Which AI tools do leaders say are critical for navigating staffing obstacles and driving financial performance objectives? We collected input from 750 contact center leaders across industries and operation sizes to find the answers.
- The top CX and operational challenges heading into 2022
- The most important use cases for AI in the contact center
- How AI initiatives differ across contact center sizes
- The near-term AI adoption plans for small, mid-sized, and large contact centers
- Where the opportunities lie for contact centers.
Below we outline some report highlights. Download the full survey report for deeper insights into contact center AI initiatives within the enterprise and beyond going into 2022.
Large or small, contact centers face similar challenges
Across industries and company sizes, contact centers faced similar struggles in 2020-2021. Leaders say their biggest challenges have been managing work-from-home agents’ productivity and performance amid higher than usual inbound call volumes. Many also pointed to additional difficulties stemming from a combination of pandemic-related business restrictions and severe staffing shortages.
The most important use cases for AI
Managing remote agents and high call volumes are not the only similarities shared across large and small centers. It’s interesting to note that smaller contact centers with 25-50 FTEs and large operations of 250+ FTEs were more closely aligned in their AI objectives than mid-sized centers (51-250 FTEs). Smaller contact centers, in particular, see the value of AI to drive CX with 41% of leaders selecting it as the most important use case vs. 28% that say increasing efficiency is key. Mid-sized contact centers (51-250 FTEs), by far, value increased efficiency—36% selected it as the most important use case vs. 28% of 250+ seat centers and 25% of 25-50 seat operations.
Large centers are outpacing smaller operations
As the clear drivers of AI adoption, larger contact centers are quickly putting in place the infrastructure and capabilities to meet and exceed customers’ expectations, which will set the pace and CX benchmarks for companies across industries and sizes.
SMB late-comers may soon find the CX gap widening as larger enterprises get better at understanding, anticipating, and acting upon customer insights. Only 9% of 25-50 seat contact centers and 14% of 51-250 seat operations have implemented AI. While plans to deploy AI in the next 12 months have intensified for both segments, a significant concern is that another 34% of SMBs said that they don’t intend to use AI in the near term. That could put SMBs’ CX initiatives at a severe competitive disadvantage as AI approaches mainstream adoption.
Fortunately, SMBs can take AI adoption lessons from their larger counterparts to create similar paths leading to quick productivity, CX, and ROI boosts. Addressing your top pain points first will generate early cost savings:
- Applying AI-powered tools to manage, track, and improve your work-from-home team’s performance will increase agent productivity, quality, training, development, and engagement.
- Chatbots and conversational IVR are highly effective self-service options that can considerably reduce inbound call volume. Additional cost savings will come from faster service delivery, streamlining processes and workflows, and fewer errors.
With these quick wins in place, you can focus on expanding your AI capabilities. Adding business intelligence and analytics tools to uncover customer intents and identify patterns to make informed decisions about what customers really want will help you deliver a competitive advantage no matter your company size.