2024: The State of Generative AI in the Enterprise
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This report was originally published by Menlo Ventures. Read the the full report here.
Deep Dive: Infrastructure and the Modern AI Stack
After a year of rapid evolution, the modern AI stack stabilized in 2024, with enterprises coalescing around the core building blocks that comprise the runtime architectures of most production AI systems.
Foundation models still dominate. The LLM layer commands $6.5 billion of enterprise investment. However, through trial and error, enterprises increasingly understand the importance of data scaffolding and integrations in building sophisticated compound AI architectures that can perform reliably in production, not just as one-shot demos.
Our Predictions
2024 has been a year of transition and evolution, as the wave of hype we documented in 2023 gave way to real-world implementation. Drawing on the data we’ve shared today and the trends we’ve observed as investors, these are our three predictions for what lies ahead:
Agents will drive the next wave of transformation.
Agentic automation will drive the next wave of AI transformation, tackling complex, multi-step tasks that go beyond the capabilities of current systems focused on content generation and knowledge retrieval. Platforms like Clay and Forge foreshadow how advanced agents could disrupt the $400 billion software market—and eat into the $10 trillion U.S. services economy. This shift will demand new infrastructure: agent authentication, tool integration platforms, AI browser frameworks, and specialized runtimes for AI-generated code.
David beats Goliath: More incumbents to fall.
ChatGPT’s disruption of Chegg and Stack Overflow this year was a wake-up call: Chegg saw 85% of its market cap vanish, while Stack Overflow’s web traffic halved. Other categories are ripe for disruption. IT outsourcing firms like Cognizant and legacy automation players like UiPath should brace for AI-native challengers moving into their market. Over time, even software giants like Salesforce and Autodesk will face AI-native challengers.
No relief in sight: The AI talent drought intensifies.
We are on the brink of a massive talent drought. The tech industry will encounter severe scarcity as AI systems proliferate and become more sophisticated. This isn’t just a shortage of data scientists—it’s a critical gap in experts who can bridge advanced AI capabilities with domain-specific expertise. The talent pool is already dangerously low. Brace for soaring competition and 2-3x salary premiums for already well-paid AI-skilled enterprise architects becoming the norm. Despite investments in training programs and AI centers of excellence, the gap will outpace these efforts, fueling intense competition for the limited talent needed to power the next wave of AI innovation.