# AI ROI Outside Tech Sector May Take Longer to Materialize
What if the billions poured into AI ROI outside the tech sector don't yield profits for another decade? A recent report from Apollo Global Management suggests that non-technology industries face a significantly longer "ROI runway."
While Silicon Valley celebrates immediate gains, traditional industries are still finding their footing with artificial intelligence returns.
Why the AI Payoff Is Lagging for Non-Tech Industries
> "The AI boom has evolved far beyond a technology story, but its impact on bottom lines varies wildly by sector."
The gap between tech-native firms and traditional enterprises is becoming a defining feature of the current market cycle. For many companies, initial excitement is meeting the cold reality of high implementation costs. According to a study by McKinsey, only 20% of companies have successfully scaled AI initiatives beyond pilot stages, highlighting the challenges faced by non-tech sectors.
This suggests that the "easy money" phase of AI adoption has already peaked for the average business outside Silicon Valley.
The Infrastructure Hurdle Slowing AI Returns
Shifting Focus to Operations
According to Torsten Sløk, Chief Economist at Apollo, the AI narrative is moving into a new phase. Success now depends on operational value creation rather than just adopting the latest software. A report by Gartner indicates that 75% of enterprises will shift from piloting to operationalizing AI by 2024, emphasizing the need for robust infrastructure.
This transition requires a fundamental rethink of how companies manage their data and workflows in private markets. Without modernized infrastructure, meaningful AI ROI remains elusive.
>📌 READ MORE: The growing compute shortage and its impact on global markets
What Traditional Industries Are Facing
Key Challenges to AI Adoption
Non-tech companies must navigate several hurdles before seeing a return on their AI investments. These include legacy systems, talent shortages, and the high cost of specialized hardware. A survey by Deloitte found that 47% of executives cite integration with existing systems as a major barrier to AI adoption.
The timeline for these changes often spans years, not months. Here are the key considerations for this new phase:
- Operational value: Creating efficiency through deep integration.
- Scale: Achieving enough volume to offset high initial costs.
- Disciplined underwriting: Ensuring investments are backed by realistic projections.
- Policy support: Using government initiatives to bolster growth.
An Industrial Renaissance Powered by AI
Reshaping Manufacturing
Sløk suggests that an "industrial renaissance" is currently reshaping the manufacturing landscape. AI is a vital tool in this process, but it is not the only driver of change. According to the World Economic Forum, AI could add $3.7 trillion to the manufacturing sector by 2035, but this requires strategic alignment with policy frameworks.
Government policy is providing additional support for this growth. It creates new investment opportunities for those with patience and a long-term AI strategy.
>📌 READ MORE: Apollo Academy's 2026 outlook on private markets
Patience Will Define AI Investment Winners
The path to AI profitability is a marathon, not a sprint, for industries outside the tech bubble. Non-technology sectors must commit to disciplined execution and realistic timelines. A report by Forrester predicts that 60% of AI investments will fail to meet ROI expectations by 2025, underscoring the importance of patience.
Patience and strategic planning will separate the winners from the hype-chasers. Is your investment strategy built for a decade-long wait on AI returns?
