Written by: Raman Rai
Translated by: Blockchain in Plain Language
TL;DR:
AI investments hit a new high: the global AI market is expected to reach $13 trillion by 2030. As venture capital firms bet on startups that are reshaping industries, AI investments are experiencing explosive growth.
One of the key investment areas for 2024 is AI infrastructure: as the demand for computational power increases for AI models, venture capital firms are ramping up investments in AI infrastructure, including specialized chips and data centers.
Notable funding trends: late-stage financing and AI infrastructure investments dominate, while AI applications in healthcare, finance, and defense attract significant investments, with investors seeking projects that create real impact.
The next billion-dollar startup: the future of AI investment will focus on areas like automation robots, energy, and entertainment, where human-AI collaboration has paved the way for groundbreaking startups.
1. An Introduction to AI in the Venture Capital Ecosystem
With billions of dollars flooding into the AI space, it can be said that the 'AI boom' has not waned—and will only continue to grow.
AI has become one of the most aggressively funded industries in the venture capital space.
According to Pitchbook data, global AI investment reached $290 billion over the past five years, with private investment firms conducting over 15,400 deals since 2022. This intense activity reflects a strong confidence in the future of AI. There are differing opinions on how large the AI market will become by 2023.
According to McKinsey's data:
'AI has the potential to bring $13 trillion in growth to the global economy by 2030, equivalent to a cumulative GDP increase of 16% compared to now. This means an additional annual GDP growth of 1.2%.'
Statista and Bloomberg Intelligence both predict that by 2030, the AI market could grow to $2 trillion, covering everything from AI software to hardware and services. PwC estimates that AI could contribute $15.7 trillion to the global economy by 2030 primarily through increased productivity and heightened consumer demand for AI-enhanced products.
It can be said with certainty that AI has become a part of our daily life, and the hype has passed. However, with excitement comes noise—investors now face thousands of AI companies, each claiming to be the next 'big star.' Data privacy issues, talent shortages, ethical AI, and centralization risks add further challenges to this already competitive industry.
2. Part One: How to Navigate Noise in a Competitive Market
Today, over 100 venture capital funds are actively investing in the AI market, covering horizontal applications (like infrastructure) as well as vertical applications involving specialized industries such as healthcare, finance, and agriculture.
To understand the current state of venture capital in the AI field, I will introduce two types of investors:
Pioneers: active investors willing to boldly bet across multiple AI domains. Pragmatists: conservative funds that see potential in AI but are more selective or cautious in their investments.
1) Pioneers: The most active venture capital firms
Pioneers are known for their willingness to take risks and lead trends, playing a crucial role in shaping the future of AI investment. Here are some notable players:
Andreessen Horowitz (a16z) has made 29 investments since 2023 across multiple fields, including a $100 million investment in Character.AI and a $224 million investment in Genesis Therapeutics. a16z has made significant bets at the intersection of AI, biotechnology, and consumer technology.
Sequoia Capital has adopted a particularly aggressive strategy, leading financing rounds for several well-known startups, such as Cohere (language models) and Viz.ai (medical imaging). In 2023, about 60% of Sequoia's new investments were focused on AI, up from just 16% the previous year, a significant increase.
General Catalyst has invested $750 million in the healthcare AI sector, including companies like Commure, Sword Health, and Overjet. They have made 19 AI investments, of which less than half involve generative AI (GenAI) projects.
Alumni Ventures has made numerous investments in AI 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, said:
'Over the past year, AI has injected new life into the investment ecosystem.'
2) Pragmatists: Conservative venture capital firms
As pioneers rush in, pragmatists choose to wait and see.
These funds see the potential of AI but tend to take a more selective approach, focusing on sustainable returns and more stable market conditions. Here are some typical examples:
Kleiner Perkins tends to choose relatively safe AI investments, such as Together AI ($102.5 million Series A), which supports the development of AI across a wide range of applications.
