The Hype is Over: AI Landscape in Venture Capital 2024

CoinVoiceDec 19, 2024
The Hype is Over: AI Landscape in Venture Capital 2024

TL;DR:

  1. AI funding hits record high: The global AI market has the potential to deliver $13 trillion by 2030. AI investment is booming as VCs bet on startups that are reshaping industries.
  2. AI infrastructure is one of the key investment areas in 2024: As AI models demand increasing computing power, VCs are pouring resources into AI infrastructure, including specialised chips and data centers.
  3. Funding trends to watch: Late-stage funding and AI infrastructure investment dominate while AI applications in healthcare, finance and defence sectors are capturing huge investment as investors seek real world impact.
  4. The next billion dollar startups: The future of AI investment lies in areas, such as autonomous robotics, energy and entertainment, where human-AI collaboration is already paving the way for groundbreaking startups.

At a glance:

In this article I’ll be covering:

  • Introduction to AI in the VC Ecosystem
  • Part 1: Navigating noise in an overcrowded market
  • Part 2: Top AI funding rounds in 2024
  • Part 3: 5 key opportunities that will lead to the next billion dollar AI startup
  • Challenges and Ethical Consideration

Introduction to AI in the VC Ecosystem

With billions pouring into the AI race, it is fair to say that the ‘’AI hype’’ has not died down — and it’s only getting bigger.

AI has emerged as one of the most aggressively funded sectors in venture capital.

In five years, global AI funding has hit $290 billion with private investment firms completing over 15,400 deals since 2022 alone, according to Pitchbook. This intense activity reflects the high level of confidence in AI’s future. There are many differing views on how big the AI market will become by 2023.

According to McKinsey & Co:

“AI has the potential to deliver $13 trillion by 2030, or about 16 percent higher cumulative GDP compared with today. This amounts to 1.2 percent additional GDP growth per year.”

Statista and Bloomberg Intelligence both forecast the AI market could grow to $2m trillion by 2030, covering sectors from AI software to hardware and services. PwC predicts that AI could contribute to $15.7 trillion to the global economy by 2030 primarily through productivity gains and increased consumer demands for AI-enhanced products..

It is official — AI is here to stay as part of our daily lives. The hype is over.

However, with excitement has come noise — investors now face an overwhelming array of AI companies, each claiming to be the next big thing. Data privacy concerns, talent shortages, ethical AI and centralisation risks adds challenges to an already competitive field.

Part 1: Navigating noise in an overcrowded market

Today, more than 100 VC funds are actively investing in the AI market, covering both horizontal applications, such as infrastructure, and vertical applications across specialised industries including healthcare, finance and agriculture.

To understand the current state of venture capital in AI, I shall introduce two types of investors:

  • Pioneers: Active investors who are placing bold bets across various AI sectors.
  • Pragmatists: Conservative funds who see promise in AI but remain selective or cautious.

Pioneers: The most active VCs

Pioneers are known to be risk-takers and trendsetters who shape the trajectory of AI investment. Here are a few notable players:

As Stephanie Zhan, a Sequoia Capital partner who invests in seed and early-stage companies, notes:

“AI has brought new life to the investing ecosystem in the last year.”

Pragmatists: The Conservative VCs

While Pioneers rush in, Pragmatists take a step back.

These are the funds that see AI’s potential but prefer a selective approach to revenue and more stable market conditions. Notable examples include:

  • Kleiner Perkins prefer to stick to safer bets in AI investments, such as Together AI ($102.5 million Series A) where foundational technologies support broad applications in AI.
  • Benchmark Capital: Known for its anti-hype philosophy, Benchmark led a $24 million Series A funding round for 11x in September 2024, a startup creating autonomous digital workers to streamline GTM operations. Benchmark prefer a focus on practical solutions rather than speculative technology.
  • Bessemer Venture Partners: Bessemer has invested around $250 million in AI, focusing on applications that solve for real-world problems rather than chasing hype. Their support of EvenUp ($50.5 million Series B),an AI startup that assists personal injury lawyers in automating medical documents, reflects their cautious approach.
  • Union Square Ventures (USV): USV’s AI investments are estimated around $150 million, primarily in network-driven applications. Their investment in Recursion Pharmaceuticals, which uses AI for drug discovery, aligns with their thesis of network effects over high-stakes tech.
  • GGV Capital: With about $180 million in AI investments, GGV favours established sectors like SaaS and enterprise software, using AI as an add-on rather than a central focus. Their approach supports growth without diving into experimental tech.

So, what is causing the hesitance?

Pragmatists are wary of the challenges AI brings:

  1. High capital requirements: Developing AI is expensive — from data to compute power — and these VCs are hesitant to make large upfront bets.
  2. Regulatory uncertainty: As AI regulation lags behind its rapid development, pragmatists prefer to wait until the rules are clearer, especially in fields like autonomous driving and healthcare.
  3. Market volatility: AI startup valuations are skyrocketing, and some investors worry about an “AI bubble” that could burst. Pragmatists avoid overhyped markets until the hype settles.
  4. Ethical and privacy concerns: With data regulations tightening worldwide, AI’s ethical concerns add risk. Pragmatists stay cautious, avoiding areas where privacy concerns could overshadow returns.

