AI tools have democratized software development, with nearly half of users who 'vibe code' coming from executive, product, operations, and sales roles. Coding is no longer an exclusive engineering function but a universal skill for problem-solving across the entire business.

Even within the code-centric Claude Code environment, nearly 50% of agentic tasks are for business functions like back-office automation, sales, and marketing. This is a strong leading indicator that agentic AI is rapidly expanding beyond its initial software development niche.

GitHub's user base is expanding beyond professional developers. Non-technical staff in departments like legal and finance are now using tools like GitHub Copilot to build small applications and assets, effectively broadening the definition of a "developer" in the enterprise.

AI adoption is forcing corporate legal teams to become more technical, leading to the expansion of "legal ops" roles. Companies now hire engineers directly onto their legal teams to manage systems, processes, and AI tool integrations—a significant shift from traditional legal department structures.

With AI coding assistants, the barriers to shipping software are eroding. At Ramp, designers and customer support agents are now shipping code to production. This suggests a future where the traditional, siloed Engineering, Product, and Design (EPD) team structure becomes obsolete.

Contrary to belief, OpenAI data shows non-technical roles are the fastest-growing adopters of advanced AI. In five months, legal department usage of 'Codex' exploded 108x and sales grew 41x. This vastly outpaces the 5x growth among engineers, signaling a major shift in where AI value is being created.

Inside a company, AI adoption isn't uniform. Engineers embrace it for tools, and Sales adopts it because its ROI is easily measured. However, General & Administrative functions like Finance and Legal are slower to adopt due to data infrastructure hurdles and the models' current weakness with numerical reasoning.

At Block, the most surprising impact of AI hasn't been on engineers, but on non-technical staff. Teams like enterprise risk management now use AI agents to build their own software tools, compressing weeks of work into hours and bypassing the need to wait for internal engineering teams.

Anthropic has seen a proliferation of personalized work apps created by employees in roles like sales. Tools like Claude Code lower the barrier to building software, allowing teams to create tailored solutions for repetitive tasks instead of using generic tools.