Retool’s AI in Production Survey Shows Collective Business Transformation Yet to Materialize

Retool, the leading platform for internal software development,released the findings from its second State of AI in Production survey. Retool is used by thousands of companies from Fortune 10s to growth-stage startups to build customized internal applications that solve business-critical problems. In September 2023, Retool launched Retool AI, which enables developers to design, develop, and deploy AI-powered applications and workflows quickly in a single platform.

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“AI has transformative potential—but the hype around it often overshadows the necessary hard work of identifying and building viable use cases. Similarly, fear mongering around whether AI will replace jobs can prevent companies from using it to unlock productivity and build high-quality software”

Sociologists have dubbed this decade the “age of AI,” and an estimated 55% of Americans are “regularly” using it. Yet, in polling 730 technology workers, Retool found that while AI is bearing significant ROI for individuals (with 85.5% of respondents that use AI tools saying it positively impacted productivity), businesses as a whole haven’t quite found their footing when it comes to leveraging AI collectively. The data also revealed higher expectations for AI’s utility in internal—versus external—use cases, and mixed feelings on whether AI will replace workers.

“AI has transformative potential—but the hype around it often overshadows the necessary hard work of identifying and building viable use cases. Similarly, fear mongering around whether AI will replace jobs can prevent companies from using it to unlock productivity and build high-quality software,” said David Hsu, CEO and founder of Retool. “There is a lot of excitement around AI, but actually applying it in your business—and driving business value out of it—is not simple. Developers are the key here—wrangling AI to be consistent, reliable, and requires core software engineering concepts (e.g. testing, observability, etc.). And we need to move far beyond the chat UI, which is fully reactive and difficult to derive value from. Enterprises will need to invest in software engineering talent and custom software in order to stay competitive and leverage the transformative potential of AI.”

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In fact, while public narratives speculate about the impact on jobs, in practice, some respondents say the real risks are not between humans and the machine (AI, in this case), but between those that use the machine and those that do not, both humans and businesses. For business leaders, this could mean that broader company-wide AI initiatives will become a competitive advantage versus a catalyst for employee fear of replacement. As the economy continues to digest the impact of a non-ZIRP reality, businesses are more conscious than ever of bottom line, creating opportunities for those who are able to deploy AI to drive significant operational efficiencies.

Still respondents, who include software developers, business and engineering leaders, executives, product managers, designers, and more, did allow some job risk. 45.7% of respondents suggested entry-level ICs were most at risk of replacement by AI. (This underscores findings from our 2023 report: C-suite and VPs had the biggest expectation of AI changing—not necessarily replacing—their roles; a year on, many seem to view it as a tool rather than a threat.)

The survey also found that daily use of AI increases exactly linearly with seniority: C-suite respondents were the biggest daily users of AI at ~72%, begging the question of how leadership can lead by example when it comes to AI adoption.

Additional findings of the survey include:

• This year’s survey saw a decrease in those secretly using AI at work. More than a quarter (27.3%) of respondents using AI at work are doing so in secret, down from last year’s 34.4%.
• Almost three-quarters of respondents use copilots and other AI tools (e.g. ChatGPT, Claude, etc.) in their work at least every week, with 56.4% nearing daily use. Product and Engineering are leading daily adoption at 68% and 62.6% respectively.
• When asked what respondents would change in their AI stack, 41.2% of respondents said they would change something in the pipes (e.g., the tools/frameworks used for data transformation and chaining).
• Respondents shared that their companies are deploying different approaches to AI hardware and resource allocation. A minority of those surveyed own or operate GPUs themselves (13.2%), with the rest split between renting from major cloud providers (38.9%) and emerging providers (15.8%).
• A slight majority of respondents (53.7%) say operating costs of GPUs (rented or owned) are worth the investment.
• Only 8.5% of respondents reported seeing more promise for AI in external use cases, versus 57.9% equal promise for both internal and external, and 33.7% more promise for internal.
• Despite the prevailing narratives suggesting AI is taking over the world, 61.7% of respondents said they are only in early innings with their AI internal use cases.
• The proliferation of the chatbot is well-established, with over half of respondents (55.1%) saying they have either built an AI-powered chatbot or their company has. Fully 80% of respondents said they expect chatbots to remain useful for at least a few years, but their permeance may fade as other use cases become more prominent. (And some respondents reported feeling “fatigue” over their ubiquity.)

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