Are 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 approach. However, this conservative stance is not necessarily a disadvantage. Their select approach provides stability and rapid AI growth, although it may risk missing out on transformative opportunities in the long term.

Pioneers like Sequoia and a16z claim stakes in foundational AI and generative technologies, so ultimately they’re paving the way for the next era of technological transformation. If AI continues to grow at its current pace, the Pragmatists’ cautious stance could leave them sidelined in what may be the defining sector of the decade.

Part 2: Top AI funding rounds of 2024

Now that we know which big VC funds are ruling the AI landscape, let’s look at the start-ups who received the biggest cheques in 2024.


Notable deals in Q4 2024 across Europe and the US:

  • Glean (raised $260 million in Series E): An enterprise AI-based search engine with a valuation of $4.34 billion.
  • Codeium ($150 million in Series C): An AI coding platform to boost developer productivity, valued at $1.1 billion.
  • Opkey ($47 million in Series B): An AI test automation platform for finance, HR, and enterprise planning.
  • Butlr ($38 million in Series B): Specializing in anonymous people-sensing and occupancy solutions using physical AI.

These deals demonstrate the range of AI applications capturing investors’ attention, from logistics to automation.

So what are the key themes that is driving AI funding in 2024?

  1. Generative AI continues to bring in massive investment

Generative AI remains a top investment area despite the cost and scalability challenges it brings. Generative AI startups have received an astounding $26 billion in funding over the last five years particularly across content creation, healthcare and enterprise solutions, including QuizGeckoWritesonic and Tome.

2. AI infrastructure and hardware are receiving the most funding

As generative AI models demand more and more computing power, VCs are betting on the backbone of it all: AI infrastructure. Companies developing specialised chips, data centers, and platforms are seeing increased funding:

  • Groq, an AI semiconductor and software startup, raised $640 million in a Series D round led by BlackRock, and is now valued at $2.8 billion. Groq’s success shows the growing appetite for companies supporting the “engine room” of AI, from chip design to large-scale computing.

BlackRock and Microsoft have launched a $30 billion AI investment fund to build AI infrastructure including data centres and energy projects to meet the demands of AI. This trend reflects a foundational shift: with AI advancing, VCs recognise that the infrastructure supporting AI (think chips, servers, and data platforms) is as critical as the algorithms themselves.

3. Large late-stage rounds are taking centre stage

VCs are pouring substantial capital into established AI companies with proven models, pushing some funding rounds into the billions. Although early-stage investment is still happening, late-stage rounds are dominating. In Q3 2024 alone, we saw:

And if you thought that was big, OpenAI’s October 2024 round raised $6.6 billion, led by Thrive CapitalMicrosoft, and Nvidia, bringing its valuation to $157 billion.

4. Sector-specific AI is on the rise

VCs are increasingly drawn to startups applying AI in healthcare, finance, and defence:

  • Healthcare: AI is transform drug discovery and diagnostics, and investors are noticing such as Insilico Medicine (drug development) and Ainnocence (drug discovery).
  • Finance: AI is reshaping decision-making, for example Taktile uses machine learning to help banks create customisable decision flows for credit scoring, recently raised $20 million. PolySign applies AI to digital asset security, illustrating how machine learning is finding its way into everything from lending practices to financial security.
  • Defence: Europe’s Helsing, raised $488.2 million in a Series C round, specialising in AI-powered military intelligence and defense systems. Shield AI in the US focuses on autonomous drones for military operations. Both startups showcase AI’s expanding role in defence technology where real-time insights and automation are needed.

5. Less seed-stage deals due to higher selectivity

Seed-stage deals are slowing as investors zero in on startups with established product-market fit.

For early-stage AI startups, it’s becoming harder to secure funding without proven potential. VCs are prioritising late-stage rounds for companies with clear paths to profitability which could include strong historical tracton, strong customer base that are not moving to competitors and a large market where they are a niche, such as Cognigy ($100 million in Series C round).

Part 3: 5 key opportunities that will lead to the next billion dollar AI startup

Generative AI and foundation models were the biggest hype of 2024. But, what are we seeing next in the AI space that could make the next billion dollar AI startup.

My key predictions

The next AI revolution is not about making tech smarter but fundamentally about changing human experience — the way we live, work and even age.

Here are three predictions on what the future could hold:

  1. The internet as we know it will vanish. Goodbye Google Search, Bing and Yahoo. The next evolution of the internet won’t be a simple search bar but a dynamic field of digital agents doing the browsing for us. Imagine tens of billions of personal AI agents handling everything from research to filtering out spammy ads and bots. The era of “do it yourself” web searches may soon be dated as dial-up.
  2. We will take a leap closer to human immortality. From anti-aging breakthroughs to AI-powered health diagnostics, we’re coming closer towards a future where living to 100 could be the baseline. AI-driven advances in molecular biology and regenerative medicine may turn aging into a solvable problem.
  3. Human-AI collaboration will be the norm. Forget “AI replacing jobs”, we’re entering an era where human intuition, creativity and ethical judgement combined with AI’s data processing and analytical capabilities will help solve problems neither could solve alone. This partnership will be the defining trend of the next decade.

