WorkJam adds autonomous AI layer for frontline staff

WorkJam has added an autonomous AI layer to its frontline operations platform. The new functions are available now.

The update adds automated task assignment and reprioritisation to a platform already used for task management, communications, learning and shift management. The system assigns work to specific employees on specific shifts, confirms completion and uses the results to inform later decisions.

WorkJam sells its software to retailers and other employers with large frontline workforces. Its customers include TJX, Ulta Beauty, Marks & Spencer and Shell, and more than 1.5 million employees use the platform.

WorkJam is positioning the change as a move beyond AI tools that only provide alerts or recommendations to managers. The software sits between enterprise systems and shop-floor staff, and the new layer is designed to link those systems more directly to execution at store level.

According to WorkJam, the software learns from outcomes at several levels of an organisation. Each store learns from its own conditions and results, while districts, regions and the wider estate learn from patterns across multiple locations.

Store workflow

The system reads conditions at each location and changes priorities throughout the day as those conditions shift. The aim is to reflect local differences while also applying lessons from other sites in the same network.

The autonomous AI functions are integrated with WorkJam's existing communications, staffing, learning and task tools rather than operating as a separate recommendation engine. The platform also supports proof of completion, training reinforcement, capacity planning and real-time communication.

Another part of the offering is aimed at retailers that want to connect their own systems to the platform. Customer IT teams can integrate existing decision tools, create custom widgets to surface enterprise data to employees and build their own AI workflows on top of the software.

Operational limits

The system operates within operational constraints including shift schedules, compensable time, certifications, labour rules and internal policies. Managers can override any autonomous decision, and decisions are logged for audit and compliance purposes.

WorkJam also said the platform does not duplicate data between systems, with actions reflecting current conditions in real time. That is likely to matter for employers trying to avoid conflicts between workforce systems, store operations software and compliance rules.

Steven Kramer, Chief Executive Officer at WorkJam, set out the company's argument for the product shift.

"Most frontline AI tools deliver better visibility or recommendations for managers to act on. The real breakthrough comes when you combine a strong execution platform with autonomous intelligence that actually closes the loop. The right work gets done, the system learns from what happened at each store, and performance compounds across the chain. That's what we built," said Steven Kramer, Chief Executive Officer at WorkJam.

A further product development, called the WorkJam AI Task Priority Engine, is due in the second half of 2026. The tool is designed to run the decision loop autonomously in real time by reading signals across labour, traffic, demand, customer feedback and outputs from a customer's own enterprise AI systems.

Under that model, each task would receive a dynamic priority score that changes continuously as conditions change. Each recommendation would also include a plain-language explanation to allow managers to review and, if necessary, intervene.

The announcement reflects a broader push by software suppliers to embed AI more directly into day-to-day operations for frontline staff rather than limiting the technology to analytics dashboards. In retail, where staffing levels, compliance demands and store conditions can shift quickly, vendors are increasingly arguing that execution on the shop floor is the next battleground for AI adoption.

WorkJam said it was recently named a Leader in the Nucleus Research Task Management Technology Value Matrix 2026.