Benchmark Capital is known for its anti-hype philosophy; they led an 11x $24 million Series A financing in September 2024 for a startup aiming to create automated digital employees to streamline go-to-market operations. Benchmark Capital prefers to focus on practical solutions rather than speculative technologies.
Bessemer Venture Partners 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) reflects their cautious investment strategy; EvenUp is an AI startup that helps personal injury lawyers automate medical documentation.
Union Square Ventures has invested about $150 million in AI, primarily focusing on applications driven by network effects. Their investment in Recursion Pharmaceuticals aligns with their belief that network effects outweigh high-risk technologies; Recursion utilizes AI for drug discovery.
GGV Capital has invested around $180 million in AI, preferring mature areas like SaaS and enterprise software, using AI as an additional technology rather than a core technology. Their strategy supports growth without delving into experimental technologies.
So, what is causing the hesitation of these funds?
Pragmatists remain cautious about the challenges brought by AI:
High capital demands: Developing AI is costly—from data to computing power—these venture capital firms hold a cautious stance on large upfront investments.
Regulatory uncertainty: As AI regulation lags behind its rapid development, pragmatic funds prefer to wait for rules to clarify before making decisions, especially in fields like autonomous driving and healthcare.
Market volatility: The skyrocketing valuations of AI startups have raised concerns among some investors about a potential 'AI bubble' bursting. Pragmatic funds avoid over-investing during market overheating until the hype settles.
Ethical and privacy issues: With tightening global data regulations, the ethical problems facing AI have increased risks. Pragmatic funds remain cautious, avoiding investments in areas where privacy issues might overshadow returns.
3) Have pragmatists missed out on good opportunities?
Conservative funds like Kleiner Perkins, Bessemer Venture Partners, Benchmark Capital, Union Square Ventures, and GGV Capital may be seen as missing out on AI investment opportunities due to their cautious investment approaches. However, this conservative stance is not necessarily a disadvantage. Their selective investment strategy, while providing stability and enabling them to capitalize on rapid AI growth, may also lead to missing out on opportunities with transformative potential in the long run.
Pioneers like Sequoia and a16z have made significant investments in foundational AI and generative technologies, ultimately paving the way for the next era of technological transformation. If AI continues to grow at its current pace, the cautious stance of pragmatists may leave them on the sidelines in this industry that could define the next decade.
3. Part Two: Top AI Funding Rounds in 2024
Now that we understand which major venture capital funds are leading the AI field, let's take a look at the startups receiving the most funding support in 2024.
Major deals in Europe and the U.S. in Q4 2024:
Glean (Series E financing $260 million): An AI-based enterprise search engine, valued at $4.34 billion.
Codeium (Series C financing $150 million): An AI programming platform that enhances developer productivity, valued at $1.1 billion.
Opkey (Series B financing $47 million): A company providing an AI testing automation platform for finance, HR, and enterprise planning.
Butlr (Series B financing $38 million): Focused on providing anonymous people sensing and occupancy solutions using physical AI.
These transactions showcase the broad areas of AI application, attracting investor attention from logistics to automation.
So, what are the key themes driving AI financing in 2024?
1) Generative AI continues to attract significant investment
Despite the challenges of cost and scalability presented by generative AI, it remains a focal area for investment. In the past five years, generative AI startups have raised a total of $26 billion in funding, particularly in the fields of content creation, healthcare, and enterprise solutions, including companies like QuizGecko, Writesonic, and Tome.
2) AI infrastructure and hardware are receiving the most funding
As the demand for computational power increases for generative AI models, venture capital firms are betting on the 'pillars' 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, completed $640 million in Series D funding led by BlackRock, achieving a valuation of $2.8 billion. Groq's success illustrates the growing attention on companies supporting the 'engines' of AI (from chip design to large-scale computing).
BlackRock and Microsoft have jointly launched a $30 billion AI investment fund aimed at building AI infrastructure, including data centers and energy projects to meet the demands of AI. This trend reflects a foundational shift: as AI progresses, venture capital firms recognize that supporting the infrastructure for AI (such as chips, servers, and data platforms) is as important as the algorithms themselves.
