Across nearly every industry, companies are racing to put AI into their products, and a striking number of those efforts stall after the first impressive demo. Technology leader John Campbell Crighton has seen the pattern closely enough to explain it. Over more than 20 years leading software development, DevOps, and product across healthcare, finance, and energy, most recently overseeing an electronic medical records and revenue cycle platform serving more than 100,000 users, he has come to treat AI as a multiplier rather than a novelty.
A multiplier magnifies whatever it is applied to. Point it at a real problem on a solid foundation and only then will it build value. “The biggest wins come when AI removes real friction for real people,” he says. The reason so many AI efforts collapse after the demo is that the exciting part was never the hard part. The durable work lies underneath it.
Point AI at Real Friction, Not Novelty
AI multiplies whatever it touches, and so the first decision is what to aim it at. The biggest wins come from removing the daily tasks that drain the people using a product, not from adding an impressive capability no one asked for. When Crighton’s team built AI-driven tools into their EMR platform, they cut down clinician reporting workflows and saved customers thousands of hours. That is the multiplier working as intended, aimed at a recurring drain on real users and giving that time back. The value was never in the sophistication of the AI. It was in the size of the friction it removed.
Build the Foundation Before You Scale the Ambition
A multiplier is only as good as what it runs on, which is why Crighton insists that the infrastructure come before the ambition. Innovation sticks only when the foundation can carry it, and AI layered onto an unstable platform simply multiplies the instability, which is exactly how a promising feature becomes the thing that breaks production.
The work here is deliberately unexciting. Crighton’s team migrated to Amazon Web Services, established a consistent monthly release cycle, and put quality assurance automation in place to raise testing coverage. None of that is the frontier, and all of it is what made the frontier possible. “That discipline is what led us to ship new modules like customer relationship management, scheduling, and billing with confidence,” he says, and it lifted customer satisfaction along the way. Ambition outruns infrastructure at a company’s peril. The exciting capability a team wants to ship is only as durable as the boring foundation it ships on.
The Team Is What Sustains the Momentum
The final foundation is human, and it is often easily overlooked. Great technology is built by great teams, Crighton says, and a multiplier applied by a team that keeps turning over never builds, because the momentum resets every time knowledge walks out the door. Having recruited, onboarded, and trained over 100 technology professionals, his organization held a 98% retention rate. Keeping the best people is what keeps the momentum, letting each advance build on the last rather than starting over.
Sustainable AI innovation is mostly foundation, real workflows worth solving, infrastructure that can carry the ambition, and a team stable enough to keep building. The AI is the multiplier on top, and the companies that chase it without the foundation get a demo, while the ones that invest in the foundation get a business. To learn more about building AI-driven innovation that lasts, connect with John Campbell Crighton on LinkedIn.
