Session Overview
Verint Engage 2025 brought together a panel of experts to explore the role of generative and agentic AI in reshaping customer experience (CX). The discussion highlighted the evolution from rigid, script-driven bots to dynamic, contextual AI agents capable of managing multi-step processes and non-linear customer journeys.
Key themes included practical starting points such as intelligent triage and “Where Is My Order?” tracking, the balance between pragmatist and “true believer” adoption strategies, and the importance of governance and observability in scaling AI responsibly. Panelists emphasized that a hybrid future is inevitable where generative AI will coexist with legacy systems in the near term, gradually advancing from automation to true autonomy.
Industry Perspective
This session points to a pivotal moment in the CX market where organizations are shifting from experimentation and moving into enterprise-scale adoption. Conversational AI has promised value but has struggled with customer frustration and limited functionality. Generative AI changes the equation by offering contextual reasoning and the ability to pivot across customer journeys. For example, turning a simple phone call about a transaction request into fraud detection and escalation when a suspicious charge is identified through the conversation.
Agentic AI extends this further by orchestrating multiple processes across the enterprise. A refund request that also involves a change of address, for instance, requires the AI to coordinate tasks across billing, logistics, and customer service systems; a big leap from task automation and into cross-functional orchestration.
theCUBE Research data shows that 62% of enterprises now prioritize AI initiatives for CX transformation, but complexity and governance remain top obstacles. This session reinforced that point by highlighting how capabilities are advancing rapidly but adoption barriers include cultural resistance (the “fear of losing power” over predictable systems), regulatory restrictions, and the difficulty of scaling prototypes into production.
The “pragmatist vs. true believer” framing is particularly relevant for CX leaders. Pragmatists enhance legacy systems with new AI capabilities, ensuring compliance and continuity in industries like healthcare and financial services. True believers adopt an “AI-first” mindset, prioritizing agility and rapid deployment. Both paths have merit, but most enterprises will converge on a hybrid model that layers AI functionality onto existing infrastructure.
Notably, panelists challenged the oft-cited statistic that 95% of AI projects fail. They argued this figure is inflated by experimental pilots and science projects. While a fair assessment, if we only look at mature organizations implementing AI in the most practical ways, the number would be inflated just the same.
Moving Forward
For organizations preparing to embrace AI and LLMs in CX, several imperatives emerged from this session:
- Anchor AI to Use Cases: Start small with tangible, high-impact applications like intelligent triage or order tracking. Use the “jobs to be done” framework to ensure alignment with customer outcomes rather than chasing technology hype.
- Plan for Hybrid Futures: Expect to manage a “hybrid state” where curated NLU bots, legacy IVRs, and generative AI coexist. Design governance and integration strategies that allow these systems to complement one another.
- Implement Guardrails and Observability: Security, privacy, and compliance must be embedded into AI deployments. Platforms should provide auditability, metacognition (AI monitoring AI), and scrutability with the ability to explain both what AI did and what it was prevented from doing.
- Balance Culture and Regulation: Address the “fear of losing power” by involving stakeholders early, while navigating regulatory restrictions with secure, compliant deployments.
- Build for Scale, Not Just Prototypes: Avoid the trap of flashy demos that fail in production. Enterprises should establish frameworks for scaling AI from pilot to enterprise deployment, including KPIs, success metrics, and operational ownership.
Looking ahead, the industry will remain in a hybrid state for at least the next 18–24 months. But the trajectory shows automation will evolve toward autonomy, with agentic AI enabling cross-enterprise workflows and delivering on the long-standing vision of a conversational economy. CX leaders who ground their AI strategies in clear use cases, strong governance, and scalable platforms will be best positioned to close the engagement capacity gap and unlock sustainable competitive advantage.
Real-Time Fan Engagement as a Platform Problem
Chiplet Summit Signals the Operational Era of Chiplet-Based Design
GitLab Pushes Agentic AI Beyond Code With Duo Agent Platform GA
Last-Mile Connectivity Emerges as a Hidden Constraint on Network Agility
Executive CISO Titles Signal a Structural Shift in Cyber Leadership