3) Large late-stage funding rounds become the focus
Venture capital firms are pouring large amounts of money into AI companies with established business models, pushing some funding rounds into the billions. While early investments are still ongoing, later funding rounds are becoming dominant. In just the third quarter of 2024, there were several major funding events:
Waymo (Alphabet's self-driving division) raised $5 billion.
Safe Superintelligence, an AI research lab founded by OpenAI co-founder Ilya Sutskever, secured a $1 billion investment from top investors like Andreessen Horowitz and Sequoia Capital.
Cohere completed $500 million in Series D funding, bringing its valuation to $5.5 billion.
If you think this is still not big enough, then OpenAI raised $6.6 billion in its October 2024 funding round, led by Thrive Capital, Microsoft, and NVIDIA, achieving a valuation of $157 billion.
4) The rise of AI in specific domains
Venture capital firms are increasingly inclined to invest in startups applying AI in healthcare, finance, and defense:
Healthcare: AI is transforming drug discovery and diagnostics, and investors have taken note of this trend, such as Insil1C0 Medicine (drug development) and Ainnocence (drug discovery).
Finance: AI is reshaping decision-making processes, such as Taktile using machine learning to help banks create customized credit scoring decision flows, recently raising $20 million; PolySign applying AI to digital asset security, demonstrating how machine learning penetrates various aspects from lending practices to financial security.
Defense: Europe's Helsing completed $488.2 million in Series C funding, focusing on AI-driven military intelligence and defense systems; America's Shield AI specializes in military drones. Both startups showcase the expanding role of AI in defense technology, where real-time insights and automation are becoming increasingly important.
5) Seed-stage deals decrease, investors become more selective
Due to stricter vetting of startups by venture capital firms, seed-stage deals are slowing down.
For early-stage AI startups, securing funding is becoming increasingly difficult, especially without clear potential. Venture capital firms are more inclined 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 vast market space, such as Cognigy (Series C financing $100 million).
4. Part Three: 5 Key Opportunities That Will Lead to the Next Billion-Dollar AI Startups
Generative AI and foundational models are the biggest trends of 2024. So, what might we see next in the AI field that could give rise to the next billion-dollar AI startup?
My key predictions
The next AI revolution lies not in making technology smarter, but in fundamentally changing the way humans live—how we live, work, and even age.
Here are my 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 realm made up of digital agents completing our browsing tasks for us. Imagine hundreds of billions of personal AI agents handling everything from research to filtering out spam ads and bots. The era of 'do-it-yourself' searching may soon become a relic of the dial-up internet age.
2) We will be closer to human immortality.
From breakthroughs in anti-aging to AI-driven health diagnostics, we are moving towards a future where living to 100 could become the norm. Progress in AI in molecular biology and regenerative medicine may turn aging into a solvable problem.
3) Collaboration between humans and AI will become the norm.
Forget the phrase 'AI will replace jobs'; we are entering a new era where human intuition, creativity, and moral judgment combine with AI's data processing and analytical capabilities to help solve problems that neither humans nor AI can resolve alone. This collaboration will become the defining trend of the next decade.
These changes lay the groundwork for the next wave of billion-dollar startups.
Here are five opportunities that will create the next billion-dollar startups:
1) The rise of automated robots: household assistants and industrial aides
Collaboration between humans and AI could fundamentally change robotics, creating automation systems that support rather than replace us. Automated robots are already beginning to enter our homes and workplaces, providing hands-free assistance in areas where humans are present but limited.
Consumer Applications: Figure and Tesla's Optimus are leading this transformation by introducing affordable humanoid robots for home use. Imagine a future where middle-class households have robot assistants to help care for children and do household chores, just like having a washing machine or dishwasher.
Industrial Applications: Companies like Agility Robotics, Sanctuary AI, and Co.bot are advancing collaborative robots in industrial environments. Co.bot recently raised $100 million in Series B funding, showcasing the growing demand for 'collaborative robots' (cobots) that can safely work alongside humans to handle heavy or repetitive tasks. As robots take on labor-intensive jobs, humans can focus on strategic tasks, enhancing productivity and safety.
