AI-driven automation is now the norm in modern customer service. In fact, only 5% of contact centers surveyed by CMSWire in 2026 said they did not use AI at all.
With automation taking over many routine customer support tasks, human agents are receiving an ever-greater concentration of urgent, complex, critical, and emotionally demanding cases. Their traditional, pre-AI mix of consumer interactions – with simple routine everyday calls easing the strain of more intense situations – is lost. The agents effectively become something like a customer service “trauma unit” for escalations, with longer handle times, greater variance, and compounded cognitive strain.
If you treat AI-to-human hand-offs as generic leftover demand, you’re inevitably going to underestimate the toll on your frontline teams. That means inaccurate forecasts, unrealistic schedules, and constant scrambling to adjust intraday staffing in real time. The costs can be significant, including chronic agent burnout and attrition, systematic inefficiencies, and frustrated customers.
To prevent that, management of your complex hybrid ecosystem has to be geared toward fully integrated AI-human teams. Legacy assumptions about how work moves through your enterprise are no longer sufficient, and workforce management (WFM) must be rethought, from strategy to planning.
Adopting such an approach, with the appropriate WFM tools, has a multilayered payoff of reduced operating costs, increased agent retention, and higher CSAT scores.
We saw this at NiCE World 2026, when Lowe’s Companies, Inc. showcased their successful automation of over 434,000 schedule changes with NiCE AI-driven solutions and over $1 million in savings within eight months. Their traditional WFM just wasn’t built for the pace, complexity, or expectations of their evolving workforce. With NiCE, their system became more autonomous, enabling greater operational consistency and intelligent flexibility.
Similarly, when a sustained wave of unplanned demand swings made every forecast a moving target, TD Bank turned to NiCE for a solution. The bank shared their impressive successes at NiCE World 2026 as well, explaining that AI-driven forecasting and scheduling helped them make faster, smarter decisions every day (e.g., capacity flexed dynamically by 6%-8% thanks to key AI recommendations). As a result, they were able to save $18 million, exceed service level goals, and achieve record high CSAT scores.
Both TD Bank and Lowe's are planning to take the next step: eliminating the manual steps between insight and action for faster real-time intraday adjustments, more preemptive decisions, and less time spent on administration. They'll get there with NiCE Copilot for Workforce Managers — AI decision support embedded in the tools managers already use — which handles routine tasks and escalation decisions and assists with more sophisticated requests.
The evolution is already underway. According to the 2026 WFM Trends for Contact Center Leadership survey of 400 North American and EMEA contact center leaders, 83% have adjusted their staffing or forecasting assumptions due to AI-provided insights. And the savings they’re realizing are being reinvested in quality, flexibility, and coaching rather than headcount reduction.
Once you've made that shift in thinking, the next step is mastering the delicate art of orchestrating a blended workforce day to day.
You have one workforce, not two
In a hybrid contact center, human and digital agents function as one workforce — with two distinct types of workers inside it.
AI agents can take over intent-rich, routine tasks at machine speed, efficiently handling things like password resets, order updates, and basic account tweaks. This frees human agents for interactions requiring empathy, creative negotiation, or critical judgment.
However, if you rapidly scale capacity with AI but lump bot-handled volume together with more complex human escalations, both agent burnout and containment failure are only a matter of time. And if you accelerate automation without intelligent forecasting, then you’ll soon encounter friction, disjointed customer journeys, and operational blind spots.
You’ve got to systematically adapt your overarching workforce management strategy to deliver dynamic, strategic, and comprehensive orchestration. AI containment, deflection rates, and escalation patterns must be balanced with human cognitive load, scheduling preferences, and training needs. And all that needs to be aligned with business-level regulatory constraints and service level expectations. It is a complex, challenging, and comprehensive configuration task that more and more WFM professionals are being called upon to perform to ensure sustainable effectiveness.
Best practices for hybrid WFM
These challenges aren’t hypothetical. In a recent NiCE-sponsored AMA with the r/workforcemanagement community on Reddit, practitioners raised questions about forecasting in low-volume and volatile environments, reflecting the complexity WFM teams are navigating today.
Summarizing the exchange, Mark Gill, Solutions Engineer at NiCE, noted that “WFM is evolving rapidly to deal with the changing landscape that AI brings. …The fundamentals still matter, but the tools and strategies we have available today are making it easier to balance customer experience, employee experience, and operational efficiency.”
We’ve developed a series of best practices you can easily and immediately implement to achieve that balance with NiCE Workforce Management. They address issues such as recognizing the distinct characteristics of each type of interaction; avoiding the assignment of work to human agents that AI agents should handle; ensuring readiness for peak complexity spikes; staffing for variance instead of averages; and handling bot degradation and token budgets.
Those best practices, detailed in “The Dawn of Hybrid Workforce Management: A WFM Leader’s Guide,” are the basis for a resilient, integrated hybrid contact center. Building upon that foundation, new autonomous, agentic operating models are about to take AI-human workforce management to a whole new level.
Evolution of the WFM platform
The hybrid workforce is one primary catalyst of change in today’s contact centers. Another is the evolution of the WFM platform itself. It’s evolving from a passive set of tools into an agentic engine capable of forecasting, scheduling, analyzing, and even intervening with minimal human involvement.
As that process accelerates, and more multistep tasks can be safely handed off to AI, your WFM team will focus on strategy – setting objectives, defining guardrails, reviewing auto-generated recommendations, and owning outcomes. It’s a conceptual shift from managed operations to governed autonomy.
But before all that happens, you’ll need to address concerns about oversight and transparency. AI safeguards like human-in-the-loop and explainability are among the building blocks of trust as autonomy expands, underpinning the future of workforce orchestration.
For the WFM professional, skills like data literacy, judgment under uncertainty, exception handling, AI assist oversight, and stakeholder communications will become far more valuable. That repositioning for higher-value work will change how you search for and evaluate managerial talent.
That shift is possible because WFM in NiCE means the same interaction signals and AI models that drive routing, self-service, and agent assist across the customer journey also inform WFM decisions, giving leaders a view of workforce demand that a standalone scheduling tool can't produce.
Are you ready to manage a hybrid contact center?
If you’re still forecasting, scheduling and staffing the same way you did with an all-human workforce, then you’re already partly flying blind. Traditional approaches simply cannot give you a clear view of how work moves through a hybrid enterprise, which carries steep risks for both your employees and your business.
Managing a hybrid contact center requires an intelligent, sensitive, and unified orchestration strategy. That means seamlessly blending human and digital teams, while simultaneously recognizing their differences and taking them into account. And as AI technology advances, WFM will increasingly draw on a whole new set of skills and tools.
For the essential playbook of the next generation of workforce management, download The Dawn of Hybrid Workforce Management: A WFM Leader’s Guide today. You’ll learn about eight configuration best practices, four reimagined WFM disciplines, and a five-step transition plan, as well as the (very rapidly approaching) future of agentic WFM.
