WorkJam Adds Autonomous AI Layer to Its Frontline Operations Platform

New capabilities deliver closed-loop execution that prioritizes work in real time at each store, learns from outcomes at every level of the organization, and continuously compounds performance improvement across locations

MONTREAL, July 13, 2026 /PRNewswire/ -- WorkJam, the complete AI frontline operations platform used by leading retailers including TJX, Ulta Beauty, Marks & Spencer and Shell, today announced new autonomous AI capabilities that add a powerful intelligent layer on top of its existing unified platform.

WorkJam already provides deep, integrated capabilities across task management, communications, learning, shift management, and AI powered workforce orchestration. The new autonomous AI capabilities extend this foundation by closing the loop between enterprise systems and frontline execution. Instead of stopping at insights or recommendations, the AI autonomously assigns the right task to the right person on the right shift, continuously prioritizes and reprioritizes work in real time as conditions change, confirms completion, and learns from every outcome so the next decision is better.

"Most frontline AI tools deliver better visibility or recommendations for managers to act on," said Steven Kramer, CEO of WorkJam. "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."

The system learns at every level of the retail organization at once. Each store learns from its own results and conditions. Each district learns from the patterns across its stores. Each region learns from its own dynamics. And the entire fleet learns from everything happening across all locations. This means the work any single store sees is shaped by its own reality and sharpened by everything the system has learned at every level above it. The improvement compounds over time rather than plateauing.

Prioritization that fits each location and keeps improving

WorkJam reads the conditions at each location and prioritizes and reprioritizes the work around the clock as conditions change. Because the system learns at every level, the prioritization gets smarter over time — not just for one store, but across the entire organization. Each location's team knows what matters most on its floor at any moment. The system learns on two levels at once: what it knows about each location and what that location's own results teach it, alongside what's working across the whole fleet. The work each location sees is shaped by its own unique conditions and sharpened by everything the system has learned elsewhere. The improvement is continuous, adjusting in real time and compounding as the system learns.

Because these capabilities sit on top of WorkJam's existing communications, task management, learning, and staffing modules, organizations get more than isolated AI recommendations. They get autonomous execution that is already deeply integrated with how work actually happens on the floor — from work assignment and proof of completion to training reinforcement, capacity planning, and real-time communication.

WorkJam is built to be extensible by a retailer's own IT teams. They can plug in their existing intelligence and decisioning systems, create custom widgets that surface enterprise data to the right employees without duplicating it, and build their own AI workflows directly on the platform. For those that don't have these AI Models, WorkJam can be the full solution.

Autonomy that respects the realities of frontline work

WorkJam's AI operates inside hard operational constraints: shift schedules, compensable time, certifications, labor rules, and each organization's own policies and SOPs. Every autonomous decision is governed by those rules, can be overridden by a manager at any time, and is fully logged for audit and compliance. No data is duplicated between systems, so every action reflects current conditions in real time.

Available now, with major advancement in H2 2026

These autonomous AI capabilities are in market today. The WorkJam AI Task Priority Engine, arriving in the second half of 2026, extends them by running the loop autonomously in real time. It reads signals across labor, traffic, demand, customer feedback, and the outputs of an organization's own enterprise AI, then produces a dynamic priority score for every task that recalculates continuously as conditions change. Every recommendation includes a plain-language explanation so managers can trust it, audit it, and step in when they choose.

WorkJam's long-term vision continues to evolve towards a comprehensive intelligent operations platform that seamlessly orchestrates frontline operations from inception to completion. This platform is designed to establish an autonomous execution system — enabling a truly connected store.

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

About WorkJam

WorkJam is the complete AI frontline operations platform, the execution layer between enterprise systems and the frontline. It connects the employees who run the operation to each other, to headquarters, and to the systems the business depends on. On a single platform, WorkJam unifies targeted communications, task management and audits, learning, shift management, and employee self-service. Its AI works inside those workflows: it decides what needs to happen, triggers the right response across the platform, targets it to the right person on the right shift, and verifies it gets done. Every outcome feeds the next decision, and the learning compounds at every level. Over 1.5 million employees at some of the world's most demanding brands rely on WorkJam to drive productivity, strengthen employee retention, and run more consistent operations at scale. Learn more at workjam.com.

Media Contact

WorkJam: Adam Hatch, [email protected], 617.359.9946

SOURCE WorkJam