# Infobip Releases India Digital CX Report 2026 > Source: > Published: 2026-07-01 09:35:15+00:00 Practitioners building AI-driven CX should treat the shift described in Infobip's report as an operational signal, not a product claim. High channel adoption without orchestration and data unification creates brittle production surfaces for agentic workflows; teams should prioritise identity resolution, event-stream reliability, and API contracts before moving to autonomous journey orchestration. ### What happened Infobip published the **India Digital CX Report 2026**, distributed via The Hindu and available from Infobip's website, documenting how Indian enterprises are evolving CX stacks toward integrated platforms that combine customer data, AI, automation, and journey orchestration (Infobip report, The Hindu press distribution). ANI's coverage of the release quotes topline adoption metrics: **91%** WhatsApp adoption in India and Indonesia, **60%** in-app messaging usage, and **18%** RCS adoption (ANI). The report and press coverage also cite global topline figures: **96%** of brands automate some customer interactions, **60%** have centralized customer data, **58%** say channels are fully in sync, **27%** use an orchestration platform, and **50%** describe their tools as API-ready (Infobip materials; ANI reporting). ### Technical context Observed patterns in comparable enterprise CX programmes show the gap between channel adoption and orchestration is the main limiter for operationalising AI. The numbers cited in the report - notably **27%** using orchestration platforms and **50%** API-ready - match a recurring industry pattern where fragmented toolchains and incomplete identity graphs block reliable model-driven automation. For practitioners: reliable agentic or autonomous workflows require consistent event semantics across channels, robust identity resolution, and idempotent APIs that let orchestration engines retry or compensate without creating duplicate actions. ### Platform and product notes The report highlights AgentOS (Infobip) as an example of a platform that unifies customer data, journey orchestration, and embedded AI; this is presented in the downloadable report materials (Infobip report). The press distribution also lists recent vendor recognitions for Infobip, including Gartner Magic Quadrant leadership and other industry rankings (The Hindu press distribution). ### Context and significance The Indian market's high channel adoption, especially WhatsApp, creates opportunity and complexity. High adoption of conversational channels increases the surface area for automation but also raises governance and privacy needs. The report emphasises data protection and compliance as business-critical in India, framing built-in governance as a differentiator for orchestration platforms (Infobip report). ### What to watch Track three indicators: platform-level orchestration adoption (growth from the reported **27%** baseline), improvements in API readiness and contract maturity (relative to the cited **50%**), and investments in centralized customer data or conversational CDPs, which the report identifies as gaining traction. The report is a vendor-released market study; independent verification of enterprise deployments is not supplied in press materials. ## Key Points - 1High channel adoption (WhatsApp **91%** in India/Indonesia) creates scale opportunities but increases orchestration complexity. - 2Only **27%** of brands use orchestration platforms, indicating a common industry bottleneck before agentic CX can scale. - 3Practitioners should prioritise identity resolution and API contract stability to operationalise agentic workflows reliably. ## Scoring Rationale This is a vendor-released market study distributed via press wire. The adoption metrics are self-reported and without independent verification. The score reflects practical relevance for CX/ML teams tracking orchestration maturity in APAC, but the vendor-PR nature and absence of independent data cap the impact ceiling. Practice interview problems based on real data 1,625 SQL & Python problems across 15 industry datasets — the exact type of data you work with. [Try 250 free problems](/problems)