The hidden cost of build vs. buy for agentic AI in regulated industries
The article from The New Stack examines the build vs. buy dilemma for agentic AI in regulated industries like finance and healthcare. Building custom AI agents provides full control over data and compliance but demands substantial upfront investment in infrastructure, security, and ongoing maintenance. Buying off-the-shelf solutions offers faster deployment and lower initial costs but may lead to vendor lock-in, limited customization, and hidden fees for compliance features. The hidden costs include integration complexity, training, and potential regulatory penalties if the solution fails to meet specific industry standards. The article emphasizes that organizations must evaluate total cost of ownership, including long-term scalability and adaptability to evolving regulations.
Developers must weigh compliance and control against speed and cost when choosing AI solutions.