AI Startups and IPOs: Huge Deals Fueling Growth

AI Startups Attract Increased Investor Confidence

Investment firms specializing in venture capital are demonstrating growing confidence in the potential of artificial intelligence (AI) startups to succeed as publicly traded companies.

This positive outlook is translating into increased investment activity, with larger sums of capital being allocated to AI-driven ventures at earlier stages of development.

Favorable Funding Landscape for AI Companies

Currently, it represents an opportune moment for startups leveraging artificial intelligence – whether developing AI technologies directly or building applications upon existing AI infrastructure – to secure funding.

While numerous startup sectors experienced funding increases in 2021, AI startups are exhibiting particularly robust growth across various stages, suggesting widespread market interest.

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Global AI Funding Trends Revealed

Recent data compiled by CB Insights illustrates a dynamic global AI funding environment, characterized by significant regional disparities.

We will analyze these figures with insights from Jai Das, a partner at Sapphire Ventures, and Rudina Seseri, a partner at Glasswing Ventures – both frequent contributors to our discussions on AI investment.

Analyzing Capital Flow in the AI Market

Initially, we will examine the data to pinpoint the current distribution of capital within the AI startup ecosystem.

Subsequently, we will explore the reasons behind the increasing popularity of both early-stage and late-stage investments in AI startups.

Key Factors Driving AI Investment

• Strong Customer Demand: A broad base of customers is actively seeking AI-powered solutions.
• Geographical Concentration: Funding activity is unevenly distributed across different regions globally.
• Investor Confidence: Venture capitalists are increasingly optimistic about the long-term prospects of AI companies.

The current market conditions suggest a sustained period of growth and innovation within the AI startup landscape.

This trend is expected to continue as AI technologies become more integrated into various industries and aspects of daily life.

Growth in AI Startup Funding

According to reports from CB Insights, a substantial $17.9 billion was invested in global artificial intelligence startups during the third quarter of 2021. Funding secured by these companies has consistently increased each quarter since the first quarter of 2020, when a low point of $6.3 billion in investment was recorded.

However, the third quarter of 2021 stands out not merely as another period of strong fundraising, but due to a significant surge in the number of deals completed.

Consider the following:

The combination of record-breaking deal numbers and volume has prompted further investigation. What factors are driving this trend?

Numerous startup sectors are experiencing increased venture capital totals, fueled by a greater frequency of larger, so-called mega-rounds – investments exceeding $100 million. The AI startup landscape mirrors this pattern. In Q3 2021, AI startups secured 45 mega-rounds, marking the third consecutive quarter with at least 45 such deals, following 47 and 46 deals in Q1 and Q2 2021, respectively.

The current pace of mega-rounds within the AI startup sphere is markedly different from previous years. Data from CB Insights and TechCrunch analysis indicates an average of 19.75 mega-deals were finalized per quarter in 2020. This figure was lower at 13.5 per quarter in 2019, 12.25 in 2018, and just six in 2017.

Interestingly, the proportion of early-stage deals relative to the overall AI startup deal share is gradually decreasing as midstage investments gain prominence. In 2020, early-stage AI investments constituted 65% of all deals, while midstage deals accounted for 20%. Through 2021 to date, these percentages have shifted to 61% and 22%, respectively.

Given that there were 2,412 total AI funding rounds in 2020 and 2,073 through the third quarter of 2021 – an accelerating trend – it is reasonable to anticipate a rise in total deal volume for 2021. This increase will likely lead to new highs in both absolute early- and midstage deal volume, even if the comparative deal share changes. (In fact, the dollar share of mega-rounds among AI startup funding rounds has decreased from a peak of 70% in Q1 2021 to 57% by Q3.)

Furthermore, the size of early- and midstage AI startup deals is also increasing. The average deal size for AI startups has risen from $18 million in 2020 to $33 million so far this year. However, recognizing that average figures can be influenced by a few substantial deals, the median deal size is a more reliable indicator. This is also accelerating, moving from $5 million in 2020 to $7 million thus far in 2021, representing a gain of approximately 40%.

Specifically, median funding events for angel-stage AI startups are now valued at $6 million through Q3 2021, an increase from $4 million in 2020.

The available data suggests a dynamic sector actively addressing a wide range of challenges. Seseri of Glasswing corroborated this view, stating in an email to The Exchange that while “enterprise interest” in AI-powered startup products has “broadened considerably in recent years,” both AI and machine learning solutions have “become more robust across various sectors,” thereby stimulating market demand in areas such as sales, marketing, and cybersecurity.

A wider customer base and diverse applications create substantial opportunities for startups to develop innovative solutions.

