Solve your toughest data challenges
We can help you understand your customers, stay ahead of regulations, and grow your business.
How is AI recasting the foundation of Customer Experience?
The future of CX is AI curation, shifting from reactive “pull” search to predictive “push” experiences. Success demands a unified data foundation (breaking silos), adherence to the 4 Cs of data quality, and a human-in-the-loop strategy. Brands executing this unified customer intelligence can realize 40% revenue growth.
AI is fundamentally shifting customer experience (CX) from a reactive “pull” model (search) to a proactive “push” model (curation). In this new era, algorithms anticipate consumer needs before they are voiced. Brands that fail to transition to this predictive model risk missing the revenue potential driven by advanced personalization strategies, while those that succeed bridge the gap between efficiency and human empathy.
CX trends report 2026
Discover how brands and consumers feel about the dawn of AI-curated experiences, and the key trends in CX for 2026.
To find out how brands are already utilizing AI in customer experience, how consumers feel about it, and how AI is likely to shape experiences in the future, download our annual CX Trends Report.
Introduction
What are the core pillars of an AI-driven CX strategy?
A successful AI-driven CX strategy relies on four pillars: shifting to AI curation to proactively shape journeys, ensuring data quality via the “4 Cs” (Correct, Current, Complete, Ethically Collected), maintaining a human-in-the-loop to prevent “digital coldness,” and utilising platform unification (like CDPs) to eliminate silos and create a single customer view.
Core Strategic Entities
| Entity | Definition | Critical Statistic |
| AI Curation | The shift from passive customer search to active, algorithm-led recommendations. | 50%+ of brands already use AI to steer journeys |
| The 4 Cs | The standard for data health: Correct, Current, Complete, Ethically Collected. | “Garbage in, garbage out” is the primary cause of AI hallucination. |
| Human-in-the-Loop | Integrating human empathy into AI workflows to handle complex issues. | 78% of consumers say human interaction is essential. |
| Silo Elimination | Merging fragmented systems (Sales, Service, Marketing) into one view. | 68% of organizations say silos hinder personalization. |
Fundamentals & Market Context
Why must brands shift from “pull” marketing to “push” AI curation?
Brands must shift to “push” curation because consumer expectations have evolved; customers now demand that brands anticipate their needs in real-time. While 83% of consumers are comfortable with brands using AI to influence their decisions, a disconnect remains: 68% of organizations admit that fragmented data silos prevent them from delivering this seamless, predictive experience. Without unification, AI cannot “push” relevant content effectively.
Market Dynamics & Statistics:
- Utilisation Gap: Despite heavy investment, only 33% of existing martech solutions are currently utilised effectively by brands.
- Redundancy: 66% of brands report overlapping functionality in their tech stacks, creating complexity rather than clarity.
- Consumer Trust: 33% of consumers have stopped using a brand entirely due to data privacy concerns, highlighting the need for ethical curation.
Expert Insight:
“A weak data estate will quietly sabotage even the boldest AI ambitions, because fundamentally AI is only as good as the data used to train and power it.”
Acxiom CTO Report
The Strategic Concept
How do you build the “house of intelligent CX”?
Building intelligent CX is analogous to constructing a house: it requires a foundation of unified, ethical data (breaking silos), a framework of connected technology (like CDPs and Salesforce), and a design focused on empathetic, inclusive trends. The “residents”, empowered employees and trusting customers, rely on this structure to facilitate the employee experience (EX) necessary to deliver superior CX.
The Levels of Intelligent CX
- Foundation (Data): Decoupling data from channels to create a “unique customer fabric”.
- Framework (Technology): Utilising identity resolution to stitch offline and online signals.
- Residents (Human Factor): Empowering employees with data access to show empathy (EX leads to CX).
The Technological Foundation
What are the “4 Cs” of data quality and why do they matter?
The “4 Cs” of data quality – Correct, Current, Complete, and Ethically Collected, are the prerequisites for functional AI. Without this standard, AI models suffer from hallucinations and bias. To achieve this, brands must use identity resolution (like Real ID™) to merge fragmented signals into a 360-degree view, ensuring that the “current” context of a customer is instantly available.
