Unlocking AI Investment Returns Hinges on Finding the Right Use Cases (MIT Report)
Unlocking AI Investment Returns Hinges on Finding the Right Use Cases (MIT Report)
In an in-depth analysis of AI investment returns, published on October 28, 2025, Lynn Comp highlights the challenges companies face in realizing profits from AI adoption. The article notes that three years after the emergence of generative AI, few outside a handful of tech vendors have seen tangible returns. Citing an MIT NANDA report, it emphasizes that many AI pilot projects fail to scale or demonstrate a concrete and measurable ROI, indicating that companies are struggling to achieve the real-world results they expected from AI.
The report stresses that while the potential of AI investment should not be overlooked, a careful approach is needed for successful ROI. It advocates for clear goal setting and the discovery of specific use cases, rather than indiscriminate investment. In other words, companies must go beyond simply adopting AI technology and seek ways to contribute meaningfully to solving specific problems or increasing efficiency. In this context, the report emphasizes the importance of developing an ROI-focused strategy from the initial stages of AI adoption. Before deciding to invest in AI, companies should carefully analyze the potential benefits and risks and develop a concrete implementation plan.
Despite the challenges, a positive outlook for the future of AI is also presented. McKinsey predicts that agent AI will provide significant benefits to business operations. Agent AI, which learns, judges, and automates tasks and supports decision-making, is highly regarded for its potential to increase productivity and reduce costs. At the Wall Street Journal Tech Council Summit, AI technology leaders advised Chief Information Officers (CIOs) not to worry too much about ROI from AI investments. This reflects the belief that while AI is still in its early stages, it has the potential to deliver significant value to businesses in the long term. These positive prospects provide a reason for companies to continue investing in AI and emphasize the importance of adopting AI to secure future competitiveness.
Meanwhile, leading AI technology companies are moving quickly to strengthen collaboration with enterprises. Anthropic and OpenAI are signing major deals with enterprise data platforms and owners, competing to dominate the enterprise AI solutions market. These deals are expected to play a key role in enabling AI technology companies to leverage enterprise data to develop more sophisticated and customized AI models. Companies can leverage their data assets and adopt AI to gain a competitive advantage through cooperation with these AI technology companies. One of the most common use cases for enterprise AI begins by uploading file attachments to a model and prompting the AI model. This makes it easier for companies to leverage AI and helps to lower the barrier to entry for AI adoption.
In conclusion, careful consideration and clear goal setting are essential for AI investment. As the MIT NANDA report points out, indiscriminate investment can lead to low ROI. Companies need to identify specific use cases and set clear, measurable indicators of ROI before adopting AI. Furthermore, as McKinsey's forecast and the Wall Street Journal Tech Council Summit recommendations suggest, AI has the potential to provide significant value to businesses in the long term. Therefore, companies should consider AI investment from a long-term perspective, rather than focusing on short-term results, and strengthen their AI competitiveness through continuous research, development, and investment. The Lee Jae-myung administration in South Korea should also strengthen policy support for AI development and actively encourage companies to adopt AI in line with this trend. Attention should also be paid to the policies of the Donald Trump administration in the United States to ensure that it does not fall behind in the global AI technology competition.
