# The DIY Software Movement: How AI Is Letting Companies Build Their Own Enterprise Tools
A growing number of companies—from small businesses to large enterprises—are embracing a do-it-yourself approach to software development, using generative AI to build internal tools they would otherwise purchase from major vendors like Workday, SAP, and Salesforce. Chicago-based consultancy West Monroe, for example, needed a program to check payroll for errors and another to surface insights about its roughly 2,000 employees for managers. Buying those capabilities from a vendor would have cost more than $300,000 a year, according to chief people officer Tanya Moore. Instead, employees built the software themselves earlier this year using OpenAI’s ChatGPT and Codex. What was once a binary choice—buy from a vendor or keep doing the work manually—has been transformed by generative AI into a third option: build it in-house.
## AI-Powered Internal Tools Across Departments
Companies are applying this DIY strategy across HR, sales, finance, and other business functions. Spotify employees built „HR Bot,” a personalized HR help desk that draws from the company’s regularly updated employee handbook to answer questions about remaining vacation days, parental leave policies by country, and other routine workplace matters. According to chief HR officer Anna Lundström, the tool—which debuted in November 2025—is widely used by staff and has freed up her team to focus on other tasks; without AI, Spotify might have sought external support to build it. Similarly, communication software provider Twilio built an internal AI tool called Jarvis for its salespeople that listens to sales calls, analyzes rep performance, and serves as a personalized coach. A spokesman said Jarvis has achieved about 80% adoption across sales teams and reduced the sales-deal lifecycle by 54% for users compared with non-users. Twilio CEO Khozema Shipchandler told Business Insider that if a tool like Jarvis already exists or comes to market, Twilio „probably won’t use it, because we’ve already built our own.”
## A Growing Threat to Vendor Revenue
The trend is significant enough that analysts are taking notice. According to a recent McKinsey survey of 1,719 executives and managers, about a third of organizations decided against buying at least one software product or feature because they could build it using AI tools. While most companies aren’t replacing entire enterprise software platforms with in-house alternatives, the strategy could dent the incremental revenue vendors earn from selling add-on features. The trend „is going to erode a bit of the walled garden,” said HR-tech industry analyst Kyle Lagunas, noting that HR teams „can self-serve a lot more.” Omega Venture Partners, a Silicon Valley technology investment firm, put the threat more starkly in an August report: „The vendor’s most dangerous competitor may now be the customer.” The movement is particularly notable given that investors erased hundreds of billions of dollars from software companies’ market values earlier this year over fears that AI could make building software cheaper than buying it—though Gartner still forecasts worldwide IT software spending to grow nearly 16% this year, reaching $1.47 trillion.
## Risks and Limitations of the DIY Approach
Despite the potential savings, maintaining homemade software comes with real challenges. Someone must fix bugs, roll out updates, respond to feature requests, and ensure tools keep working as more employees rely on them. There’s also the risk that AI-powered tools will make costly mistakes, such as leaking staffers’ private information. „If an agent skips a compliance step or approves pay outside your grid, you’re not dealing with a minor hallucination,” wrote Workday CTO Gabe Monroy in a June blog post. „You’re dealing with an audit, a regulator, or a lawsuit.” Enterprise vendors also bring years of experience building HR software and vast amounts of collected data—advantages SAP CEO Christian Klein argued at a recent Goldman Sachs conference that large language models alone can’t replace. West Monroe’s Moore said her firm’s eight in-house tools each underwent months of testing before launch and are reviewed every few months, but she acknowledged that other businesses may lack the expertise or appetite for the same path: „There’s a lot riding on that accuracy.”
## The Savings Can Be Substantial
For some companies, the potential for massive savings justifies the challenge. Gray, a design, engineering, and construction firm in Lexington, Kentucky, with about 2,300 employees, expects to avoid spending $1 million on vendor and consulting fees by building a financial forecasting tool in-house starting later this year with Microsoft’s Copilot and Anthropic’s Claude. That figure reflects what Gray’s finance chief, Scott Parker, said the company already paid for a comparable piece of software a few years ago, which came with an additional $175,000 a year in service fees. „We’re realizing the power of AI,” Parker said. As generative AI tools mature and become more accessible, the DIY software movement appears poised to keep reshaping how companies think about building versus buying—and how enterprise vendors must respond to their newest competitor: their own customers.
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Forrás: https://www.businessinsider.com/spotify-twilio-using-ai-build-software-saaspocalypse-2026-9#article.