Customer self-service has been a go-to solution for easing the load in contact centers for a long time. Think about IVRs - they've been around since the 1970s, helping automate basic tasks. Over the years, better search engines have made it easier for customers to find answers themselves by tapping into knowledge bases. Tools like these have been working side by side with contact center teams for decades, giving agents some breathing room and helping reduce the constant need for businesses to grow their headcount.Lately, chatbots and generative AI have seriously leveled up the self-service game. During the pandemic, digital channels exploded - and so did the use of bots in contact centers. Before that, customers were only using chat and AI bots around 10% of the time. But things have changed fast. According to Gartner, chatbots are on track to become the main way customers connect with companies by 2027. Even more interesting? They predict that around 40% of customer interactions will be handled by unofficial bots - like ChatGPT or Apple Intelligence.Turns out, customers are really on board with this shift, too. A survey from Heretto found that most people actually prefer starting with self-service when they need help. And AI chatbots aren’t just convenient - they’re getting results. A Glassix study shows they resolve issues 71% of the time and even do it 18% faster than human agents.Contact center agents are starting to see the real perks of having AI on their side. These days, chatbots are handling about 30% of the tasks agents used to do themselves. That frees them up to focus on the conversations that really need a human touch. It’s not just about lightening the load -it’s a big win for efficiency. A survey by LangChain found that agents using AI tools like chatbots aren’t just getting help with the repetitive stuff - they’re able to spend more time on the meaningful, complex interactions that truly make a difference.And today’s AI chatbots are smarter than ever. Thanks to generative AI, they can hold more natural, context-aware conversations. Unlike the old-school bots that just followed a script, these new ones pick up on context and nuance, so their responses feel more helpful - and a lot more human.In 2025, contact centers are leaning into AI to work smarter, not harder. It’s helping teams run more efficiently, personalize customer experiences, and simplify the way things get done. Here are some of the top trends making that happen:
Agentic AI: From copilot to autopilot AI isn’t just backing up agents anymore - it’s starting to take the lead on more complex tasks. These new “agentic” systems don’t just assist; they can actually analyze data, make decisions, and take action on their own, with minimal human involvement. The result? Big boosts in efficiency and some serious cost savings.
Empathetic AI enhancing customer interactions AI tools are getting better at picking up on human emotions in real time, which means they can respond in a more personal and empathetic way. That kind of connection goes a long way - it helps build stronger relationships with customers and leaves them feeling more satisfied with the experience.
Enhanced multimodal support AI makes it easier for contact centers to support customers on whatever channel they prefer - voice, text, or visual interactions. It’s all about creating a smooth, connected experience so customers can get help in the best format for them.
Advanced chatbots and virtual assistants More companies are now using advanced chatbots that can handle even the tricky, complex interactions, and it’s really paying off. Customers stay more engaged, and things run more smoothly behind the scenes.
Ethical AI and data privacy As AI becomes more common, there’s a bigger focus on doing it right - making sure these systems are transparent, responsible, and follow the rules regarding data privacy. It’s all about building trust while keeping everything ethical and above board.
As more contact centers start reaping the benefits of bots, it's raising some big questions about where workforce management (WFM) fits into all of this. If you're navigating a bot-infused world, here are a few things to keep in mind.
WFM forecasting
Most WFM systems are designed with people in mind - they focus strictly on managing the human side of the workforce. So even if you’re among the 58% of contact centers that have integrated your chatbot with your WFM tools, most of what gets tracked is the agents’ workload and interaction history - not what the bots or IVRs handle.That means when your WFM system forecasts staffing needs, it filters out self-service interactions and zeroes in on what your agents actually handled. And here’s the cool part: if your self-service channels get better and start resolving more on their own, the system automatically adjusts and shows a lighter agent workload - and the opposite happens if self-service dips. You don’t need to tweak anything manually. Your WFM tools adapt on their own, giving you smart, reliable staffing forecasts either way.
