Dive Brief:
- The lion’s share of e-commerce retailers have invested in agentic commerce in some form, most often to boost revenue growth and customer experience, according to a LogicBroker survey of over 600 enterprise e-commerce leaders released Thursday. Nearly 96% have invested in AI capabilities.
- Notably, the top applications are customer-facing, including Al-powered product discovery, Al chatbots, and personalized recommendations.
- Nearly half — 47% — plan to invest $1 million or more into agentic commerce in the next 12 months.
Dive Insight:
The days of businesses only deploying AI solutions on the backend and always keeping a human in the loop are over. Most retailers are comfortable bringing AI solutions directly to the customer.
“Keeping humans in the loop with AI is still sound advice, but the application has shifted,” Julie Geller, principal research director at Info-Tech Research Group, said in an email. “The question isn't about whether to keep humans involved; it is where in the customer journey that involvement matters most and how you design for it.”
Beyond revenue growth and improving the customer experience, e-commerce decisionmakers cited investing in AI for cost reduction and operational efficiency, according to the LogicBroker survey.
AI chatbots have a mixed impact on customer experience. While customers appreciate being able to access help 24/7 and fast responses; AI chatbots consistently fail to handle complex inquiries and customers often are frustrated by what they see as a roadblock to speaking with a human representative.
“Many of these agents sit in an uncomfortable middle ground, neither convincingly human nor comfortably machine,” Geller said. “Responses can be hollow, nonsensical, or arrive too late to matter, and either way, the experience actively damages the brand it was meant to serve.”
With such experiences, it’s no surprise that two-thirds of consumers prefer talking to a human, according to a survey conducted by YouGov on behalf of Pegasystems Inc.
The problem is most companies are underinvesting in the handoff, Geller says.
“When a customer reaches a live agent after an AI interaction, the burden of continuity should never fall on them,” Geller said. “They should not have to repeat themselves or wait while an agent catches up. The transition needs to be invisible, with the agent arriving fully informed and ready. Right now it rarely is.”
Meanwhile, the ROI of AI can be elusive. Gartner predicts that costs per resolution for generative AI will exceed $3 by 2030 — more expensive than many offshore agents. Rising data center costs, AI vendors pivoting from subsidized growth to seeking profitability, and complex use cases all may contribute to rising AI costs.
That’s not to say companies shouldn’t invest in AI. Geller says the strongest use cases of AI is when it “is operating quietly in the background.”
Retailers are also investing in operational capabilities on the back-end: 44% are investing in pricing optimization, and 43% in automated inventory management, according to LogicBroker.
“Pricing optimization and demand forecasting work well because the variables are quantifiable, the feedback is immediate, and there is no direct customer relationship at stake if the model gets it wrong,” Geller said.
AI can also be useful for product discovery, and consumers have signaled their comfort using the technology for research.
“On the customer-facing side, product discovery has real merit when trained on behavioral signals and context rather than just search terms,” Geller said. “A shopper who looks at something three times and never buys is communicating something, and AI reads that better than any keyword logic.”
