Author: Raman Rai
Translation: Blockchain in Vernacular
TL;DR:
AI Investments Hit New Highs: The global AI market is expected to reach $13 trillion by 2030. AI investments are exploding as venture capital firms bet on startups that are reshaping industries.
One of the key investment areas in 2024 is AI infrastructure: As AI models continue to demand more computing power, venture capital firms are increasing their investments in AI infrastructure, including specialized chips and data centers.
Funding trends to watch: Late-stage rounds and AI infrastructure investments dominated, while AI applications in healthcare, finance, and defense attracted significant investment as investors sought projects that would have real impact.
The next billion-dollar startups: The future of AI investing will focus on areas such as autonomous robotics, energy, and entertainment, where human-AI collaboration is already paving the way for groundbreaking startups.
Overview: This article will discuss:
Introduction of AI in the Venture Capital Ecosystem
Part 1: How to deal with noise in a competitive market
Part II: Top AI Funding Rounds in 2024
Part 3: Five key opportunities to lead the next billion-dollar AI startup
Challenges and ethical considerations
1. Introduction of AI in the Venture Capital Ecosystem
With billions of dollars pouring into the field of artificial intelligence, it’s fair to say that the “AI boom” isn’t dying down — and is only getting bigger.
Artificial intelligence has become one of the most heavily funded industries in the venture capital world.
According to Pitchbook, global AI investments have reached $290 billion over the past five years, with private investment firms completing more than 15,400 deals since 2022. This intense activity reflects a high level of confidence in the future of AI. Opinions vary as to how big the AI market will become by 2023.
According to McKinsey:
“AI has the potential to add $13 trillion to the global economy by 2030, equivalent to a cumulative GDP 16% higher than today. This translates into an additional 1.2% of GDP growth per year.”
Both Statista and Bloomberg Intelligence predict that the AI market has the potential to grow to $2 trillion by 2030, covering everything from AI software to hardware and services. PwC predicts that AI will contribute $15.7 trillion to the global economy by 2030, primarily through improved productivity and increased consumer demand for AI-enhanced products.
It’s safe to say – AI has become part of our daily lives and the hype is over. However, with excitement comes noise – investors are now faced with thousands of AI companies, each claiming to be the next big thing. Data privacy concerns, talent shortages, ethical AI and centralization risks add more challenges to this already competitive industry.
2. Part 1: How to deal with noise in a competitive market
Today, more than 100 venture capital funds are actively investing in the AI market, covering horizontal applications (such as infrastructure) as well as vertical applications involving specialized industries such as healthcare, finance, and agriculture.
To understand the current state of venture capital in AI, I’ll describe two types of investors:
Pioneers: aggressive investors who are willing to make bold bets in multiple AI fields. Pragmatists: conservative funds that believe AI has potential but are more selective or cautious in their investments.
1) Pioneers: The most active venture capital firms
First movers are known for taking risks and setting trends, and they play a key role in shaping the future of AI investing. Here are some noteworthy players:
Andreessen Horowitz (a16z) has made 29 investments since 2023, covering a variety of fields, including a $100 million investment in Character.AI and a $224 million investment in Genesis Therapeutics. a16z has made big bets at the intersection of artificial intelligence, biotechnology, and consumer technology.
Sequoia Capital has taken a particularly aggressive approach, leading several financing rounds for high-profile startups such as Cohere (language models) and Viz.ai (medical imaging). In 2023, about 60% of Sequoia Capital's new investments will be concentrated in the field of artificial intelligence, a significant increase compared with only 16% the previous year.
General Catalyst has invested $750 million in healthcare AI, including companies such as Commure, Sword Health, and Overjet. They have made 19 AI investments, less than half of which are in projects involving generative AI (GenAI).
Alumni Ventures has made multiple investments in the field of artificial intelligence and machine learning, covering consumer and enterprise applications including SenseTime, Dataminr and Iterative Health.
As Stephanie Zhan, a partner at Sequoia Capital who focuses on seed and early-stage investments, puts it:
“Over the past year, artificial intelligence has breathed new life into the investment ecosystem.”
2) Pragmatists: Conservative venture capital firms
While pioneers are rushing in, pragmatists are choosing to wait and see for the time being.
