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Independent research reinforces this. MIT’s 2025 State of AI in Business report found that despite tens of billions in spend, only 5% of custom enterprise AI tools make it to production. Enterprises lead in pilot volume yet lag in scale. The findings point to approach, not model quality, as the real limiter. This article explores three platform-engineering principles that consistently turn AI from hype into working enterprise systems.

When building a platform, engineering leaders often focus on technology choices without first building a shared vision with developers, specialist teams and other stakeholders. This results in low adoption or, in the worst case, wasted investment. This article will provide a practical leadership framework for securing developer support before a single platform component is built.

Most internal platforms don’t fail on day one: they fail on day 2, 200, or 2000. What starts as a solid solution to today’s needs often turns into tomorrow’s bottleneck: brittle delivery processes, endless ticket queues, and systems so complex they collapse under their own weight. At Syntasso, we built Kratix to flip this pattern.

You know the saying, “If we build it, they will come”? Well, it doesn’t hold up when building software today, and it definitely doesn’t work for internal platforms. You see, internal platforms are products. And like any product, they (should) have users. In this case, your users are your developers. That makes platform engineering a form of consumer software development, even if the consumer is inside your organisation.