of homegrown applications within the enterprise
• Agentic automation deployed around core enterprise functions, from Sales to HR
• Vertical applications transformed by GenAI, from Legal and Financial Services to Healthcare
• GenAI enabling hyperpersonalised experiences, replacing human 'agents'
• Code development reinvented, moving from coding to writing specifications
• Data security as the next cyber frontier as data volumes expand in the GenAI era
• and others that will almost certainly emerge as new models open up further use cases

As big slices of the software category are being redefined AI is creating an abundance of opportunity. But founders preparing AI-centric investment propositions must pay close attention to a rapidly shifting competitive landscape and how investors will scrutinise their proposition.

Knowing who else is emerging in your space, how well funded they are, and how you will steal a march on them, have now become pressing investor questions.

Let's talk!