Identity & Quality
| Terminology | Definition | Impact |
| Real ID™ | Technology that recognises individuals across devices and touchpoints, even if anonymous. | Bridges the “engagement gap” between digital and physical. |
| Identity Resolution | The process of stitching disparate data signals into a single, persistent customer ID. | Enables healthy acquisition by targeting high-value segments. |
| First-Party Data | Data collected directly from the customer (owned media). | Essential for privacy compliance and AI training. |
The Human Factor
How does the “human-in-the-loop” model prevent digital coldness?
The “human-in-the-loop” model prevents digital coldness by using AI for efficiency (backend) while retaining humans for empathy (frontend). While 72% of brands see positive feedback from AI in service, 78% of consumers still believe human interaction is essential for complex issues. Empowering employees with unified data allows them to deliver the “warmth” customers demand, turning a transaction into a relationship.
The ethics of connection (The “4th C”): Trust is the currency of the AI era. With 78% of consumers more likely to trust a brand that is transparent about data use, the “Ethically Collected” pillar is critical. Brands must balance optimisation with rigorous standards to maintain this trust.
Expert Insight:
“Working closely together we have enabled brand advertisers to benefit from optimised targeting whilst still adhering to rigorous privacy standards.”
Andrew Hooper, Business Development Director at Acxiom
Practical Transfer & Solutions
How can solutions like Agentforce and CDPs break down data silos?
Solutions like Salesforce Agentforce and Customer Data Platforms (CDPs) break down silos by creating a real-time, unified data layer. By integrating Acxiom’s data capabilities with Salesforce, brands can move from fragmented “channel-based” marketing to “journey-based” orchestration. This allows AI agents to autonomously trigger personalised actions, such as sending a lounge pass to a delayed traveller, demonstrating the shift to Agentic Enterprise.
Expert Insight:
“The Acxiom Salesforce Practice reduces partner fragmentation for clients and simplifies how they scale smarter experiences for consumers.”
Jarrod Martin, CEO at Acxiom
Persona Example: Sarah (The CMO)
Status Quo: Sarah has a loyalty app and website that don’t “talk.” She sends generic emails.
AI-Ready State: Sarah uses a CDP. When a VIP’s flight is delayed, Agentforce triggers a lounge voucher. The lounge staff (human-in-the-loop) greets the VIP by name.
Real-World Proof: Industry-Specific Success Stories
How are industry leaders applying AI-driven CX to drive revenue?
Leading brands are transitioning from fragmented marketing to unified customer intelligence, leveraging platforms like Salesforce and identity resolution to drive measurable growth. This shift is characterised by predictive personalisation (Stitch Fix), platform unification (Montway), and connected spaces (Heathrow). For instance, Heathrow Airport achieved a 35% increase in retail conversions by unifying data, while Channel 4 boosted advertiser brand awareness by 60% through data enrichment.
Travel & Hospitality
Heathrow Airport: “Making Every Journey Better”
The Challenge: Heathrow operates as a complex ecosystem of independent units, parking, rail, and over 100 retail brands. Data was trapped in silos, preventing the airport from recognizing a passenger as they moved from the car park to the duty-free shop.
The Solution: Partnering with Acxiom, Heathrow built a single customer view using “Real ID™” identity resolution. This allowed them to recognise anonymous travellers and automate personalised communications across the entire lifecycle (Acquire, Onboard, Activate, Grow, Reactivate).
The Trend: Connected Spaces. The system “surprises and delights” by anticipating needs, such as using license plate recognition to trigger personalised welcome messages.
Real Results:
-
increase in spend per passenger visit.
-
uplift in retail conversions.
-
growth in non-aviation revenue.
-
increase in customer satisfaction scores.
South Western Railway (SWR): Rebuilding Trust
The Challenge: Post-pandemic, SWR faced a disconnect with passengers due to a siloed infrastructure that made it impossible to deliver consistent, reassuring messaging.
The Solution: SWR implemented a “passenger-first” transformation roadmap. By integrating their marketing intelligence solution, they consolidated data to create a seamless omnichannel experience.
