Experts across healthcare are all listing serious workforce challenges as one of the top issues facing the industry. Burnout, retirements, and a lack of skilled professionals are all contributing to staffing shortages. Frontline workers are feeling increasing levels of stress. Healthcare isn’t burning people out just because the work is hard. It’s burning them out because the work isn’t designed to be easy.
The US Department of Health and Human Services issued a report by the Surgeon General specifically targeting this important issue. The report identifies the need to help health workers prioritize quality time with patients and colleagues stating: “Inefficient work processes, burdensome documentation requirements, and limited autonomy can result in negative patient outcomes, a loss of meaning at work and health worker burnout.”
Every day, smart clinicians and staff waste time hunting for the “right” handoff, repeating data entry, or following rules like “that’s the way we’ve always done it”.
That slow drip of friction (process drift) adds up to delays, rework, and fatigue.
Demand continues to rise and staffing is thin; that friction becomes full-blown bottlenecks. Healthcare enterprises are working to make improvements; many have invested in Lean Six Sigma training for their staff. Unfortunately, today’s demands are not in line with traditional process improvement methodologies. It can take weeks to schedule process review meetings; weeks to read SOPs; and weeks to draft a process flow. Those weeks add up and must be eliminated for improvements to be impactful in healthcare.
AI technology changes the tempo; new AI tools designed specifically for process improvement are available. These tools reduce the time to create and illustrate a process, review it for improvement, and publish documentation such as an SOP and Job Aids. The power of AI technology is best seen when it eliminates mundane, time consuming, repetitive, and low valued activities.
There are innovative tools today that can create a process or build it from information that already exists. Just feed the application materials like policies, job aids, emails, instructions, procedures, even dictated notes and it can generate a process flow diagram instantly. Leaders and clinicians can look at the diagram and provide feedback. The same AI technology can be used to recommend improvements.
The instant creation of an as-is process models can cut project timelines significantly as AI does the heavy lifting and delivers the ability to move quickly to the improvement phase of a project.
Because healthcare has always been rich in policy and poor in shared understanding this tool could be a game changer.
In most cases, the knowledge exists, sometimes only in people’s heads but it’s easy for someone to create an outline. However, the content is presented, as documents or text entry, AI technology stitches it together into a visual representation of the process.
That flips the conversation from “What do we do?” to “Why do we do it that way?” These are the questions that actually lead to improvement.
Burnout often lives in the in-between. Things like extra clicks “because the system didn’t take it,” repeat phone calls to clarify a missing step, redundant fields nobody remembers why we keep. Having an end-to-end process map makes the invisible visible. Teams can separate good friction (the checks that prevent harm) from bad friction (steps that don’t add value). The result is clearer, safer workflows that are easier to train, staff, and sustain.
Where to start
Pick one process that staff identify as a pain point. It could be discharging instructions, perioperative readiness, referral intake, or denials management. Gather what already exists (SOPs, emails, notes). Generate the initial map and distribute it electronically to SMEs for review and comment. Use the information to make changes to the initial process model. In a one-hour session, validate it with the people who run the work and agree on three changes everyone can live with. Publish the updated model with owners clearly labeled. Set a two-week check-in to see if the change sticks. Then repeat.
Guardrails matter
Don’t boil the ocean. Velocity builds trust. Trust creates capacity. Capacity lets you tackle the next issues Also, protect privacy. Keep PHI out of AI tools. That information is not necessary for process creation.
What this is and isn’t
AI can draw a map. It cannot set your values. Leaders still choose the order of priorities such as safety first; patient experience next; throughput and cost right behind. They can still invest in change management, because the hardest part of improvement isn’t the diagram, but it is creating new habits and sticking to them.
The payoff
AI-powered process improvement won’t make the work easy. It makes the work easier to fix. It gives an organization a shared understanding in hours, not weeks and it helps separate good friction from bad. It will ultimately free up time for collaboration, innovation, and patient care.
In a time when staffing is tight and patient expectations are high, using AI to help with process improvements isn’t a tech win – it is a human one.
Frank Vega
Frank Vega is the founder and CEO of The Efficiency Group, a process-improvement firm using Gen AI to create BPMN models in minutes. Under his leadership, TEG has supported organizations across healthcare, government, supply chain, finance, and manufacturing, including initiatives with the National Institutes of Health, the Department of Energy, the Department of Defense, and General Dynamics IT. Frank’s work centers on making Lean Six Sigma and continuous improvement accessible to non-experts, enabling faster kaizen cycles, cleaner documentation, and measurable gains in throughput, quality, and cost. He frequently speaks on the practical use of AI in process mapping and on building a culture of improvement that scales beyond specialist teams.