These funds see the potential of AI but prefer to take a discerning approach, focusing on sustainable returns and more stable market conditions. Here are some typical examples:
Kleiner Perkins prefers to choose relatively safe AI investments, such as Together AI ($102.5 million Series A), whose underlying technology supports the development of AI in a wide range of applications.
Benchmark Capital: Benchmark Capital is known for its anti-hype philosophy, having led a $24 million Series A round in September 2024 for 11x, a startup that creates automated digital workers to streamline go-to-market (GTM) operations. Benchmark Capital prefers to focus on real solutions rather than speculative technologies.
Bessemer Venture Partners: Bessemer has invested approximately $250 million in AI, focusing on applications that solve real problems rather than chasing hype. Their support for EvenUp ($50.5 million Series B), an AI startup that helps personal injury attorneys automate medical documentation, reflects their cautious investment strategy.
Union Square Ventures: USV has invested approximately $150 million in AI, primarily in applications driven by network effects. Their investment in Recursion Pharmaceuticals, which uses AI for drug discovery, is consistent with their investment philosophy that network effects trump riskier technologies.
GGV Capital: GGV has invested approximately $180 million in AI, preferring mature areas like SaaS and enterprise software, using AI as an add-on technology rather than a core technology. Their strategy supports growth rather than experimental technologies.
So what is causing these funds' hesitation?
Pragmatists are cautious about the challenges posed by AI:
High capital requirements: Developing AI is expensive — from data to computing power — and these venture capital firms are wary of large upfront investments.
Regulatory uncertainty: As the regulation of AI lags behind its rapid development, pragmatic funds prefer to wait for the rules to become clear before making decisions, especially in areas such as autonomous driving and healthcare.
Market volatility: Valuations of AI startups have soared, and some investors are concerned that the “AI bubble” could burst. Pragmatic funds avoid overinvesting in overheated markets until the craze subsides.
Ethical and privacy issues: As data regulations tighten around the world, ethical issues surrounding AI increase risk. Pragmatic funds remain cautious and avoid investing in areas where privacy issues could obscure returns.
3) Are the pragmatists missing out?
Conservative funds like Kleiner Perkins, Bessemer Venture Partners, Benchmark Capital, Union Square Ventures, and GGV Capital may be perceived as missing out on AI investment opportunities due to their cautious investment approach. However, this conservative stance is not necessarily a disadvantage. While their selective investment strategies provide stability and are able to capture the rapid growth of AI, they may also miss some opportunities with transformative potential in the long run.
Pioneers like Sequoia and a16z (Andreessen Horowitz) have made important investments in foundational AI and generative technologies, ultimately paving the way for the next era of technological change. If AI continues to grow at its current pace, the cautious stance of the pragmatists may sideline them in an industry that could define the next decade.
3. Part 2: Top AI Financing Rounds in 2024
Now that we have an idea of which large venture capital funds dominate the AI space, let’s take a look at the startups that will receive the most funding in 2024.
Notable transactions in Europe and the United States in Q4 2024:
Glean ($260M Series E): an AI-based enterprise search engine valued at $4.34B.
Codeium ($150M Series C): an AI programming platform that improves developer productivity, valued at $1.1B.
Opkey ($47M Series B): an AI test automation platform for finance, HR, and corporate planning.
Butlr ($38M Series B): Focuses on providing anonymous people sensing and occupancy solutions using physical AI.
The deals demonstrate the wide range of AI applications, from logistics to automation, that are attracting investor attention.
So, what will be the key themes driving AI funding in 2024?
1) Generative AI continues to attract significant investment
Despite the cost and scalability challenges generative AI presents, it remains a key area of investment, with $26 billion raised in generative AI startups over the past five years, particularly in the content creation, healthcare, and enterprise solutions sectors, including companies such as QuizGecko, Writesonic, and Tome.
2) AI infrastructure and hardware receive the most funding
As the demand for computing power for generative AI models continues to increase, venture capital firms are betting on the "backbone" of AI - AI infrastructure. Companies focused on developing specialized chips, data centers, and platforms are receiving more funding:
Groq, an AI semiconductor and software startup, has raised $640 million in Series D funding led by BlackRock Group, valuing the company at $2.8 billion. Groq’s success shows the growing attention being paid to companies that support the “engine” of artificial intelligence, from chip design to large-scale computing.
