CX Today

A recent Gartner report suggests that by 2030, generative AI could cost more per customer interaction than a live human agent. What does that mean for small and midsize businesses?

In this episode of CX Today, Francesca Roche speaks with Nathan Strum, CEO of Abbey Connect, about how SMBs should rethink automation budgets, customer journeys, and long term growth strategies. Instead of focusing only on cost reduction, Nathan outlines a rebalancing approach that starts with human systems and works backward to apply AI where it adds value.

For more Customer Experience tech news visit https://www.cxtoday.com

Rhys Fisher, Associate Editor at CX Today, sits down with Kevin McGachy, Head of Solutions at Sabio, to cut through the AI noise that's plaguing contact centers.
If you're tired of flashy AI demos that promise the world but deliver generic chatbots, this conversation is your reality check.
Kevin breaks down the costly mistakes organizations make when racing to deploy AI, why voice is still king despite the digital self-service push, and how outcome-based strategies can protect you from vendor lock-in and wasted investment.
This isn't another AI hype session; it's a practical roadmap for CX leaders who need results, not regrets.
In this frank discussion, McGachy exposes the pressure-driven mistakes that are costing organizations time, money, and competitive advantage:
• The ROI Trap: Why building business cases solely around cost reduction creates friction and misses the real value of AI – like addressing high attrition through “zero human impact” automation that doesn't eliminate jobs
• Technology-Agnostic Design: How to avoid vendor lock-in by designing systems that can swap between LLMs (Gemini, GPT, etc.) based on performance and cost, rather than betting everything on today's ‘winning’ model
• Voice's Staying Power: Why customers still prefer voice for urgent or emotional issues – and how modern conversational AI creates fluid, human-like experiences that adapt in real-time versus rigid IVR decision trees
• Outcome-Based Pricing: Sabio's approach to only charging clients when AI successfully resolves customer interactions, eliminating the risk of paying for underwhelming results

AI may be everywhere in customer experience, but according to Bloomreach CEO and Co-Founder Raj De Datta, much of it still falls short of delivering real business impact.
Speaking to CX Today, De Datta reflected on Bloomreach’s recent milestone of surpassing $260 million in annual recurring revenue, a result he attributes largely to the company’s AI-native approach and the evolution of its Loomi AI platform.
Rather than treating AI as an add-on, Bloomreach has embedded it directly into the mechanics of personalization, campaign execution, and product discovery.
De Datta warned that many organizations rush to introduce AI without rethinking the workflows underneath:
“When you go bolt on AI to an otherwise pre-existing workflow with very little change or a pre-existing system, it’s not that it doesn’t work, it’s just that it doesn’t add that much value.”

Simple use cases, such as AI-generated copy suggestions, can add incremental value, but rarely move the needle on revenue or efficiency.
The conversation also explored the rise of agentic commerce and what it means in practice, with De Datta outlining three emerging models, from AI-led research conducted through conversational agents; to on-site conversational experiences; and finally, fully agent-driven purchasing.
While much of the industry is focused on the end state, he suggested most near-term value will come from the first two.
Looking ahead, De Datta advised CX leaders to focus on discoverability in conversational channels, invest in AI-native customer communication platforms, and apply AI to operational tasks that free up teams to focus on higher-value work.
As AI becomes a primary interface rather than a background tool, the pressure on CX teams to get this right is only increasing.

In an era where data breaches are daily headlines, how a company handles a mistake matters more than the mistake itself. Brad Anderson, President of Product Engineering and Security at Qualtrics argues that “radical transparency” is the only way to survive a security misstep.
In this interview with Nicole Willing, Anderson warns against the common corporate instinct to minimize the impact of a breach (“only a small number of users affected”) before having the facts.
He explains that modern trust is built on clarity: telling customers exactly what happened, who was affected, and what is being done to fix it. If a brand cannot prove it is protecting data, it cannot build loyalty.
Beyond crisis management, Anderson details how to build trust proactively by using AI to detect “digital frustration” signals—like rage-tapping—and intervening to help customers before they abandon the brand. There is a clear difference between AI “science projects” and AI that actually solves problems, Anderson argues, making the case that leaders must shift focus to “pragmatic AI” tools that actively close feedback loops and repair broken journeys in real-time.
Don’t miss this conversation on the critical trust barrier for enterprise AI adoption, and the rise of AI-enabled “synthetic research” to cut insight time from weeks to hours.
For more Customer Experience tech news visit https://www.cxtoday.com

Francesca Roche sits down with Sarah Bruno, a Partner in the Emerging Technologies Group at Reed Smith, to discuss the recent investigative sweep by California’s Attorney General targeting retail, grocery, and hotel sectors for their use of consumer data in surveillance pricing.
Sarah Bruno explains that the sweep focuses on how companies use algorithms to set individualized prices based on personal and non-personal data that consumers may not anticipate is being collected. She highlights why these sectors are targeted, given their broad consumer base and the variety of data collected both online and offline.
The discussion covers the complexity of compliance. Bruno emphasizes the importance of transparency and human oversight in algorithmic pricing to avoid misleading, unfair, or discriminatory outcomes. She notes that algorithmic pricing can unintentionally lead to discriminatory effects based on data patterns, rather than company intent, and stresses the role of disclosure to maintain customer trust.
Bruno considers how this California sweep could set a precedent for other states, influencing how businesses across the U.S. approach personalized pricing, loyalty programs, and CX transparency. She underscores that companies may need to adapt their data collection, notice, and transparency practices to align with evolving regulatory expectations while preserving customer engagement.