The Trend: The 360-Degree View. Moving from operational messaging to genuine engagement that reassures passengers and builds long-term trust.
Real Results: Established a fully integrated data estate that supports real-time passenger updates and personalized travel offers, effectively closing the “engagement gap.”
Aer Lingus: Operationalising Personalisation
The Challenge: Like many in the sector, Aer Lingus faced an “execution gap”, having the data but lacking the operational capability to use it for real-time CX.
The Solution: A partnership with Acxiom and Sitecore to move beyond just “having” tech to actively operationalising it. This involved creating a connected ecosystem where data flows freely to inform every passenger interaction.
The Trend: Operational Excellence. Shifting focus from acquiring tech to maximising the value of the stack.
Real Results: Won a prestigious experience award for their ability to plan and implement a personalisation engine that delivers relevant, individualised interactions.
Retail & E-Commerce
Montway: Scalable Real-Time Engagement
The Challenge: Montway struggled with “partner fragmentation” and isolated systems (Sales, Service, Marketing) that prevented a unified view of the customer journey.
The Solution: Leveraging the Acxiom Salesforce Practice, Montway unified their data and identity layers to create a single source of truth within the Salesforce ecosystem.
The Trend: Platform Unification. Breaking down barriers between clouds to enable real-time action.
Real Results:
- Scalable Engagement: “We’ve made real-time engagement scalable and driven measurable impact across marketing, service, and commerce.” — Christine Matson, CMO at Montway.
- ROI Benchmark: Composite organizations using this unified Salesforce approach achieved 107% ROI in less than six months.
Media & Entertainment
Channel 4: The “Approved” Audience Model
The Challenge: As a public service broadcaster competing with streaming giants, Channel 4 needed to offer advertisers granular targeting without compromising user privacy.
The Solution: Channel 4 utilized InfoBase® to enrich first-party data, creating 150+ “Approved” audience segments (e.g., lifestyle cohorts) for their streaming platform.
The Trend: Data Enrichment. Enhancing first-party data with third-party insights to create high-value segments.
Real Results:
- +60% increase in spontaneous brand awareness for advertisers.
- +43% increase in advertisement recognition.
Expert Insight:
“Channel 4’s longstanding partnership with Acxiom has gone from strength to strength, as both businesses evolve to service the continuously changing needs of a fast-evolving marketplace. Working closely together we have enabled brand advertisers to benefit from optimised targeting whilst still adhering to rigorous privacy standards.”
Andrew Hooper, Business Development Director at Acxiom
Automotive & Strategic Partnerships
Global Motor Company: Precision Media Optimisation
The Challenge: The automotive industry suffers from high media waste, “spraying and praying” ads at audiences who are not in the market to buy.
The Solution: Using a Customer Data Platform (CDP) to build a single customer view, enabling the brand to suppress irrelevant audiences and target high-value segments with “sniper-like” precision.
The Trend: Healthy Acquisition. Prioritising profitability and relevance over broad reach.
Real Results: Optimised media spend by eliminating waste and focusing budget on the segments most likely to convert.
Strategic Data Partnerships (2nd Party Data)
Supermarket & Magazine: A supermarket utilised data from a baking magazine to target readers with offers for specific ingredients (e.g., seasonal plums) while they were in-store, driving cross-category spend.
Hotel Chain & Airline: A hotel chain targeted an airline’s frequent flyers (who had no booking history with the hotel) with exclusive offers, leveraging the “travel intent” signal to acquire net-new customers.