These shifts are laying the groundwork for the next wave of billion dollar startups.

Here are 5 biggest opportunities that will create the next billion dollar startup:

1. Autonomous Robotics: The rise of household helpers and industrial assistants

Human-AI collaboration could fundamentally transform robotics, creating autonomous systems that support rather than replace us. Autonomous robots are already entering our homes and workplaces, providing hands-free assistance in areas where human presence is essential yet limited.

  • Consumer applicationsFigure and Tesla’s Optimus are leading the charge with affordable humanoid robots aimed at household use. Imagine a future where, like owning a washing machine or dishwasher, middle-class homes have in-house robotic helpers for childcare and chores.
  • Industrial ApplicationsAgility RoboticsSanctuary AI, and Co.bot are advancing collaborative robotics for industrial settings. Co.bot recently raised $100 million in Series B funding, demonstrating the growing demand for “cobots” that work safely alongside humans on physically demanding or repetitive tasks. With robots handling the labour-intensive work, humans can focus on strategic tasks, enhancing productivity and safety.

2. Energy Grids: Building sustainable, efficient energy systems

The energy sector remains a largely untapped area in AI, with opportunities to optimise and autonomously manage energy use. The vision is for every home and business to utilise intelligent energy management systems, creating a resilient and efficient grid.

  • Autogrid, now part of Schneider Electric, uses AI to optimise energy distribution in real-time, minimising waste and making renewable energy more reliable. Grid AI and Stem Inc. are also making strides in demand prediction and energy storage solutions, supporting smart grids that could reduce carbon footprints on a massive scale.

3. Quantum Molecular Modelling in Drug Discovery

In healthcare, quantum molecular modelling offers unprecedented potential in drug discovery and materials science. By combining quantum computing and AI, we can accelerate the identification of promising drug candidates, saving time, costs, and potentially lives.

  • Insilico Medicine uses AI to predict molecular behaviour, significantly reducing the time it takes to find new drug candidates. Schrodinger applies quantum modelling for accurate drug interaction simulations, while Atomwise employs deep learning to design disease-targeted compounds.

4. AI in Entertainment: The rise of synthetic media and hyper-personalised content

The entertainment industry is starting to see a creative transformation powered by AI, where synthetic media and personalised content redefine storytelling. AI can now generate media content and even partner with creators, allowing for innovative and high-quality experiences.

In conversation with Farid Haque, Venture Partner at AlphaQ Venture Capital and AI and DeepTech Investor, he shared his vision for AI-created films and series, where real human actors become a “high art” experience. As AI-driven production takes on routine content creation, real human performances will become rare and sought-after, adding a layer of exclusivity to live-action productions.

Actors could sign rights to their voice and face for AI-generated films, creating a new revenue stream while preserving the “high art” of human-led performances. The economic model shifts as AI technology allows studios to use actors’ digital profiles, while traditional, in-person acting becomes a premium experience.

  • DeepBrain AI allows actors to license digital “clones” of themselves, opening new revenue models. Flawless AI enables seamless voice and lip-syncing across languages, transforming global media distribution.

5. Gaming and Advanced NPCs

Gaming is one of the most natural fits for human-AI collaboration, as AI enables deeper engagement, more realistic NPCs (non-playable characters) and highly personalised gaming experiences. Here, AI isn’t just a tool — it’s a co-creator that adapts and evolves with players.

  • Inworld AI is developing NPCs that can remember past player interactions, creating a more immersive and responsive game world. This collaboration between players and AI characters opens new dimensions of interactivity.

Challenges and ethical considerations

As AI systems become more advanced, ensuring they are used ethically and responsibly becomes critical. It’s essential to build systems that avoid discriminating against certain groups or reinforcing biases embedded in human data. AI is, at its core, a social equity issue.

With over 3 billion people still offline — disproportionately women — AI risks deepening the digital divide. For AI to be a true force for good, people need reliable internet access and digital literacy. Today, nearly 40% of the global population lacks internet access, with even more having minimal experience with digital tools. This imbalance risks creating AI systems that favour the privileged, furthering bias and exclusion.

Investment in inclusive AI that reaches underserved communities is essential. From AI-driven remote education to accessible healthcare and digital tools for rural development, VCs, tech leaders, and policymakers need to address the digital divide and champion inclusive AI models that can empower all.

Conclusion

As AI exists within our search engines to our homes, it’s clear that this technology isn’t going anywhere. The AI “hype” is over as we’ve exhausted ourselves with the list of “AI” labelled companies and marketing fluff. It is not a 90s fashion trend that will come in and out of fashion — it has become the reality of our daily lives. Venture capital is creating a new wave of startups that will change how we live and work, from robotics to energy to media. For investors and innovators, the challenge is to look past the hype and focus on real-world impact. AI isn’t just a trend — it’s a shift that’s here to stay. The journey has just begun, and there’s much more ahead.

Source:Raman Rai

Author

This article is for informational purposes only. It is not offered or intended to be used as investment or other advice.

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