From reactive to proactive: How Agentic AI is redefining the frontline workforce

While AI innovation has swept through white-collar environments, from marketing to finance and on to software development, the vast majority of the world's workforce, those on the frontline, have remained on the sidelines of this transformation. However, that's changing fast thanks to the rise of a new class of artificial intelligence: agentic AI.

Unlike traditional AI, which passively responds to user prompts or queries, agentic AI is autonomous, contextual, and action-oriented. It doesn't wait to be asked - it detects, decides, and initiates action. For frontline-focused industries like retail, hospitality, logistics, and healthcare, this can really be a game-changer.

What is Agentic AI?

Most AI in the workplace today is what we might call "Stage 1": tools that retrieve information, answer questions, or generate content. These tools are helpful but reactive - still requiring a human to interpret the output and take the next step.

Agentic AI, by contrast, operates at a more advanced level. It understands context, sets goals, takes initiative, and executes multi-step tasks across systems - often without needing continuous human guidance. Instead of merely suggesting an action, agentic AI can launch workflows, notify the right stakeholders, monitor outcomes, and adapt based on feedback. For time-strapped frontline teams and managers, this kind of autonomous support isn't just helpful - it's game-changing.

Why the frontline has been left behind

Despite making up more than 80 percent of the global workforce, frontline employees have historically been under-served by enterprise technology. They've contended with disconnected systems, paper-based processes, and manual interventions, while their desk-based counterparts gained access to modern platforms and productivity tools.

One reason for the lag is that enterprise AI has primarily focused on knowledge work. There's been less emphasis on operational environments where workers are mobile, deskless, and often working in shifts. Another reason is infrastructure - many organisations simply lack the integrated systems needed to enable intelligent automation at the edge of the enterprise.

But that's starting to change.

Real-world frontline use cases

Agentic AI is already beginning to deliver real-world value on the frontline. Take training and compliance, for example. When a task is performed incorrectly or missed repeatedly, such as a store failing an operational audit - the AI can automatically assign targeted training or initiate a follow-up workflow. There's no need for a manager to spot the issue or manually intervene.

This is only possible when systems like task management, learning, communication, and workforce management are unified, allowing AI to detect patterns, determine appropriate responses and initiate action. With these connections in place, agentic AI becomes more than a smart tool - it becomes an intelligent orchestrator of work.

Other emerging examples include automated shift rescheduling when employees call in sick, predictive inventory checks based on real-time sales data, or compliance alerts that escalate without manual input. These capabilities are not just about saving time, they're about building resilience and consistency into frontline operations.

Overcoming the barriers

So then - what's holding companies back from adopting agentic AI more broadly? Often, the issue is not the technology itself, but organisational mindset and system architecture. Many leaders still view AI as a tool for back-office automation, rather than frontline enablement. As mentioned earlier, many others lack the integrated infrastructure needed to support end-to-end workflows.

To move forward, businesses must first identify friction points in their frontline experience, whether it's inconsistent communication, slow training delivery or inefficient scheduling. Then, they need AI solutions that integrate into existing tools and workflows rather than adding new silos.

Importantly, companies must also ensure trust and adoption from their workforce. That means implementing AI tools that are intuitive, transparent, and with a very clear value proposition. When AI is embedded in the flow of work – doing tasks such as surfacing helpful prompts, taking repetitive tasks off employees' plates, and supporting real-time decisions – then broader adoption and engagement follows naturally.

The path to autonomy

Looking ahead, agentic AI promises to unlock a fully adaptive frontline ecosystem. Imagine an environment where AI agents coordinate staffing, inventory, and customer service in real time without waiting for manual input. Training modules deploy automatically based on performance gaps, workflows adjust dynamically to changes in demand such as Christmas retail and Mothers' Day, and the increasing array of compliance requirements are automatically adhered to.

This is the direction in which forward-looking organisations are heading. Not toward AI that replaces people, but toward AI that empowers them by removing friction, closing loops, and enabling staff to focus on higher-value, human-centered work.

The frontline is finally entering the age of intelligent automation. With agentic AI, enterprises have an opportunity to rethink how frontline work is managed, measured, and scaled, moving from fragmented systems and reactive processes to connected, proactive operations that are as smart as they are seamless.