Observed Signal · May 12, 2026 · Research Report · Source: https://martechseries.com/feed/ · Impact: 2/5 · Sentiment: Neutral
Infobip Report: Disconnected Data Hinders CX Automation
Infobip's 2026 Customer Experience (CX) Maturity Report finds that while most brands (96%) automate some customer interactions, fragmentation across data and systems prevents scalable, seamless customer journeys and slows AI adoption. The report shows only 58% of brands have fully synchronized channels, 60% centralize customer data, 27% use an orchestration platform, and 50% report tools are fully API-ready. Agentic AI is used by 53% of brands but adoption is limited by user trust (71%), data privacy concerns (64%) and tech-stack integration (41%). Sector analysis ranks retail and telecommunications highest on journey automation and system potential, with banking trailing slightly. Infobip and industry commentator Frost & Sullivan highlight that overcoming fragmented systems and trust barriers will determine which brands scale effective AI-powered CX.
Report highlights widespread martech fragmentation and specific barriers to scaling AI-driven CX—important for brands and MarTech/CDP vendors but not an industry-shifting platform or regulatory event.
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Key Takeaways & Evidence Grounding
- Infobip published the 2026 Customer Experience (CX) Maturity Report.
- 96% of brands automate customer interactions in some way; only 58% say channels are fully in sync.
- 60% of brands have centralized customer data; 27% use an orchestration platform; 50% say tools are fully API-ready.
- 53% of brands report using agentic AI in customer journeys; primary barriers to deeper AI deployment are user trust (71%), data privacy (64%), and tech-stack integration (41%).
- Sector CX scores: retail and telecommunications lead journey automation (32/100) and system potential (59/100); banking scores 30/100 for automation and 56/100 for system potential.
Connected Companies & Entities
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Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
AI Turns Fragmented Data into Better Customer Experience
The article argues that fragmented data and siloed systems, not lack of effort, are the main reasons customer experiences fall short of expectations. Based on a global survey of 2,000 consumers and 750 senior decision-makers, it reports that only 27% of German enterprises (≥500 employees) recognise their CX is not fully connected, and that more than half of German companies lack real-time access to relevant customer data and interaction signals. The piece presents AI — including AI agents — as a way to analyse live signals, prepare decisions, and orchestrate interactions across systems, describing a shift toward an "Autonomous Enterprise" where humans set goals and AI coordinates execution. It warns that AI exposes weak data foundations and that organisational change (integrated data, processes and responsibilities) is required for AI to deliver consistent, relevant CX.
Brands Overestimate CX Improvements, Consumers Disagree
Medallia Inc. published its 2026 State of Customer Experience Report based on surveys of more than 1,500 consumers, 550+ global CX practitioners, and benchmarks from over 600 anonymized Medallia customer programs. The report finds a widening perception gap: 66% of CX practitioners believe experiences improved last year, while only 17% of consumers agree. It highlights growing AI adoption in CX—over 80% of practitioners report positive returns and 81% say their organizations have clear, measurable AI goals—alongside organizational friction: 30–40% of departments take no action on received customer insights. The report signals a shift toward signal-based strategies and broader data sources (e.g., conversational intelligence paired with digital behavior analytics), with many practitioners planning new metrics in 2026 and most CX leaders expecting higher budgets.
AI adoption hits 90% in CX, deployment paths diverge
Five9’s “2026 Business Leaders CX Report” finds 90% of customer experience (CX) organizations are piloting or deploying AI, but there is no consensus on governance or deployment architecture. Respondents are split among end-to-end platforms, hybrid setups, and best-of-breed solutions. Infrastructure trends favor flexibility: 84% are transitioning from on-premises to cloud and 74% operate hybrid customer care environments (16% fully cloud, 10% fully on-premises). Data security is the top implementation concern (31%), followed by reliability, scalability, and customer consent (27%). Early AI deployments focus on operational efficiency—self-service automation (42%), quality management (41%), and speech/text analytics (40%)—while customer-facing use cases like knowledge authoring (30%), journey analytics (28%), and personalization (26%) lag. Roughly nine in 10 respondents report positive ROI across AI use cases, shifting the conversation toward operational execution, governance, and trust.
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