There is so much excitement about how AI is changing customer service operations. What was once a reactive, cost-heavy, and manual function into a proactive function that drive revenue growth. C-level executives and board members are more than curious. They are leaning heavily into the ROI potential of AI in customer service technology. Our research reinforces this shift; Forrester’s job impact report shows that AI will put more than half of today’s customer service jobs under pressure.

AI also has other advantages. It’s reshaping the customer service technology landscape by replacing existing capabilities supported by best-in-class vendor ecosystems. This means that AI will ultimately reduce vendor sprawl, lower total cost of ownership, and give organizations more flexibility in deploying and paying for the capabilities that they only need.

But despite this excitement, there’s confusion. Today’s vendor solutions are not equally mature. AI adoption is slow. And value is hard to quantify beyond the straightforward use cases. More stakeholders are involved in purchase decisions due to this uncertainty, purchases stall or cycles are extended.

Forrester has published two reports to help customer service and IT leaders with the discovery and evaluation of top vendors in the space. The Customer Service Landscape highlights top vendors and includes an analysis of market dynamics and top use cases. The Customer Service Wave drills into the strength of offering and strategy of the top 12 vendors in the space.

Customer Service Solution Are Evolving Into Agentic Solutions

Via our Wave evaluation, we found that vendors are pursuing different modernization strategies. As you consider vendors for your customer service operations, look for:

  1. New UX and unified tooling to manage CSR and AI operations. Today, CSRs use AI-assist tools to manage their workload. As AI becomes more pervasive, the role of AI and the CSR flips: AI addresses the majority of the work, while CSRs assist AI by taking action on exceptions or work that AI can’t handle. This shift also prompts the need for new user experiences tailored to AI-first jobs as well as capabilities such as unified analytics to manage the quality of AI and CSR engagement. Look for vendors that offer tightly blended AI and CSR experiences and measurement and optimization frameworks for AI.
  2. In-product learning loops to strengthen AI. AI outputs within customer service operations must be monitored to pinpoint improvements. This takes orchestration across many capabilities. For example, process intelligence tools surface automation opportunities and process bottlenecks; quality management and conversation intelligence measure CSR and AI agent performance and surface insights. These insights prompt upskilling and CSR coaching, new knowledge base content, and improved processes. Look for vendors that offer frameworks spanning feature sets that are used to suggest changes and eventually make them.
  3. Broader sets of capabilities. Conversational AI, CCaaS and case management are rapidly consolidating as vendors attempt to own the end-to-end orchestration of customer conversations, engagement, and case workflows. Prioritize customer service solution vendors that either showcase strong end-to-end capabilities within their product or have solid partnerships and well defined integration patterns with adjacent ecosystem vendors.

Connect with me via inquiry to dive deeper into customer service trends, vendor strategies and offerings. There’s a lot going on in this space!