BlackRock Group and Microsoft have jointly launched a $30 billion AI investment fund to build AI infrastructure, including data centers and energy projects, to meet the needs of AI. This trend reflects a fundamental shift: as AI advances, venture capital firms recognize that the infrastructure that supports AI (such as chips, servers and data platforms) is as important as the algorithms themselves.
3) Large late-stage financing rounds take center stage
Venture capital firms are pouring money into AI companies with established business models, pushing some funding rounds into the billions. While early-stage investments are still happening, late-stage funding rounds are taking over. In the third quarter of 2024 alone, the following major funding events took place:
Waymo (Alphabet’s self-driving division) raised $5 billion.
Safe Superintelligence, the AI research lab founded by OpenAI co-founder Ilya Sutskever, has received $1 billion in funding from top investors including Andreessen Horowitz and Sequoia Capital.
Cohere has completed a $500 million Series D funding round, bringing its valuation to $5.5 billion.
If that’s not big enough for you, OpenAI raised $6.6 billion in a funding round in October 2024, led by Thrive Capital, Microsoft, and Nvidia, at a valuation of $157 billion.
4) The rise of AI in specific fields
Venture capital firms are increasingly looking to invest in startups that apply AI to healthcare, finance, and defense:
Healthcare: AI is transforming drug discovery and diagnostics, and investors have taken notice, such as Insil1C0 Medicine (drug development) and Ainnocence (drug discovery).
Finance: AI is reshaping the decision-making process. For example, Taktile uses machine learning to help banks create customized credit scoring decision flows and recently raised $20 million. PolySign applies AI to digital asset security, demonstrating how machine learning can penetrate everything from lending practices to financial security.
Defense: Europe's Helsing completed a $488.2 million Series C round of financing, focusing on AI-driven military intelligence and defense systems; the United States' Shield AI focuses on military drones. The two startups demonstrated the expanding role of artificial intelligence in defense technology, and real-time insights and automation are becoming increasingly important.
5) Fewer seed-stage deals, more selective investors
Seed-stage deals have slowed as venture capital firms have become more selective about their startups.
It is becoming increasingly difficult for early-stage AI startups to obtain funding, especially without clear potential. Venture capital firms prefer to invest in later-stage companies that already have a clear path to profitability, which may include companies with strong historical growth, a stable customer base, and a broad market space, such as Cognigy (C Series C financing of $100 million).
4. Part 3: 5 key opportunities that will lead the next billion-dollar AI startups
Generative AI and underlying models are the biggest craze in 2024. So, what will we see next in the AI space that could give rise to the next billion-dollar AI startup?
My key predictions
The next AI revolution is not about making technology smarter, but about fundamentally changing the way we live, work, and even age.
Here are my top three predictions for the future:
1) The Internet as we know it will disappear.
Say goodbye to Google Search, Bing, and Yahoo. The next evolution of the internet will no longer be a simple search box, but a dynamic field of digital agents doing the browsing for us. Imagine tens of billions of individual AI agents handling everything from research to filtering out spam ads and bots. The days of “do-it-yourself” search may soon be a relic of the dial-up era.
2) We will get closer to human immortality.
From anti-aging breakthroughs to AI-driven health diagnostics, we are moving toward a future where living to 100 may become the norm. Advances in AI in the fields of molecular biology and regenerative medicine could transform aging into a solvable problem.
3) Collaboration between humans and AI will become the norm.
Forget the “AI replacing jobs” narrative; we are entering a new era where human intuition, creativity, and moral judgment combined with AI’s data processing and analytical capabilities will help solve problems that neither humans nor AI can solve alone. This collaboration will be the defining trend of the next decade.
These changes are setting the stage for the rise of the next wave of billion-dollar startups.
Here are five opportunities that will create the next billion-dollar startup:
1) Automated robots: the rise of home and industrial assistants
Human-AI collaboration has the potential to fundamentally change robotics, creating automated systems that support us rather than replace us. Autonomous robots are already entering our homes and workplaces, providing hands-free assistance in areas where human presence is limited.
Consumer applications: Figure and Tesla's Optimus are leading this change, launching affordable humanoid robots for home use. Imagine a future where middle-class families have robot assistants to help with childcare and housework, just like they have washing machines or dishwashers.
