Survey Shows Nearly 25% of Tech Firms Use Generative AI for Software Development

San Francisco – Nearly one-in-four U.S. technology firms say they currently use generative AI tools to boost software development, with significant growth in adoption across major business functions predicted over the next year, according to a new survey of senior technology executives by global strategy consulting firm Altman Solon. 

Altman Solon surveyed 292 senior technology executives and interviewed a panel of industry experts to better understand opportunities for generative AI in businesses. The survey results point to strong demand for generative AI tools across business functions despite a limited number of off-the-shelf and customizable solutions.  

The survey identified software development as the top business function for generative AI adoption at 22%, followed by marketing (11%), customer service (8%), and product development (6%). When asked about future generative AI adoption, the expected adoption rates approach 80% or more in software development, marketing, and customer service, with a 62% expected adoption rate for product development. 

Generative AI Adoption and Likely Adoption Over Time

Click to expand

Generative AI Adoption and Likely Adoption Over Time

“There is clearly a strong demand for new generative AI tools that will grow exponentially over the next year,” said Altman Solon Partner Josh Zaretsky. “As the market matures, it will be important for AI providers to develop more easy-to-use and customizable solutions, which customers have come to expect from SaaS and other more established technology applications.” 

Among the companies surveyed, off-the-shelf solutions and custom apps built on an out-of-the-box model are tied as the most popular development models of generative AI tools, with 70% of respondents choosing one of these two options for current or intended generative AI development. Companies surveyed who used SaaS tools were two to three times more likely to prefer out-of-the-box solutions, suggesting a solid market in ready-made, enterprise-grade generative AI tools. 

“The survey clearly shows that respondents would prefer deploying generative AI in the public cloud or in their providers’ environment rather than build their own infrastructure,” said Altman Solon Partner Swope Fleming. “This could be a new growth driver for cloud providers as adoption ramps up.” 

The survey shows that most enterprises are interested in outsourcing generative AI app development and prefer deploying generative AI models on the public cloud of their choice. Nearly half (48%) said they were using generative AI in the cloud independent of their provider, compared to 32% who used the application providers’ environment. Only 20% of respondents say they are using their own private infrastructure.  

Current and Intended Development & Deployment of Generative AI

Click to expand

Current and Intended Development & Deployment of Generative AI

In making development and deployment decisions, organizations surveyed cited customization as the most important criterion (62%), followed by deployment cost (55%) and scalability (52%). Although security didn’t make the top three decision criteria, 24% of organizations surveyed listed security as most important. Respondents who chose security as their deciding factor were more likely than others to deploy with a private infrastructure, suggesting particular attention to security.  

In March 2023, Altman Solon analyzed emerging enterprise use cases in generative AI. Leaning on a panel of industry experts and a survey of 292 senior executives, Altman Solon analyzed preferences for developing and deploying enterprise-grade generative AI tools. The survey also looked in-depth at the key factors that go into developing and deploying generative AI tools. Respondents were from U.S.-based businesses of various sizes. Altman Solon has released two insights so far, on generative AI enterprise deployment and as a business transformation application. More insights will be released in the coming months.