AI and Customer Experience in 2026: From Agentic AI to Anticipatory CX
55% of CEOs say AI is their top investment priority. Yet most lack the data foundation to make it work. Consequently, KPMG's global CX benchmark reveals what separates AI leaders from the rest.
- 55% of CEOs call AI their top priority, but 75% admit they can't hire the talent to execute on it. As a result, the ambition-capability gap is real.
- Agentic AI doesn't just follow rules - it senses, reasons, and acts. That changes CX from reactive to anticipatory.
- Only 25% of banks have the cloud infrastructure to support AI-driven services. Most organisations are nowhere near ready.
- Instead, the companies winning with AI aren't replacing humans. They're freeing humans to do what AI cannot: build trust and show empathy.
KPMG interviewed 80,000 people about customer experience. Their conclusion: AI is no longer a future bet - it's the technology defining who wins and who falls behind. The 2025-2026 Global Customer Experience Excellence report positions agentic AI as the central enabler for the next generation of CX.
However, here's the uncomfortable truth. Most companies talking about AI in CX don't have the data foundation to make it work.
The Ambition-Capability Gap
55% of CEOs rank AI as their top investment priority. At the same time, 75% admit that competition for AI talent could slow their growth.
Everyone wants AI. Yet few have the infrastructure, data quality, or organisational readiness to use it well. Among the companies we work with, we see this gap constantly: ambitious AI roadmaps built on top of fragmented data, disconnected systems, and manual processes.
The question isn't whether to invest in AI. It's whether your foundation can support it.
What Is Agentic AI - and Why Should You Care?
KPMG defines agentic AI as systems that independently sense, reason, and act. This isn't the chatbot on your website. Agentic AI can:
- Coordinate processes across teams, channels, and systems in real time
- Adapt to changing customer needs without human intervention
- Act autonomously within defined guardrails
- Learn continuously from feedback loops
Two Roles: Orchestrator and Participant
As an orchestrator, AI manages complexity the customer never sees. It ensures the right information reaches the right person at the right time across departments. The customer experiences coherence; behind the scenes, AI is preventing the chaos.
As a participant, AI interacts directly - answering questions, recommending next steps, completing transactions. Not as a poor substitute for a human, but as an informed agent drawing on the full breadth of organisational knowledge.
What the Best Companies Actually Do with AI
They've moved from reactive to anticipatory
The real shift isn't faster responses. Instead, it's predicting needs and acting before the customer has to ask. That requires data, models, and processes most companies haven't built yet.
They use AI to amplify people, not replace them
KPMG's key finding: "Outperformers balance technology adoption with a relentless focus on people - especially customers."
In practice, this means AI handles:
- Pattern recognition across thousands of feedback responses
- Routine follow-up automation (close-the-loop notifications, task routing)
- Sentiment classification that would take analysts weeks to do manually
- Churn prediction based on behavioural signals
Meanwhile, humans invest the freed-up time in strategic advisory, relationship building, and the judgement calls AI cannot make.
The Empathy Paradox
The pillar with the strongest growth in KPMG's data? Empathy - up 4% in Australia. In an era of accelerating AI adoption, the human dimensions differentiate most. Indeed, AI that lacks empathy undermines trust. This is not a contradiction. It's the point: AI should make space for more human connection, not less.
Competition Is No Longer Brand vs. Brand
One of the report's most provocative claims: "Competition is no longer just between brands - it's brands competing for a place in the customer's personal AI's decision logic."
As consumers and businesses use AI assistants to evaluate providers, your structured customer data becomes a competitive asset. Consequently, if your feedback, reviews, and performance data aren't captured and accessible, you become invisible to AI-driven decisions.
This has direct implications for Voice of Customer programmes. In other words, systematic, structured data collection isn't just about internal improvement - it's about external visibility.
Three Prerequisites - and Where Most Companies Fail
1. Clean, Structured Customer Data
AI without data is blind. The most sophisticated model in the world cannot personalise experiences without a foundation of clean, structured feedback and behavioural data. Therefore, this starts with systematic NPS, CSAT, and open-ended question collection.
