A PwC study reveals the leading 20% of companies capture 75% of AI's economic gains. They focus on using AI to identify new growth opportunities and reinvent business models, rather than simply improving efficiency on existing tasks.
RAMP built its AI platform in-house because they view internal productivity as a competitive moat. Owning the tool allows them to move faster, deeply understand user pain points, and leverage internal learnings to inform their external customer-facing products.
RAMP discovered that the best way to teach employees AI is through the product itself. The most successful users learned by immediately using a feature and getting a result. This suggests designing AI tools where features act as implicit lessons, teaching best practices during use.
While AI can make individuals 10x more productive, this doesn't automatically create a 10x more valuable company. An 'institutional AI' layer is needed to coordinate efforts and align individual output toward shared business goals like scaling revenue.
RAMP found employees were stuck not because AI models were weak, but because the setup was too painful. They built an internal platform, "Glass," to provide a fully configured AI workspace from day one, proving the 'harness' is the key to enterprise-wide adoption.
RAMP's internal AI tool is built on the principle of not limiting user upside. Instead of simplifying the tool by removing features for non-technical users, they make advanced complexity invisible while preserving full capability, breaking from conventional software design wisdom.