Customer experience (CX) remains a critical differentiator in enterprise operations, yet the gap between escalating customer expectations and delivered service is widening. A recent Verint report, The State of Customer Experience 2026, highlights that over half of businesses are currently falling short of customer service expectations. This analysis delves into the report’s key findings, offering strategic guidance for senior marketing and CX leaders to address this disparity by effectively integrating advanced AI with human capabilities across customer engagement channels.
The Widening Experience Gap and the Mandate for AI-Driven Resolution
Customer expectations are accelerating, significantly influenced by the instantaneous information access provided by AI. The Verint report reveals a substantial increase in customer expectations, with 42% of consumers in 2026 reporting higher expectations over the previous 12 months, a figure that has more than doubled from 19% in 2024. This rapid shift places considerable pressure on enterprises to deliver faster, more effective CX.
Analysis: This trend underscores a critical challenge: traditional service models struggle to keep pace with digitally native customer demands. Simply deploying AI for deflection is no longer sufficient; customers expect AI to resolve issues end-to-end. The consequence of failing to meet these expectations is significant, impacting customer satisfaction as well as retention.
What to do:
- Prioritize AI for comprehensive issue resolution: Develop and deploy AI solutions, such as intelligent virtual assistants (IVAs), that are capable of handling complex queries and processing transactions, not merely answering FAQs. For example, in financial services, an IVA should process a credit limit increase or dispute a fraudulent charge without human intervention, if applicable based on policy.
- Measure AI effectiveness by resolution rate: Shift key performance indicators (KPIs) from simple containment rates to First Contact Resolution (FCR) for AI-handled interactions. Aim for AI FCR rates above 80% for designated use cases.
- Invest in robust data readiness: Ensure AI models are trained on rich, contextualized enterprise data, including historical interaction logs and knowledge bases, to improve accuracy and relevance. Implement strict data governance policies (e.g., anonymization, access controls) to protect customer information and ensure compliance (e.g., GDPR, CCPA).
What to avoid:
- Deploying superficial chatbots: Avoid generic chatbots that only provide basic information or repeatedly ask for clarification, leading to customer frustration and unnecessary escalations.
- Ignoring AI performance metrics beyond cost savings: While cost efficiency is a benefit, focusing solely on it overlooks the primary customer value driver: issue resolution.
- Underestimating the pace of expectation growth: CX strategies must be agile and regularly updated to reflect evolving customer behaviors and technological advancements.
Rebalancing Human and AI Interaction Across Stabilized Channels
Despite the demand for fast, AI-driven resolution, the report indicates a rising preference for human agents, with 61% of customers preferring human interaction, up 5% from the previous year. Concurrently, channel preferences are stabilizing, with a 70/30 split between digital and phone interactions. A notable 95% of consumers interact with companies across two or more channels in a 12-month period, highlighting the pervasive need for omnichannel capabilities.
Analysis: This rebalance emphasizes that customers desire both efficient AI and accessible human support, with seamless transitions between the two. The stabilization of channel preferences offers an opportunity for enterprises to optimize resource allocation, ensuring that AI and human agents are deployed strategically across touchpoints. This requires an operating model that prioritizes contextual handoffs and agent enablement.
Operating Model and Roles:
- AI-First, Human-Ready: Design contact center workflows to leverage AI for routine, high-volume interactions. Equip human agents with AI-powered tools (e.g., Verint Copilot Bots) to handle complex, sensitive, or escalated cases more effectively.
- Contextual Handoffs: Implement Smart Transfer Bots that provide agents with the complete context of a self-service interaction, eliminating the need for customers to repeat information. Establish clear escalation paths and Service Level Agreements (SLAs) for AI-to-human transfers (e.g., transfer within 30 seconds with full transcript).
- Agent Enablement: Empower agents with Knowledge Automation Bots for instant access to approved information and Coaching Bots for real-time guidance based on best practices. This reduces Average Handle Time (AHT) and improves FCR.
