Investing in complementary technology is pivotal in driving AI adoption, and companies that adopt it are more likely to see better AI outcomes. According to a new study, firms need to be ready to make a significant investment in AI to see any gains. Only when firms increase their intensity of AI adoption to at least 25%, meaning that they are using a quarter of the AI tools currently available to them, do growth rates pick up and investments in AI start to pay off. The study also found that adopting complementary technology, such as big data capabilities and cloud computing, contributes to better AI outcomes. The researchers suggest that firms need both the technology and the skills that go with it to utilize AI effectively and obtain the payoff at earlier stages of investment. Firms that need to protect their proprietary algorithms as intellectual property or that work with sensitive data sets they’d rather not allow a third party to process should build “absorptive capacity” in AI know-how. Conversely, if AI is a complement to a firm’s core work, the firm can license something that’s already available.
The Significant Investment in AI: What it Takes to See Gains for Startups
According to a recent study, businesses need to make a considerable investment in artificial intelligence (AI) to achieve any gains. The study shows that about 92% of large companies have been achieving returns on their investments in AI, with the same percentage increasing their AI investments. However, what does it take for startups and early-stage companies to get to this point?
Sukwoong Choi, a postdoctoral scholar at MIT Sloan, suggests that AI utilization is tied to startups’ products and services. In a new paper co-authored by Yong Suk Lee, Taekyun Kim, and Wonjoon Kim, Choi finds that firms need to be ready to make a significant investment in AI to see any gains, because limited AI adoption doesn’t contribute to revenue growth.
The study surveyed 160 startups and small businesses in South Korea about their use of AI technologies such as natural language processing, computer vision, and machine learning. Of the firms included, 54% had adopted AI to some degree. The correlation between AI adoption and revenue growth followed a J-curve: slow and steady at first, then substantial. The turning point was an intensity of AI adoption of 25%. For firms with AI intensity below 25%, annual revenue growth was essentially zero; for firms above the 25% threshold, growth approached 24%.
The researchers found that it takes time to see gains, and when firms increase their intensity of AI adoption to at least 25%, do growth rates pick up, and investments in AI start to pay off. “There’s a disruptive power for AI. With lower utilization, it’s harder to make a profit,” Choi said. “When you’re in those early stages of AI adoption, you may need some time to obtain the payoff to using AI.”
Here are three things companies should know about investing in AI:
1. It takes time to see gains
The survey results suggest that it takes time to see gains from AI investments, particularly for startups and early-stage companies. For firms with an AI intensity below 25%, annual revenue growth was essentially zero. In contrast, companies with an AI intensity above 25% saw growth rates approaching 24%. Thus, businesses must be patient when investing in AI and allow themselves time to obtain the benefits.
2. Invest in complementary technology
According to the study, firms must be ready to make a significant investment in AI to see any gains. But, it is also essential to invest in complementary technology to achieve optimal results. AI should complement a company’s existing infrastructure, and firms should look for ways to integrate AI into their overall business strategy.
3. AI is more directly relevant to startups’ products and services
As AI utilization is tied to startups’ products and services, businesses must align their AI investments with their overall business strategy. Startups must identify areas where AI can add value, and they should focus on creating AI-powered products and services that meet their customers’ needs.
In conclusion, businesses must be ready to make a significant investment in AI to see any gains, particularly for startups and early-stage companies. With a patient approach, complementary technology investments, and strategic alignment, AI can provide disruptive power to businesses and help them achieve revenue growth.
The Role of Complementary Technology in Driving Growth from AI Investments
A new study has found that several factors can influence a firm’s adoption of AI, including the size of the firm, the CEO’s prior entrepreneurial experience, and adoption of complementary technology, such as big data capabilities and cloud computing. Companies that adopt complementary technology are more likely to drive growth from their investments in AI.
Smaller firms and firms founded by CEOs with prior entrepreneurial experience are more likely to adopt AI intensively. In contrast, larger firms or spinoffs from other companies are less likely to adopt AI at that level, although lab-based spinoffs are an exception.
Investing in complementary technology is one of the most influential factors that contribute to better AI outcomes. Big data capabilities contribute to better AI outcomes through more mature data collection and management, while cloud computing provides the computational power necessary to run complex analyses. Both of these technologies help firms drive growth from their investments in AI.
According to Sukwoong Choi, one of the co-authors of the paper, investing in complementary technology drives the adoption of new technology such as AI. To adopt and utilize AI effectively and obtain the payoff at earlier stages of investment, firms need both the technology and the skills that go with it.
The pivotal role of complementary technology emphasizes the need for smart investment to support AI adoption. To accelerate AI adoption, firms must have access to the technology and the infrastructure that supports it.
The study also suggests that a company’s research and development strategy plays a crucial role in its adoption and utilization of AI. Internally focused R&D helps a company build “absorptive capacity” in AI know-how that positions it to more intensively adopt and use AI technology. This is helpful for firms that need to protect their proprietary algorithms as intellectual property or for firms working with sensitive data sets they’d rather not allow a third party to process.
However, if AI is a complement to a company’s core work and is not the focus of that work, firms can turn to external resources. Large language models, such as OpenAI’s ChatGPT, are a good example of this. They’re readily available, widely used, and constantly being refined.
In conclusion, firms must invest in complementary technology to drive growth from their investments in AI. The role of complementary technology is pivotal in driving AI adoption, and companies that adopt it are more likely to see better AI outcomes. The study suggests that firms need both the technology and the skills that go with it to utilize AI effectively and obtain the payoff at earlier stages of investment.
Considering Point Solutions for AI Work
Sukwoong Choi suggests that it’s important to consider point solutions for the AI work a firm is trying to do. If a firm’s area of work is more systematic, then an internally focused R&D strategy may not be necessary, and the firm can license something that’s already available.
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