Companies involved in large language models (LLMs), chip manufacturing and data centres have attracted substantial funding and experienced remarkable growth in recent months. However, a major challenge to fully realising AI’s economic potential is the extent of its adoption in businesses. Amid this transition, investors are assessing how the AI industry will transform over the next decade. Will AI developers (which create AI technologies and applications, algorithms, frameworks, and tools) continue to deliver most of the value or will adopters (which use AI solutions to enhance business processes or offerings) generate greater returns? A balanced investment approach ensures AI technologies progress and scale effectively, avoiding overinvestment in one area at the expense of the other.
In our research, Algorithms vs. Applications: The AI investment perspective, we explore the factors that motivate investors to choose between AI developers and adopters. We analyse how they manage the risks associated with each option and how they can balance these risks to achieve their desired returns.
Key findings of the report:
- Global AI funding saw a recovery in Q2 2024, increasing to US$24.9bn from US$13.3bn in the first quarter. Funding in 2024 is set to surpass the total for 2023. Amid this recovery, there has been a mindset shift among investors that are focusing on AI developers: from “growth at all costs” to “capital-efficient growth”. Although the potential for profitability was always a consideration, investors are now prioritising developers who can demonstrate profitability (through discipline around costs) and create measurable value for their clients.
- Investor interest in AI adopters has surged, especially after the launch of generative AI (genAI), given its promise to enhance productivity. However, concerns remain that genAI may overshadow established AI technologies, such as predictive analytics and robotic process automation, particularly in asset-heavy industries where these traditional solutions could be more effective. As such, investors are scrutinising how AI is being implemented, assessing its ability to drive operational efficiencies and productivity, reduce costs and drive revenue.
- Late-stage venture capital (VC) is generally more open to risk than private equity (PE), which tends to favour lower-risk, mature investments. As such, VC firms are likely to maintain their focus on AI developers, while PE firms are more likely to increase investment in adopters.
- Beyond developers and adopters, there is a substantial investment opportunity in AI infrastructure such as data centres. The growing demand for computational power to support AI applications over the next five to ten years underscores the long-term need for such infrastructure. There was a sharp increase in global funding for data centre hardware and software in 2024: the first eight months of this year saw investments worth US$12.5bn announced, up from an average of US$2.5bn annually between 2021 and 2023.
- Constructing an investment portfolio with both developers and adopters creates a valuable feedback loop. Investing along the AI value chain helps investors deepen their understanding of adoption timelines, implementation challenges, and unmet market needs. Sharing this feedback with developers in their portfolios allows these firms to refine their offerings, boosting potential returns. More broadly, ecosystem partnerships—among developers, adopters and infrastructure enablers—can drive value and the ultimate growth of the AI industry.
