Dive Brief:
- Only a fraction of customer service organizations — 4% — have achieved the ROI they expected from AI rollouts, according to a Gartner survey of 275 service and support leaders released Wednesday during the Gartner Customer Service and Support Conference.
- Rather than view AI as a way to reduce costs, Gartner Senior Director Analyst Christopher Sladdin encouraged customer service organizations to adopt an “AI-forward” approach during his keynote speech Wednesday and to use the technology to create value within the organization.
- To create value, organizations should analyze the conversational data generated during customer interactions to derive insights into customer needs, how they’re driving successful outcomes and how they may inadvertently cause friction during the customer journey. “AI's superpower is that it enables leadership to learn from customer interactions at scale," Sladdin said in prepared remarks.
Dive Insight:
Executives often expect AI rollouts to reduce costs relative to human-handled customer service interactions. While AI tools may help agents resolve a call more quickly or spend less time taking notes after the call is over, these gains don’t necessarily translate into financial wins — like revenue or market share increases.
As such, CX teams would do well to reassess their AI approach.
CX leaders should instead pursue fewer AI use cases and tie those deployments directly to the organization’s strategic objectives, Sladdin recommended.
Clean, current data is essential to this endeavor. Executing on it means integrating and improving the data and knowledge sources which AI relies on to generate more tailored, relevant insights.
“AI-forward organizations invest nearly 1.8 times more in these foundations than in the AI use cases themselves, helping maximize the value of their overall portfolio,” Sladdin said in prepared remarks.
Driving this value still requires people to make decisions about what use cases to prioritize and which of the organization’s strategic goals should be emphasized. This means surmounting another key hurdle around AI deployments — training people in how, and when, to use the tools they’re given.
“Humans and AI are not fit for the same job. Each can deliver value but in different ways,” Sladdin said. “Leaders must stop asking how they remove humans from interactions and instead ask where their involvement creates disproportionate value for customers.”