WFM scheduling practices
How well your bots perform doesn’t directly change how you schedule your team. Instead, their impact shows up naturally over time. As more customers use self-service, your agents handle fewer interactions - and that shift gets reflected in the historical data your WFM system uses to forecast and schedule.It’s kind of like IVRs - you wouldn’t build your staffing plan around how well your IVR is working, right? Same goes for bots. There’s no need for a WFM system to plan employee schedules around bot success rates. What really matters is the data your WFM system collects about your human workforce. That’s what it uses to make smart, accurate scheduling decisions.
WFM change management
WFM forecasting algorithms should be designed to adjust automatically and respond to shifts in self-service performance. This kind of smart forecasting has been around since the rise of IVRs back in the 1980s. When success rates for bots, IVRs, or other self-service tools suddenly change, the algorithms automatically clean up the data - removing any outliers - so your forecasts stay accurate. They’re tuned in to the ups and downs of what self-service is (or isn’t) handling.On top of that, a good WFM system shouldn’t forecast for the whole day - it should break it down by interval. That’s a big deal because it helps contact centers react quickly to sudden changes in bot or IVR performance that might only show up at certain times of day. With a solution like NiCE WFM, intraday reforecasting happens automatically, adjusting staffing needs in near real-time based on how your self-service tools are performing.AvantGuard, a premier provider of wholesale alarm monitoring that offers professional monitoring services, cloud monitoring, and hybrid partnerships, integrated NiCE WFM’s smart, AI-powered forecasting, scheduling, and intraday reforecasting and automation capabilities into their 600-agent contact center. In just the first seven months, NiCE helped AvantGuard realize more than $550,000 in savings by:
Improving agent occupancy
Reducing the cost of agent attrition
Reducing staff time spent managing forecasts, schedules, and intraday demand
Reducing supervisor time spent managing schedule changes
Reducing overtime
The bottom line: Focus WFM on people, not bots
Bots are getting better fast - especially when it comes to handling complex customer service issues - and we’re still just scratching the surface in terms of adoption. The great news? Today’s WFM solutions are already built to handle this shift.There’s no need to schedule bots in your WFM system. Doing that would just mean paying for extra licenses you don’t actually need. Instead, tools like NiCE WFM focus on the traffic that reaches your human agents, helping you forecast and staff based on real employee needs.Want to see how NiCE WFM helps contact centers manage employees in an AI-powered world - without the hassle of tracking bot, IVR, or other self-service traffic? Take a closer look at what it can do.
FAQs
Q: Do I need to forecast bot traffic in my WFM system?A: No. Bot and self-service performance is automatically accounted for in the historical agent interaction data. If bots resolve more, fewer calls reach agents - and vice versa - so your agent workload history naturally reflects this ebb and flow.Q: How is AI currently used in contact centers?A: AI is used in numerous ways, including chatbots, agent assist tools, call routing, transcription, sentiment analysis, and forecasting demand.Q: What are some of the benefits of using AI for customer support?A: AI improves response times, reduces costs, enhances personalization, and helps scale support operations.Q: Can AI replace human agents entirely?A: No. AI complements human agents by handling routine tasks, while humans manage complex or emotional issues.Q: What role does AI play in reducing agent burnout and improving efficiency?A: It can automate repetitive tasks, provide support tools, and reduce cognitive load on agents.Q: What are some of the ways that AI improves response times and resolution rates?A: AI can offer instant replies, auto-suggest solutions, and route queries to the right resource quickly.
Make the smartest buying decision with the latest Gartner analysis
NiCE has been named a Gartner® Magic Quadrant™ Leader for Contact Center as a Service for the 10th consecutive year and is positioned furthest on Completeness of Vision.
Make the smartest buying decision with the latest Gartner analysis
NiCE has been named a Gartner® Magic Quadrant™ Leader for Contact Center as a Service for the 10th consecutive year and is positioned furthest on Completeness of Vision.
