2024 wasn’t just another year for AI—it was a year of profound transformation. From OpenAI’s groundbreaking advancements to a surge of venture capital, AI defined the technology conversation. Leaders pivoted, industries adapted, and the world felt AI’s growing influence at nearly every turn.
In January, AI models functioned mostly as advanced assistants—capable but circumscribed. By December, they had grown from playing a supporting role to setting new performance standards in both business and society. What started as a helpful tool was now a driving force of innovation.
Meanwhile, venture funding for AI and cloud companies in the U.S., Europe, and Israel reached an astonishing $79.2 billion by year’s end—a 27% increase from 2023. Investors sensed a seismic shift—and they were right.
From Humble Beginnings to Unstoppable Momentum
Rewind to early 2024. AI showed promise but remained boxed in: models could analyze, summarize, and generate, but they operated under tight constraints. By mid-year, those constraints had all but vanished. YC’s now-famous memo declared the end of vertical SaaS as we knew it and heralded a new era of agents. Suddenly, AI wasn’t just enhancing day-to-day tasks—it was automating entire workflows, from predicting churn to rewriting pitch decks.
Venture capital, always on the lookout for the next big thing, poured billions into AI-first startups. Healthcare diagnostics? Reimagined. Legal research? Streamlined. Even restaurant operations were overhauled by AI. The global AI market soared from $241.8 billion in 2023 to an estimated $305.9 billion in 2024—an increase of over 26%. In December, Perplexity AI landed $500 million in funding, catapulting its valuation to $9 billion with backing from SoftBank, Nvidia, and Jeff Bezos.
The Rise of Agents
In the midst of this acceleration, a wave of enthusiasm built around “agentic” frameworks—autonomous systems capable of tool-calling, task-chaining, and minimal human oversight. The vision was compelling: agents that could handle scheduling, manage projects, and even shape strategic plans, all on their own. Startups and open-source projects jumped in, believing these agents to be the next phase of AI evolution.
Yet the real-world results fell short of the hype. Many agentic frameworks struggled with complex or unpredictable tasks. As foundational models continued to improve, the necessity of standalone agentic layers came into question. Future AI systems might naturally integrate these capabilities, rendering separate frameworks redundant.
Still, the best agentic tools offered a glimpse of what could become seamless in 2025—fully autonomous AI that manages intricate tasks without missing a beat. That future is not here yet, but it’s on the horizon.
Startups and the Speculative Impact of AI
In this fast-changing environment, AI startups became central players—though many were gambling on possibilities rather than certainties. Their products hinged on reasoning models delivering on lofty promises, but as models advance, they often subsume the very features these startups create.
Healthcare startups envisioned AIs as diagnostic assistants on par with human doctors. Finance startups pursued predictive systems that could transform strategy. Yet only a fraction truly harnessed the improvements in foundational models; most simply bet on where AI might be in a year’s time. The result? An entire ecosystem built on speculation—some ventures poised for explosive growth, others fated to collapse under the next wave of model improvements.
Momentum, rather than clarity, characterized 2024. Falling AI deployment costs opened the door to all manner of experiments, from major corporations to scrappy home-based operations. This democratization allowed smaller players to compete in spaces previously reserved for tech giants. Now, we wait to see which of these startups can survive—and thrive—in an era of ever more capable AI.
The Reasoning Model Revolution
While generative AI took center stage in 2023, 2024 brought a new focus on reasoning models—AIs that move beyond generating text to solving problems dynamically. By scaling test-time compute, these models can adapt, analyze, and iterate in real time, hinting at a future where AI contributes meaningfully to complex tasks like strategy and high-level decision-making.
The leap from o1 to o3 models in just a few months was astonishing, sparking conversations about when (not if) AGI might arrive. The broader impact of these advances remains to be seen, but 2024 clearly set the stage for breakthroughs that could unfold in 2025.
OpenAI’s o3 and o3-mini
An inflection point arrived with OpenAI’s o3 model. It didn’t just lift the bar—it reset expectations entirely. With an 87.5% score on the ARC-AGI Benchmark (outperforming human baselines) and a near-perfect 96.7% on the AIME, o3 signaled that AI’s capabilities are extending beyond mere pattern recognition. Areas like finance, law, and engineering could be next in line for disruption.
However, these gains come with steep computational costs, raising questions of who can afford to leverage them. OpenAI plans to release o3-mini in early 2025, aiming to make advanced reasoning models more accessible to a broader range of companies and developers.
So where does that leave us? Reasoning AI can amplify our own expertise and creativity, rather than replacing it. Today’s question is less about what AI can do and more about what it can’t.
The Path Forward
Looking ahead, AI continues to gather momentum. Governments, businesses, and entire industries face a stark challenge: adapt or risk falling behind. Ethical, environmental, and equity concerns loom large. If 2024 taught us anything, it’s that AI’s evolution won’t slow down for us—it’s up to us to keep up.
All told, 2024 wasn’t just a year of progress; it was a turning point. And if history is any guide, such turning points don’t fade quietly—they accelerate. Buckle up for what comes next.
Tickers
Below is a curated list of companies poised to benefit from the trends discussed in this article. Some sit at AI’s cutting edge—developing foundational models or shaping cloud infrastructure—while others provide the underlying hardware and tools needed for AI’s rapid scale-up. Together, they capture the full spectrum of momentum that has defined and will continue to drive AI innovation.
- Nvidia (NVDA): Remains the gold standard in AI hardware, powering everything from generative text models to advanced reasoning systems.
- Microsoft (MSFT): With a deep investment in OpenAI and robust cloud services via Azure, Microsoft is positioned to scale as AI deployments broaden.
- Alphabet (GOOGL): Backed by trailblazing research (DeepMind, Google Research), Google continues to lead in search, cloud, and AI capabilities.
- Amazon (AMZN): AWS underpins myriad AI startups, and Amazon’s own ventures in healthcare and logistics stand to benefit from emerging agentic frameworks.
- Palantir (PLTR): Specializes in data analytics and AI solutions for government and enterprise—well placed for a future dominated by “reasoning” AI.
Second-Order Enablers
- Taiwan Semiconductor (TSM): Manufactures the cutting-edge chips fueling high-performance AI applications worldwide.
- Advanced Micro Devices (AMD): Nvidia’s main rival in GPUs and accelerators. If AMD can address driver issues, it may become a formidable challenger in data center hardware.
Disclaimer: This content is for informational purposes only and does not constitute financial advice. Always do your own research or consult a professional before making investment decisions.