The use of artificial intelligence (AI), machine learning (ML), and agentic AI in contact centers and other customer experience (CX) organizations has prompted some leaders to question the necessity of traditional systems and applications, such as workforce management (WFM), to optimize and engage their employees. This issue stems from the market’s perception that AI will eliminate the need for human agents, an idea that has been debunked, at least for the time being. But it does raise many issues for companies to consider as they make plans to strategically integrate AI into their CX operations. One of the most important is how their workforce will evolve and the role WFM is going to play in supporting a hybrid human/AI workforce.
Here are a few of the important factors CX leaders must address as they embrace and build a synergistic hybrid workforce of the future:
The evolving role of human agents in the era of AI
AI automates routine inquiry and transaction handling, freeing human agents to focus on complex, high-value, and emotionally charged issues. WFM solutions must adapt their forecasting, scheduling, intraday management, and long-term planning capabilities to account for inquiries/interactions that are increasingly expected to be offloaded to multimodal conversational AI (CAI) solutions or jointly handled by human and automated agents. This will require a shift from projecting total volumes to predicting human-handled activity, cognitive load, knowledge, and specialized skills. CX leaders will also need to consider how agent well-being and burnout prevention strategies must evolve, since human agents will increasingly handle emotionally intense and cognitively demanding interactions.
Profound shift in expectations for human agents
CX organizations will need to change their expectations, perception, hiring profiles, and compensation for agents to align with the functional requirements of an AI-enabled contact center. Job descriptions and recruiting strategies should be updated to identify “customer success advisors” who demonstrate AI literacy and fluency, critical thinking and judgment, strong analytical capabilities, and specialized skills. This profile is in contrast to entry-level employees who adhere to scripts and focus on handling speed. The new class of “brand ambassadors” should be empowered and rewarded for owning the customer relationship and journey, enhancing loyalty and lifetime value. Training programs must also evolve to reinforce AI collaboration skills, embed ethical decision‑making frameworks, and cultivate adaptive communication strategies—ensuring that agents not only meet the new role requirements but thrive within them.
Real-time adaptive intelligent AI-based routing’s impact on WFM
WFM solutions are highly reliant on and effective at using skill-based scheduling to identify and optimize agent utilization. However, the newly emerging real-time adaptive intelligent AI-based routing models take this concept from a traditional pre-planned and relatively static staffing model to a dynamic, in-the-moment optimization process. The routing engine will have the ability to override the fixed (planned) schedule, access the intraday management module, and adapt the schedule on the fly in near-real-time to deliver interactions requiring live assistance to the optimally skilled human agent best suited to handle the contact. This shift will require WFM systems to integrate seamlessly with AI routing models and must provide transparency and auditability so enterprises can have confidence in automated decision-making.
The need for massive volumes of high-quality CX data to fuel AI
Contact centers and CX organizations are a major and essential source of customer data used to support enterprise-wide AI initiatives. Companies must eliminate their data silos so that contact center, CX, and all customer relationship management (CRM) data can be shared with enterprise AI initiatives and vice versa, including WFM AI models. Data governance and compliance frameworks must evolve in parallel, ensuring sensitive customer information is protected while enabling AI‑driven insights. Building a unified data layer is critical to orchestrate AI initiatives across the enterprise, including the workforce management intelligent assignment model, which will offer enhanced scheduling capability that uses AI to plan and then adapt in real-time. As the agent role changes and they take on new responsibilities for building and enhancing customer relationships and revenue, it will become even more critical to track all components of the customer journey. This data is essential for properly planning and allocating the resources needed to deliver the personalized experiences customers expect.
Bottom Line
AI, ML, and agentic AI are changing many operational and technical aspects of contact centers, including workforce management forecasting, scheduling, intraday management, and planning. AI is not a replacement for WFM, but it is a necessary enabler that is fundamentally transforming WFM from a high-value historical forecasting and scheduling solution into an intelligent, real-time strategic optimization and engagement engine: one that will vastly improve customer and employee engagement due to its ability to facilitate the delivery of interactions requiring human assistance to the right employees, wherever they are in the enterprise. WFM must be reimagined and utilized as a strategic enabler, helping organizations orchestrate their hybrid human/AI workforce, and influence how they act, how fast they move, and how much their actions matter. This is a necessary phase in helping companies future-proof their CX organizations in the era of AI.
