Medallia’s AI Bet in Vegas: Can Customers Move From Insight to Action?

The Gist

• AI-driven analytics. Medallia introduces conversational AI and automated topic discovery tools.
• Unified account insights. B2B accounts now have centralized profiles and linked metrics.
• Enterprise impact focus. Business leaders gain faster actionable insights to improve outcomes and efficiency.

LAS VEGAS — Medallia is betting (see what we did there) that GenAI-powered analytics can finally close the gap between customer feedback and frontline action.

The company unveiled new generative AI capabilities on Feb. 11 at its Experience '26 conference at the Wynn Las Vegas. The release includes Insights Assistant, Smart Topic Builder, expanded language support and unified B2B account profiles.

According to company officials, the enhancements aim to democratize access to analytics and simplify how teams transform data into action. More than 550 brands representing hundreds of thousands of users have deployed Medallia's Frontline-Ready AI capabilities since launch last fall.

Will Medallia Hit Adoption Jackpot?

In this city, Medallia will need more than luck to hit the jackpot in terms of customer AI adoption. Not that adoption isn't there. It is, according to Medallia's numbers.

But providers in the customer experience software space won't stop facing artificial intelligence adoption hurdles in these infancy years, experts tell us. McKinsey finds that only 23% report their organizations are scaling an agentic AI system somewhere in their enterprises (i.e. expanding the deployment and adoption of the technology within a least one business function), and an additional 39% say they have begun experimenting with AI agents.

Not exactly widespread adoption.

However, Deloitte in a 2026 report finds 42% of companies believe their strategy is highly prepared for AI adoption and 30% say the same about risk and governance, both increasing from 2025.

Providers Need to Instill Confidence in AI Outcomes

But this story today is about Medallia and its customers. Will brands dive into full integration and adoption, and how will Medallia enable that to happen? And, if there is adoption reluctance, what will be the blockers and can Medallia serve as an AI Enterprise Hand Holder? That's the world we live in today when it comes to the energy between innovators and brands on the ground floor.

"If you build it, he will come — but only if we have strong security, privacy, governance, data, support, training, actionable insights and ROI." This Field of AI Adoption Dreams moment comes with some parameters, clearly.

Platform innovators that instill confidence in AI adoption that translates into outcomes — not just insights — will win in 2026, industry observers tell CMSWire.

"While adoption of AI features in AI‑enabled products appears healthy at first glance, with many vendors estimating 55% to 75% adoption, in reality, maturity has stalled," said Maria Marino, VP analyst in tech marketing for Gartner. "Users rely on AI mainly for basic tasks like summarization and content creation. Advanced use cases — those that automate entire workflows and deliver transformative business outcomes — remain blocked by factors such as security and privacy concerns, data readiness, limited user skills and fear."

The good news for Medallia? It's got real adoption momentum on its existing “Frontline-Ready AI” set; 550+ large brands already deployed capabilities like Intelligent Summaries, Root Cause Assist, Smart Response and Themes with GenAI.

"And that ain’t nothing to sneeze at for early AI efforts," said Ian Jacobs, VP, lead analyst at Opus Research.

"But the differentiator they’re aspiring to own," Jacobs added, "is the operating model itself, 'unify analysis and execution' as they say, and make action traceable inside the platform," Jacobs said. "The proof point to watch there is whether Action Planning becomes the system people actually run work through, versus some elegant and pretty add-on that still ends up exported into other tools."

Related Article: Survey Shuffle to AI Shuffle: Medallia Wants to Reshape the CX Deck

What Are the Blockers for AI in Customer Experience Adoption?

Therein lies the conundrum for Medallia and providers like them: real usage of AI in the enterprise, especially when you've got analysts predicting AI will cost more than offshore agents in four years. It's like convincing that friend who comes to Vegas "just for the sights" to drop a few hundred on some blackjack. "I'm not much of a gambler," they'll say, much like heavily-regulated brands who aren't ready to roll out artificial intelligence across the entire customer service and support enterprise.

Those very blockers to AI create short‑term financial and customer experience challenges for tech providers investing heavily in AI innovation, Marino added.

How can Medallia win amid these blockers? Go beyond launch announcements and feature‑level adoption campaigns, Marino said, adding, "Customers need education and enablement to use AI and AI agent co‑workers to achieve transformative — not incremental — value. All VoC platform vendors will need to deepen their understanding of customers’ critical business processes to accomplish this."

Customer Insights Are Cheap. 'Operational Change Is Expensive'

The big bet Medallia — and others in the conversational AI space — must land is "organizational accountability," according to Jacobs.

"We’ve learned in the conversation intelligence market that insights are cheap but operational change is expensive," Jacobs told CMSWire. "Here, the organizational bottleneck is governance. Brands need to have documented and auditable systems that decide who can act, who must approve and how to measure impact without gaming the metric."

If an AI assistant can propose “the answer,” who’s on the hook for validating it, acting on it and measuring it?

"So, for now, the differentiator is less ‘better AI’ and more ‘better accountability,'" Jacobs added. "The failure mode is no longer missing the insight, it’s missing the execution."

Medallia Experience: 2025 vs. 2026

How Medallia’s CX narrative — and analyst expectations — shifted year over year.

Medallia's New Capabilities Overview

What kind of AI dice is Medallia rolling out this week in the desert of Las Vegas? The big integration is embedding conversational AI and automated topic discovery into the platform.