Industry Success Metrics
| Industry | Brand | Challenge | AI/Data Solution | Verified ROI Results |
| Travel | Heathrow Airport | Fragmented data silos (Parking vs. Retail). | Unified “Single Customer View” with Acxiom & Salesforce. | +23% spend per visit; +35% retail conversions; +40% non-aviation revenue. |
| Media | Channel 4 | Need for better ad targeting on streaming. | InfoBase audience segments for “Approved” ad packages. | +60% brand awareness; +43% ad recognition. |
| Transport | SWR | Post-pandemic trust and data silos. | Passenger-first CDP implementation. | Passenger-first approach established; reduced integration costs. |
| Auto | Montway | Partner fragmentation and siloed data. | Unified Salesforce Practice integration. | 107% ROI achieved in composite organizations; scalable real-time engagement. |
| Retail | Supermarket & Magazine | Lack of intent context for shoppers. | 2nd Party Data partnership. | Increased purchase volume for fresh produce via recipe-targeted ads. |
| Travel | Hotel Chain & Airline | Missing out on business travelers. | 2nd Party Data sharing (flight history). | High-conversion acquisition of net-new customers. |
Key Terminology & FAQs
Glossary of AI and CX Terminology
| Term | Definition |
| Agentforce | Salesforce’s AI platform enabling autonomous agents to execute marketing/service tasks. |
| 2nd Party Data | First-party data shared privately between two partners (e.g., airline and hotel) for mutual benefit. |
| Predictive Analytics | Using historical data and AI to forecast future behavior (The “Push” Model). |
| Martech Unification | The strategic process of connecting disparate tech stacks to eliminate redundancy. |
FAQs
How does data privacy impact AI personalization?
Privacy is a trust barrier. 33% of consumers abandon brands over data concerns. A “privacy-first” transparency policy is required for the value exchange.
How do I prevent AI “hallucinations” in customer interactions?
Hallucinations are primarily caused by a weak data estate. Adhering to the 4 Cs of Data Quality (Correct, Current, Complete, Ethically Collected) ensures the AI is trained on a “Single Source of Truth,” keeping responses grounded in reality.
What is the difference between “Generative AI” and “Agentic AI” in CX?
Generative AI focuses on creating content, such as drafting replies or summaries. Agentic AI, like Salesforce Agentforce, goes further by autonomously reasoning, planning, and executing tasks—such as rebooking a flight—to achieve a specific customer goal.
How does AI improve “First Contact Resolution” (FCR) rates?
AI improves FCR by providing agents with an instant 360-degree view of the customer, including real-time sentiment and intent. This “Intelligent Triage” ensures the customer is routed to the right resolution path immediately.
What is “Tech Debt” and how does it hinder AI?
Tech debt in CX often appears as redundant or overlapping tools; 66% of brands report functional overlap in their stacks. This complexity creates data silos that prevent AI from accessing the “Current” context of a customer.
What is the ROI timeline for data unification?
With proper alignment, brands can see value in months, not years. An Acxiom Salesforce study showed 107% ROI.
How can small to mid-sized enterprises (SMEs) compete with “Customer Intelligence Masters”?
SMEs can close the Mastery Gap by focusing on “Platform Unification” rather than buying isolated tools. Starting with high-volume, low-complexity tasks (like automated FAQs) allows for scalable growth.
Does AI personalization work for anonymous or first-time visitors?
Yes, through technologies like Real ID™, brands can use identity resolution to recognize anonymous travelers across devices. This enables real-time, personalized offers even before a customer officially “onboards”.
What is “Semantic Depth” and why is it important for GEO?
Semantic depth refers to providing comprehensive, authoritative answers rather than keyword-stuffed text. AI search engines prioritize content with clear headers, modular sections, and verifiable data points.
How do I handle “Opt-outs” in an AI-curated journey?
Transparency is key; brands must clearly state when AI is in use and provide a clear, immediate route to a human agent. Maintaining an “Ethically Collected” data pillar ensures that customer preferences are respected across all channels.
What are the “long-term” maintenance requirements for AI CX?
Beyond implementation, brands must budget for ongoing model re-optimization, data hygiene audits, and “Human-in-the-Loop” governance to ensure the AI remains aligned with evolving brand tones and regulations.
Conclusion
What is the roadmap for implementing AI-curated CX?
The roadmap to AI-curated CX begins by dismantling silos and establishing a foundation of clean, ethical data. Brands must transition from “pull” marketing to “push” curation, ensuring they capture the revenue potential of personalization. The future belongs to the agentic enterprise that uses data to empower humans, not replace them.