Market research firm Forrester earlier this week predicted that spending on off-the-shelf and custom AI software will reach $64 billion by 2025, doubling from $33 billion in 2021.
According to a blog post by Forrester analyst Michael O’Grady, three categories are driving AI software growth: AI maker tools (tools used to develop AI applications), AI-centric software (software that depends on AI to function), and AI-infused software (software equipped with AI capabilities). AI maker tools are expected to see an 18% annual growth rate, while AI-centric software will experience a 14% growth rate. AI-infused software, meanwhile, is poised to increase from 27% of AI software spend in 2021 to 31% by 2025.
The market's upward trajectory is fueled in part by two key trends: the acceleration in AI adoption during the COVID-19 pandemic and the proliferation of vendors that offer AI software. Forrester predicts that cybersecurity will be the most significant area of AI software growth between now and 2025, with a focus on real-time threat monitoring and automated response to attacks.
Forrester said the U.S. and China will capture 71% of total AI software spend in 2022, making the two countries the leading investors in AI software. Forty-seven percent of AI spend will come from the U.S. this year. “The U.S. leads AI enterprise adoption and is the leading destination for private AI investment, with $23.6 billion of funding in 2020,” the Forrester report states.
U.S. firms IBM and Microsoft make up the largest AI portfolios.
While the U.S. leads in AI enterprise adoption, China exceeds in research. In 2022, Chinese researchers published 63% more research. Chinese AI firms mostly operate in manufacturing. China boasts the world’s largest AI voice recognition startup, iFlytek, with 700 million users. In the finance sector, WeChat Pay accommodates 20 times more users than Apple Pay hosts in the U.S.
However, the impressive spending growth does not eliminate the very real complexities that come along with AI software development and adoption. Forrester emphasized that AI integration and success relies on a growing pool of talented labor, adherence to responsible AI practices, availability of infrastructure, evolution of business models, and the democratization of tools.
