Laura Wilt has a simple test for every AI initiative at Sutter Health: Does it make work easier, or does it improve care? If the answer is no, it shouldn’t be built.
As chief digital officer of the Sacramento-based integrated health system, Ms. Wilt has spent the past few years embedding that philosophy into one of the most ambitious digital transformations in healthcare. The results are tangible: ambient documentation tools have yielded a 78% job satisfaction improvement among clinicians, an AI-powered lung cancer detection workflow has pushed early-stage diagnoses to nearly 70% of cases systemwide, and more than 10,000 users engage monthly with Sutter IQ, the system’s internal enterprise AI platform.
None of it happened because of technology alone.
“Our approach really starts with patients first and people always,” she said. “Bringing together people and working together is how we can transform — it can’t just be a digital effort. Digital can absolutely be a catalyst, and bringing an innovative approach to that helps accelerate change, but it really takes that broad, cross-functional collaboration to make transformation stick.”
To that end, Sutter has intentionally embedded physician, nursing and pharmacy informatics directly into its digital team, and leadership convenes regularly to align on priorities and review outcomes. That structure, Ms. Wilt said, keeps new tools grounded in clinical reality rather than drifting toward technology for technology’s sake.
Building a System That Surfaces — and Scales — the Right Ideas
Sutter’s approach to identifying AI investments runs on two tracks simultaneously: top-down prioritization based on feasibility and impact, and bottom-up recognition of innovations from frontline staff who are closest to the work. Once ideas surface, an impact analysis examining outcomes, workflow efficiency and adoption determines what gets scaled.
The tools generating the most traction share a common trait.
“What we’ve seen more broadly is that the initiatives making the biggest difference are the ones most deeply embedded into everyday workflows,” Ms. Wilt said.
How Sutter Health is turning AI into a people-first transformation engine
Laura Wilt has a simple test for every AI initiative at Sutter Health: Does it make work easier, or does it improve care? If the answer is no, it shouldn’t be built.
As chief digital officer of the Sacramento-based integrated health system, Ms. Wilt has spent the past few years embedding that philosophy into one of the most ambitious digital transformations in healthcare. The results are tangible: ambient documentation tools have yielded a 78% job satisfaction improvement among clinicians, an AI-powered lung cancer detection workflow has pushed early-stage diagnoses to nearly 70% of cases systemwide, and more than 10,000 users engage monthly with Sutter IQ, the system’s internal enterprise AI platform.
None of it happened because of technology alone.
“Our approach really starts with patients first and people always,” she said. “Bringing together people and working together is how we can transform — it can’t just be a digital effort. Digital can absolutely be a catalyst, and bringing an innovative approach to that helps accelerate change, but it really takes that broad, cross-functional collaboration to make transformation stick.”
To that end, Sutter has intentionally embedded physician, nursing and pharmacy informatics directly into its digital team, and leadership convenes regularly to align on priorities and review outcomes. That structure, Ms. Wilt said, keeps new tools grounded in clinical reality rather than drifting toward technology for technology’s sake.
Building a System That Surfaces — and Scales — the Right Ideas
Sutter’s approach to identifying AI investments runs on two tracks simultaneously: top-down prioritization based on feasibility and impact, and bottom-up recognition of innovations from frontline staff who are closest to the work. Once ideas surface, an impact analysis examining outcomes, workflow efficiency and adoption determines what gets scaled.
The tools generating the most traction share a common trait.
“What we’ve seen more broadly is that the initiatives making the biggest difference are the ones most deeply embedded into everyday workflows,” Ms. Wilt said.
AI-driven chart summarization inside the EHR, ambient documentation and AI-assisted In Basket responses have all seen strong adoption precisely because they meet clinicians where they already work, rather than asking them to build new habits around a separate platform. There are now more than 10,000 monthly active users in Sutter IQ, the system’s internal enterprise version of Microsoft Co-pilot chat.
“That level of engagement tells us AI is becoming part of everyday work, not something separate,” said Ms. Wilt.
Not every initiative has gone as planned, and Ms. Wilt doesn’t shy away from that.
“We’ve had situations where an AI tool performed well in one area, but we had to pivot when we realized there wasn’t enough workflow consistency to apply it reliably at scale,” she said. “In those cases, we’ve paused and rethought our evaluation process — making sure we assess workflow readiness earlier and build in more structured feedback. Those pivots are part of learning how to scale AI effectively.”
Speed Is a Feature — So Is Knowing When to Slow Down
Consumer AI adoption has moved faster than most health systems anticipated, and Sutter has responded by moving quickly on safety and privacy conversations, establishing those guardrails before deploying tools broadly. For higher-stakes use cases, decisions flow through an AI governance team spanning ethics and compliance, legal and risk, informatics and AI.
A recent example: testing AI-based cognitive behavioral therapy for mild depression and anxiety.
“We iterated several times with the AI governance team, including focused testing and report-outs by physicians, before making broader decisions about next steps,” Ms. Wilt said. “Ultimately, it’s about balancing speed with responsibility.”
It’s a balance central to Sutter’s broader AI culture — one where the question “how might we make this work easier?” drives adoption more reliably than any mandate from above. Looking ahead, she believes healthcare is only beginning to realize what’s possible, but only if the field keeps its focus on what actually matters.
“What excites me most is how AI can be an enabler to really drive healthcare transformation,” she said. “But to do this it will have to be people-driven. If we keep that focus, AI becomes a true enabler of transformation rather than just another layer of technology.”
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