Based on our data analysis, we can draw the following conclusions:

• The increasing frequency of mega-deals for AI startups suggests a growing number of potential IPO candidates. Raising $100 million, or even a significant portion in a single round, indicates investor confidence in an exit valuation exceeding $1 billion, and potentially much higher. Most of these companies will need to independently achieve an exit rather than relying on acquisition.
• The rise in median deal value and overall deal volume points to a strong fundraising environment for early-stage AI startups. Expanding midstage deal share should also sustain robust investment activity at later stages. This trend is likely to continue driving expectations for AI startup IPOs in the near future.

However, it’s important to note that not all AI startups will be particularly groundbreaking. We may see a significant number of companies in the AI space tackling problems that are not necessarily newsworthy.

The Pervasive Rise of Artificial Intelligence

While discussions often center on futuristic applications of AI, a significant number of companies are concentrating on more practical, everyday solutions. This hasn't diminished investor excitement, however. Sapphire Ventures, led by Das, expresses strong optimism regarding “boring AI” – the application of AI to resolve straightforward challenges.

As an illustration, Das points to Verbit, a Sapphire-backed company providing AI-assisted transcription and captioning services. Verbit prioritizes exceptional accuracy through a blend of artificial intelligence and human oversight.

Sapphire’s realistic perspective on AI acknowledges the continued importance of human involvement. This is evident in both Verbit’s operations and within a recently funded healthcare company.

Das forecasts that AI will not supplant human workers, but rather enhance their capabilities. He believes AI is rapidly integrating itself into all industries. “Virtually any software company will incorporate AI into its offerings,” he stated to TechCrunch.

Lower Barriers to Entry for AI Startups

The increasing prevalence of AI is also attributable to the ease with which AI-driven startups can now be launched. Seseri notes that the entry barrier has decreased considerably in recent years.

AI/ML is no longer solely a complex technological endeavor requiring extensive development time before achieving commercial viability. This shift is due to the widespread availability of pre-built models, such as OpenAI’s GPT-3, readily available templates, and thriving open-source communities.

These resources empower startups to create innovative solutions more efficiently. Simultaneously, the demand for AI-powered solutions is growing as their benefits become increasingly apparent.

Enterprises have invested heavily in data infrastructure and practices, enabling them to unlock substantial value from the technology. Consequently, providers of advanced, high-value AI technologies can command higher prices as their impact on profitability becomes more demonstrable.

Demand and Supply Dynamics in the AI Landscape

According to a resonance map developed by pi Ventures, the AI market has experienced significant movement on both the supply and demand axes. The supply has increased due to the simplification of the technology, while demand has risen as previously unmet needs become clear.

From an investor’s standpoint, this translates to greater opportunities for entrepreneurs. “More founders are able to enter the field, demonstrate initial success, and attract investment capital,” Seseri explains.

However, founders should anticipate that investor interest may not be evenly distributed across all AI applications – at least not in the current market conditions.

• AI is becoming increasingly integrated into various sectors.
• The cost of launching an AI startup has decreased.
• Enterprises are realizing significant value from AI investments.

Geographical Disparities in AI Investment

A closer examination of the geographical distribution of artificial intelligence (AI) investment reveals a somewhat uneven landscape.

During the third quarter of 2021, the United States attracted $10.4 billion in AI startup funding, spread across 324 investment deals. Asia, meanwhile, received $4.8 billion in funding over a comparable 321 deals.

Investment levels decline significantly beyond these regions. Europe secured $1.6 billion in AI startup capital through 142 deals.

Latin America experienced a considerably smaller volume of transactions, totaling $500 million across 12 deals. Notably, Canada’s AI venture activity in the same quarter—$400 million across 24 rounds—almost equaled that of the entire Latin American region.

Currently, securing late-stage AI capital generally requires a startup to be located in North America, Asia, or Europe. Other regions exhibit limited activity, although this could evolve as promising early-stage ventures emerge in smaller AI markets.

It's possible we are observing a generational difference in the development of various startup ecosystems. North America, Asia, and Europe may be more advanced in sectors like fintech, allowing startups to focus on more complex challenges.

Conversely, emerging startup markets such as Latin America and Africa have witnessed substantial fintech investments recently. This may be attributable to less developed economies and less disrupted financial systems in these regions.

If this assessment proves accurate, we anticipate an increase in AI startup fundraising totals in Latin America and Africa in the coming years, as their fintech initiatives mature to a level comparable to those in larger markets.

Even this cautious outlook suggests a positive long-term trajectory for AI startup fundraising. This represents the current situation as we approach the end of the year.