2) Energy Grids: Building sustainable, efficient energy systems
The energy sector remains an underdeveloped area in AI, with tremendous potential for optimizing and self-managing energy usage. The vision for the future is for every home and business to use smart energy management systems, creating a resilient and efficient power grid.
Autogrid (now part of Schneider Electric) uses AI to optimize energy distribution in real-time, minimizing waste and increasing the reliability of renewable energy. Grid AI and Stem Inc. have also made progress in demand forecasting and energy storage solutions, supporting smart grids that could significantly reduce carbon footprints.
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 with AI, we can accelerate the screening of promising drug candidates, saving time, costs, and potentially saving lives.
Insil1C0 Medicine uses AI to predict molecular behavior, significantly shortening the time to find new drug candidates. Schrodinger uses quantum modeling for precise drug interaction simulations, while Atomwise employs deep learning to design compounds targeting diseases.
4) AI in the entertainment industry: The rise of synthetic media and hyper-personalized content
The entertainment industry is witnessing a creative transformation driven by AI, where synthetic media and personalized content are redefining storytelling. AI can now generate media content and collaborate with creators to create innovative and high-quality experiences.
In a conversation with Farid Haque, a venture partner at AlphaQ Capital and AI and deep tech investor, he shared a vision of AI creating films and series where live actors become a 'high art' experience. As AI-driven production handles routine content creation, live performances will become scarce and highly sought after, adding a layer of uniqueness to live film and television productions.
Actors can authorize their voice and facial expression rights to AI-generated films, creating new revenue streams while retaining the 'high art' characteristic of human-led performances. As AI technology evolves, the economic model shifts, allowing studios to utilize actors' digital profiles, while traditional live performances become a premium experience.
DeepBrain AI allows actors to authorize the use of their digital 'clones,' opening up new revenue models. Flawless AI makes seamless cross-language voice and lip-syncing possible, driving a transformation in global media distribution.
5) Gaming and advanced NPCs (non-player characters)
Gaming is one of the most natural domains for human-AI collaboration, as AI enables deeper interactions, more realistic NPCs (non-player characters), and highly personalized gaming experiences. Here, AI is not just a tool; it is a co-creative partner with players, continually adapting and evolving based on player behavior.
Inworld AI is developing NPCs that can remember players' past interactions, creating a more immersive and responsive gaming world. This collaboration between players and AI characters opens up a new dimension of interactivity.
5. Challenges and Ethical Considerations
As AI systems continue to advance, ensuring they are used ethically and responsibly becomes crucial. It is necessary to build systems that avoid discriminating against specific groups or exacerbating potential biases in human data. AI is fundamentally a social equity issue.
Currently, over 3 billion people globally lack internet access, with women making up a significant proportion—this creates the potential for AI to exacerbate the digital divide. To make AI a truly benevolent force, people need reliable internet access and digital literacy. Today, nearly 40% of the global population cannot go online, and many have very limited experience using digital tools. This imbalance could lead AI systems to bias privileged groups, further exacerbating prejudice and exclusion.
Therefore, investing in inclusive AI to cover underserved communities is crucial. From AI-driven remote education to accessible healthcare to digital tools that promote rural development, venture capitalists, tech leaders, and policymakers need to address the digital divide issue and advocate for inclusive AI models that benefit everyone.
6. Conclusion
As AI permeates every corner of our lives from our search engines to our homes, it is clear that this technology has embedded itself in human society and is here to stay. The 'hype' around AI has ended; we are weary of companies boasting 'AI' and marketing gimmicks. It is not a passing trend from the 90s, but a reality of our daily lives. Venture capital is giving rise to a wave of new startups that will change how we live and work, from robotics to energy to media.
For investors and innovators, the challenge is to move beyond the hype and focus on real impact. AI is not just a trend—it is a transformation destined to last. This is just the beginning; more changes await us in the future.