Let's take a peek at some of the tools Medallia says will eliminate bottlenecks typical of research-heavy platforms:

Inside Medallia's Rollout: Conversational Analytics and Native GenAI

Medallia’s latest AI updates focus on removing friction between insight and action, making analytics more accessible, faster to maintain and easier to operationalize across global and B2B environments: 

• Conversational analytics for everyone. Insights Assistant lets teams “talk” to their data in plain language, instantly validating hypotheses and uncovering root causes while respecting access controls and organizational context.
• Automated trend discovery without the black box. Smart Topic Builder uses AI to surface emerging themes in minutes instead of weeks, while keeping humans in the loop to audit, approve and trust the results.
• GenAI analytics go multilingual. Native GenAI features now support French and German, with Spanish already announced, enabling global teams to standardize insights without relying on native-language analysts.
• Insight-to-action, with proof. Enhanced Action Planning ties insights directly to execution and real-time performance tracking, linking operational changes to outcomes like NPS and CSAT.
• Unified B2B account intelligence. Account Profiles bring business-level health metrics and individual stakeholder interactions into one view, eliminating silos and simplifying retention and growth decisions.

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Insights Assistant Signals Parity, Not a Leap

From a product-strategy standpoint, Marino sees Medallia’s launch of Insights Assistant less as a breakout move and more as a necessary catch-up moment in a fast-crowding market. Conversational querying and plain-language analytics have already become table stakes across the VoC landscape.

“With the launch of Insights Assistant, Medallia is reaching parity with other VoC platforms that have already introduced similar capabilities,” Marino said.

She points to comparable offerings from Qualtrics, Sprinklr, Concentrix, Alchemer and Pisano, all of which already allow users to query dashboards, summarize results or generate recommendations using natural language.

The takeaway, she says, is straightforward: “Bottom line: Medallia is catching up.”

Lowering the Skill Barrier Changes How Users Engage

Where Marino does expect meaningful change is in how customers interact with the platform day to day — particularly among non-technical users who previously relied on analysts to surface insights.

According to Marino, Insights Assistant removes the need for users to be “data specialists or fluent in statistical methodologies” to get value from the platform. Instead, frontline managers and business users can ask role-relevant questions and receive actionable answers tied directly to operational decisions.

This behavioral shift, she notes, is not unique to Medallia. It reflects a broader SaaS trend where conversational AI is reshaping workflows by making advanced analytics accessible to a much wider audience.

Smart Topic Builder Is the Real Differentiator to Watch

If there’s a capability that could set Medallia apart in 2026, Marino points to Smart Topic Builder—not conversational analytics.

Maintaining accurate and relevant topic models has long been one of the most resource-intensive pain points across VoC platforms, she said, even as vendors promote prebuilt or industry-tuned models.

“Building and maintaining topic models has long been a challenge for users across VoC platforms, including both Medallia and Qualtrics, even though each promotes industry-tuned topic models,” Marino said, adding that she consistently hears from customers — both at Medallia’s conference and through ongoing conversations — that topic maintenance remains “a high-effort, high-overhead task.”

If Smart Topic Builder performs as advertised in live customer environments — automatically surfacing, generating and categorizing topics from unstructured feedback — Marino believes it could materially improve how usable and actionable VoC data becomes, shifting effort away from maintenance and toward execution.

No 'Extra Complexity' With Built-in AI

Medallia Post-COVID Milestones

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What We're Seeing: GenAI & Omnichannel in the Customer Service Spotlight

What have we learned at CMSWire lately? Generative AI embedded in omnichannel contact center platforms is reshaping operational efficiency by automating topic discovery, accelerating insights delivery and compressing time-to-action.

Modern conversational AI analytics platforms integrate GenAI-powered assistants that synthesize answers from large internal datasets, draft personalized responses and generate tailored follow-ups. These tools surface next-best actions and suggested responses during live interactions, reducing agent cognitive load while improving resolution speed.

Owning the Loop From Insight to Execution

At the heart of Medallia’s Experience ’26 message is a clear claim: the competitive battle in 2026 is no longer about who can surface insights fastest, but who can operationalize them reliably. As Jacobs frames it, dashboards are no longer the prize. The loop from insight to execution is.

That distinction matters because feature adoption alone doesn’t change how organizations work. In many enterprises, new AI capabilities will simply accelerate reporting — faster summaries, quicker analyses, cleaner charts — without altering decision-making or accountability. In those cases, the workflow stays the same. Only the output improves.

But for organizations willing to change how they operate, Jacobs sees two meaningful shifts emerging:

• First, self-serve analysis becomes the norm. CX and operations leaders stop waiting on specialist teams to run reports and instead use conversational assistants to ask role-specific questions and act on answers directly.
• Second, action — not the presentation deck — becomes the primary artifact of work. Launching Action Plans from reports and tracking performance inside the workflow pushes teams toward follow-through, ownership and measurable impact.

That arc mirrors how Jacobs and his team evaluated vendors in Opus Research’s conversation intelligence Intelliviews, where the real differentiator wasn’t insight generation but operationalization. The hardest problem, he notes, is no longer finding themes in customer data. It’s turning those themes into repeatable decisions, routing them to clear owners and proving that actions taken actually moved the metric.

That’s the bet Medallia is making in Las Vegas: that the platforms which win in 2026 won’t be judged by how smart their AI sounds, but by whether organizations can run their business through it — end to end.

"Medallia is telling the market that 2026 is about running the loop from insight to execution, not just generating insights," Jacobs said. "Medallia is betting that the next battleground is who owns the loop from insight to execution, not who can generate the prettiest dashboard."

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