Industrial Applications: Agility Robotics, Sanctuary AI, and Co.bot are advancing collaborative robots in industrial settings. Co.bot recently raised $100 million in a Series B round, demonstrating the growing demand for “collaborative robots” (cobots), which are able to work safely alongside humans to handle heavy or repetitive tasks. With robots taking on labor-intensive tasks, humans can focus on strategic tasks, improving productivity and safety.
2) Energy grid: Building a sustainable and efficient energy system
The energy industry remains an underdeveloped area in the field of artificial intelligence, with great potential to optimize and autonomously manage energy usage. The vision of the future is that every home and business will have access to a smart energy management system, creating a resilient and efficient grid.
Autogrid (now part of Schneider Electric) uses artificial intelligence to optimize energy distribution in real time, minimize waste, and increase the reliability of renewable energy. Grid AI and Stem Inc. are also making progress in demand forecasting and energy storage solutions, supporting smart grids and potentially reducing carbon footprints at scale.
3) Quantum molecular modeling in drug discovery
In healthcare, quantum molecular modeling offers unprecedented potential for drug discovery and materials science. By combining quantum computing and artificial intelligence, we can accelerate the screening of promising drug candidates, saving time, cost, and potentially saving lives.
Insil1C0 Medicine uses artificial intelligence to predict molecular behavior, significantly shortening the time to find new drug candidates. Schrodinger uses quantum modeling to perform precise drug interaction simulations, while Atomwise uses deep learning to design disease-specific compounds.
4) Artificial Intelligence in Entertainment: The Rise of Synthetic Media and Hyper-Personalized Content
The entertainment industry is seeing a creative transformation driven by AI, with synthetic media and personalized content redefining storytelling. AI can now not only generate media content but also collaborate with creators to create innovative and high-quality experiences.
In a conversation with Farid Haque, venture partner at AlphaQ Venture Capital and investor in AI and deep tech, he shared his vision of AI creating movies and series where real actors become a "high art" experience. As AI-driven production handles routine content creation, live-action performances will become scarce and highly sought after, adding a layer of uniqueness to live-action film and television productions.
Actors can license the rights to their voices and facial expressions to AI-generated films, creating new revenue streams while retaining the “high art” nature of human-led performances. As AI technology develops, the economic model changes, studios can use actors’ digital archives, and traditional live performances become a high-end experience.
DeepBrain AI allows actors to license the use of digital “clones” of themselves, opening up new revenue models. Flawless AI makes speech and lip syncing seamless across languages, driving a revolution in global media distribution.
5) Games and high-level NPCs (non-player characters)
Games are one of the most natural areas for humans to collaborate with AI, as AI enables deeper interactions, more realistic NPCs (non-player characters), and highly personalized gaming experiences. Here, AI is more than just a tool, it is a co-creative partner with players that can continuously adapt and evolve based on player behavior.
Inworld AI is developing NPCs that can remember players' past interactions, creating a more immersive and responsive game world. This collaboration between players and AI characters opens up a new dimension of interaction.
5. Challenges and ethical considerations
As AI systems continue to advance, it becomes critical to ensure they are used ethically and responsibly. Building systems that avoid discriminating against specific groups or exacerbating latent biases in human data is necessary. AI is inherently a social justice issue.
Currently, more than 3 billion people in the world still do not have access to the internet, and women account for a large proportion of them - which makes artificial intelligence likely to exacerbate the digital divide. In order for artificial intelligence to be a truly good force, people need reliable internet access and digital literacy. Today, nearly 40% of the world's population does not have access to the internet, and even more people have very limited experience using digital tools. This imbalance may cause artificial intelligence systems to favor privileged groups, further exacerbating bias and exclusion.
Therefore, it is critical to invest in inclusive AI to reach underserved communities. From AI-driven distance education to accessible healthcare to digital tools to promote rural development, venture capitalists, technology leaders, and policymakers need to address the digital divide and advocate for inclusive AI models that benefit everyone.
6. Conclusion
As AI becomes ubiquitous in everything from our search engines to our homes, it’s clear that this technology is here to stay and it’s not going away. The AI “hype” is over, and we’re tired of companies and marketing gimmicks that claim to be “AI.” It’s not a 90s fad, it’s a reality of our daily lives. Venture capital is spawning a new wave of startups that will change the way we live and work, from robotics to energy to media.
The challenge for investors and innovators is to look beyond the hype and focus on the real impact. AI is more than just a trend – it’s a transformation that’s destined to last. This is just the beginning, and there’s more to come.