- Data Governance for AI Training: Establish clear policies for collecting and using interaction data to train AI models, ensuring customer consent (opt-in/opt-out) is respected, particularly in regulated industries like healthcare or financial services. Regularly audit AI responses for accuracy and fairness through red-teaming exercises.
What this means:
- Unified CX Automation Platform: A single platform that orchestrates AI across self-service and assisted channels is critical. This ensures consistency and enables modular deployment of AI bots without replacing existing systems.
- Cross-Channel Consistency: Ensure that AI and human agents provide consistent information and service quality across all channels. For a telecom provider, this means a customer troubleshooting a modem online then calling in should experience a seamless continuation of support, not a restart.
- Dynamic Routing: Implement advanced routing logic that considers customer preference, interaction complexity, and agent skill sets to direct inquiries to the most appropriate resource, whether AI or human.
The CX Tightrope: Driving Loyalty Through Seamless, Outcome-Oriented Experiences
The margin between earning customer loyalty and losing it has never been thinner. Exceptional customer service is the second most important driver of loyalty, only four points behind product/service quality (48% vs. 52%). Critically, 80% of consumers will repurchase after an amazing CX, but 79% will switch brands after just one terrible experience. This data firmly positions CX as a direct driver of revenue, retention, and advocacy, rather than solely a cost center.
Analysis: This underscores that every interaction is an opportunity to build or erode loyalty. Enterprises must move beyond transactional service to deliver experiences that consistently resolve issues quickly, offer personalized interactions, and provide effortless access to human support when needed.
What ‘good’ looks like:
- End-to-End Resolution: Customers can resolve their issues efficiently through their preferred channel, leveraging AI or human agents, without friction. This means an airline customer can change a flight, apply a voucher, and receive confirmation without navigating multiple departments or systems.
- Personalized, Proactive Engagement: AI delivers tailored offers and promotions (ranked 3rd most important benefit of AI by customers in 2026, up from 4th in 2025) and fully understands customer intent. This extends to proactive outreach for potential service disruptions or personalized product recommendations.
- Effortless Human Escalation: The ability to easily reach a human agent when needed (3rd most important aspect of good CX) and avoid repeating information (4th) is paramount.
Governance and Risk Controls:
- Performance Monitoring with RAG Status: Implement a Red, Amber, Green (RAG) status for all CX channels and AI systems, monitoring FCR, AHT, CSAT, and Net Promoter Score (NPS). Set clear thresholds for performance degradation that trigger automated alerts and human oversight.
- Complaint Rate Analysis: Track and analyze complaint rates related to AI interactions, especially those concerning unresolved issues or difficult handoffs. Use this data for continuous AI model retraining and agent coaching.
- Regulatory Compliance: Ensure AI-driven interactions and data handling comply with all relevant industry regulations (e.g., PCI DSS for payments, HIPAA for healthcare). Maintain audit trails for AI decisions and human interventions.
Immediate Priorities (first 90 days):
- Audit current AI capabilities: Assess existing AI solutions for their ability to deliver end-to-end resolution and seamless human handoffs. Identify critical gaps.
- Map key customer journeys: Prioritize high-volume, high-impact customer journeys that could benefit most from intelligent AI automation and agent enablement.
- Establish CX governance committee: Form a cross-functional committee (marketing, IT, operations, legal) to define policies, data standards, and ethical guardrails for AI deployment and human-AI collaboration.
Summary
The “State of Customer Experience 2026” report clearly delineates the urgent need for enterprises to bridge a widening CX gap. Customer expectations for fast, effective resolution are higher than ever, driven by the ubiquity of AI-powered information. Winning brands will be those that strategically deploy AI to resolve issues end-to-end, equip their human agents with AI-powered tools for faster and more effective service, and maintain a sharp focus on what customers genuinely value: speed, resolution, and seamless access to human support when automation reaches its limits.
The challenge lies not in choosing between AI and human agents, but in orchestrating a balanced approach where AI delivers intelligent, agentic self-service and human agents are empowered to provide empathetic, efficient support for complex scenarios. Enterprises must invest in unified CX automation platforms that enable this delicate balance, ensuring that every customer interaction contributes positively to loyalty and directly impacts the bottom line.
