symmplr launches AI time and scheduling to predict healthcare workforce needs – Unite.AI

A hospital staffing shortage often becomes more costly when there is little time left to resolve it. Managers fight for coverage, nurses respond to last-minute requests, and overtime or premium labor fills remaining holes. symplr is trying to get ahead of those decisions with the launch of symplr Time and Scheduling, an integrated workforce management solution that combines AI-based scheduling with timekeeping.

Announced on October 26, the product brings together projected staffing demand, available staffing across the healthcare system and labor costs into one shared view. Its new AI-powered workflows recommend schedule adjustments for managers to approve, taking into account staff preferences, scheduling rules, forecasted needs and historical patterns.

The launch connects symplr’s predictive scheduling capabilities with timekeeping technology designed around the complex compensation rules and compliance requirements of the healthcare industry. It also establishes the foundation for a broader workforce operations strategy that spans planning, people and analytics.

The AI ​​recommendations target the bottleneck of scheduling balance

Building a program is just the beginning of staffing a hospital. Managers must then reconcile employee preferences with coverage needs, fill gaps, and respond when the balance changes. A schedule that looks complete on a spreadsheet can still leave a unit short of the people it needs at a given time.

The new product’s AI-based scheduling balance is designed to reduce manual adjustment work. Instead of asking a manager to make every change from scratch, propose adjustments based on relevant constraints and staffing patterns. The manager remains the approver.

This is an important distinction in a context where a staffing decision impacts both employees and clinical operations. A recommendation can help a leader compare options more quickly, while leaving the responsibility to evaluate whether the proposed coverage is right for the unit.

“Nursing leaders shouldn’t have to spend hours building schedules and scrambling to fill open shifts when they could be supporting their teams and patients,” said Ali Morin, head of nursing informatics at symplr.

The company also emphasizes greater flexibility for nurses. The expected benefit is a schedule that takes staff preferences into account in advance, with fewer urgent requests and less administrative friction in finding suitable shifts.

How predictive staffing works underneath planning

Existing Smart Square technology provides the context for the launch. Its documentation describes a predictive model that combines proprietary mathematical modeling with machine learning. Forecasts are updated weekly and analyzed through staffing matrices for individual units or service areas to compare projected patient demand to staffing supply.

The current product page describes forecasts that extend up to 120 days ahead. The practical purpose is to highlight possible gaps while managers still have time to address them, rather than waiting for an uncovered shift to become an immediate operational problem.

Smart Square also includes open shift management using a variable incentive model, company-wide visibility into staff resources, self-scheduling, and links to human resources, payroll, timekeeping and electronic health records systems. These capabilities explain how a forecast can inform action: managers must see both the projected deficit and the workforce options available to solve it.

Demand forecasting and balancing a schedule are related but different tasks. The forecast estimates the coverage needed. Schedule balancing then works based on availability, preferences and rules to recommend how to meet that need. The timekeeping records what ultimately happened.

Linking planned coverage to time worked

Integrating scheduling and timekeeping addresses a second source of administrative work: the gap between a scheduled shift and the hours that hit the paycheck. When those tasks are in disconnected tools, managers must reconcile changes and time tables after the staffing decision has already been made.

symmplr Time and Scheduling brings the two functions together so nursing leaders can consider coverage and labor costs within the same workflow. The timekeeping component is designed to manage healthcare pay rules and compliance requirements, rather than treating each shift as a block of interchangeable hours.

symmplr points to previously reported results from its scheduling and timekeeping capabilities: approximately 50% less time spent on staff and timesheet tasks, with the potential to free up up to 75% of payroll team capacity. These are the potential benefits associated with the combined features reported by the company, not a new independent evaluation of the product launched today.

The distinction is important when evaluating pitching. The opportunity is to reduce the number of manual steps between anticipating a staffing requirement, covering a shift and reconciling hours worked. The outcomes for a particular health system will depend on its workflows, existing integrations, and implementation.

A manual process persists despite growing investments in artificial intelligence

The company’s Compass 2026 survey helps explain market needs. 41% of respondents said that staffing planning for doctors and nurses in their organizations remained completely manual. Another 35% described it as minimally automated, while only 4% reported full automation.

The survey, conducted with CHIME, included 146 respondents in clinical, IT and operational roles in U.S. hospitals and health systems. It was fielded from June 1 to July 17, 2026. Its results describe that group of respondents rather than a census of each hospital.

The same research found that 21% of respondents said their organization implemented AI without establishing metrics to evaluate it. This places measurement alongside automation as an implementation priority. For planning, relevant measures include time spent managing roster, unfilled shifts, overtime, staff satisfaction, and accuracy of demand forecasts.

Making a process more automated is only useful if the resulting program works for the people who need to provide care. Involving nursing leaders and front-line staff in implementation offers the health system a way to test whether recommendations address real sources of scheduling friction.

What’s available now and what’s next

The current launch focuses on integrated planning and timing, with AI recommendations when balancing planning. symplr plans additional AI capabilities for timecard fixes and scheduling rule configuration in 2027. Those features remain on the roadmap.

Its broader healthcare AI strategy includes predictive intelligence, intelligent self-programming and tools integrated into operational workflows. The company describes source traceability and managed data as a platform priority. This broader strategy should be distinct from the specific features available in Time & Schedule at launch.

Scott Sbihli, Chief Product Officer, said symplr plans go beyond traditional planning to connect planning, staffing and workforce analytics across inpatient and outpatient care, with deeper capabilities for physicians and other providers.

symmplr will present Time and Scheduling at the ANCC’s Magnet Conference in Chicago October 29-31, in booth 631. The immediate test will be whether a more connected view of demand, available staffing and time spent can give nursing leaders fewer last-minute problems to solve and more time to support their teams.