2. Integrated Infrastructure
Only 25% of banks have enterprise-wide cloud platforms supporting data-driven services. The rest are fighting data silos and legacy systems. Your CX platform, CRM, support tools, and sales data must talk to each other. Without integration, AI has nothing to work with.
3. Expertise to Turn Insights into Action
AI generates insights. Humans turn them into decisions. Strategic prioritisation, stakeholder alignment, and implementation remain fundamentally human disciplines. Ignore this, and you'll have dashboards full of predictions that nobody acts on.
What We See in Practice
Among the Nordic B2B companies we work with, we see three patterns:
Pattern 1: AI-ready but action-poor. Companies with good data and AI tools but no process for acting on insights. The AI identifies at-risk accounts. Nobody calls them.
Pattern 2: Action-ready but data-poor. Teams eager to follow up on feedback but working from fragmented, inconsistent data. They close the loop on what they see, but they're missing half the picture.
Pattern 3: The integrated approach. Clean data flowing into AI analysis, with automated routing to the right people, who have the authority and context to act. These are the companies seeing measurable impact on churn and expansion revenue.
Most companies are in pattern 1 or 2. Thus, getting to pattern 3 requires investment in data integration first, AI second.
What This Means for Your CX Strategy
Start with the foundation. Before investing in AI tools, ensure you have clean, structured customer data. Implement systematic feedback collection and integrate it with your CRM.
Connect your systems. AI requires data flowing across platforms. A customer journey map helps you identify the touchpoints where data capture matters most.
Use AI to amplify, not replace. Automate analysis and routine follow-up. Invest the freed-up time in strategic advisory and personalised customer relationships.
Keep the human at the centre. KPMG's data is clear: the best companies balance technology with human focus. AI is an amplifier. Empathy is the differentiator. Don't confuse the two.
SurveyGauge and AI-Powered Customer Intelligence
We're building the next generation of our platform: an AI-powered Customer Intelligence Platform that:
- Predicts churn by identifying at-risk customers before they leave
- Automatically prioritises follow-up based on business value
- Classifies feedback with AI-powered sentiment and topic analysis
- Recommends actions grounded in your adviser's expertise
All built on SurveyGauge's three pillars: Platform, Administration, and Advisory. AI without expertise is just data. Expertise without AI is just slow. We deliver both.
Source: KPMG Global Customer Experience Excellence 2025-2026, "Total Experience: Redefining excellence in the age of agentic AI"
Frequently Asked Questions
Agentic AI systems can independently sense context, reason about options, and take action - without waiting for human instructions. For CX, this means AI can coordinate a customer's journey across teams and channels in real time. Moreover, it can even interact directly with customers, answering questions and completing transactions. Ultimately, the shift from rule-following AI to autonomous AI is what makes anticipatory experiences possible.
No, and the data shows the opposite trend. Specifically, KPMG's report finds that Empathy is the fastest-growing pillar - up 4% in Australia alone. The companies outperforming on CX use AI to handle routine work so their people can invest in deeper relationships. AI without human judgement is fast but tone-deaf. In short, the winners combine both.
You're not too late, but you're behind if you lack the foundation. After all, AI requires clean, structured customer data. Only 25% of banks have enterprise-wide infrastructure for data-driven services. The majority are still wrestling with silos and legacy systems. Therefore, start with systematic feedback collection and data integration. That's the prerequisite AI needs.
Skipping the data foundation. Organisations invest in AI tools without first ensuring they have clean, structured customer data flowing across systems. AI without data is blind. In our experience with Nordic B2B companies, the ones who get results invest 70% of their effort in data infrastructure. They put only 30% into the AI layer - not the other way around.
Ready to know what your customers actually think?
SurveyGauge helps Nordic B2B companies move from gut feeling to data-driven CX decisions.
SurveyGauge Team
Customer Experience Experts
SurveyGauge-teamet hjælper virksomheder med at måle og forbedre kundetilfredshed via professionelle surveys, analyser og rådgivning.
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