The most persistent obstacle to enterprise agentic AI is not compute power or model capability — it is trusted data. Without reliable, real-time intelligence embedded directly into the workflow layer where AI agents operate, automation stalls at the pilot stage. Experian and ServiceNow (NYSE: NOW) have announced a global multi-year partnership designed to solve that problem directly — natively connecting Experian's Ascend Platform into the ServiceNow AI Platform, enabling autonomous agents to access trusted decisioning and analytics intelligence in real time — without leaving the workflow environment they already run in.
The Trusted Data Problem That Is Blocking Agentic AI at Scale
Industry research cited by the two companies is unambiguous: data limitations are the primary barrier for eight in ten organisations attempting to scale agentic AI beyond initial pilots. The problem is not that enterprises lack interest in autonomous agents — it is that the agents they deploy quickly encounter the boundaries of what they can reliably act on, because the data that would enable confident, automated decisions is either unavailable, outdated, fragmented, or held in systems outside the agent's operational environment.
When an AI agent is asked to handle a vendor onboarding workflow, it can manage routing, approvals, and task sequences — but the moment it needs to assess vendor creditworthiness, verify identity, or evaluate third-party risk in real time, it typically has to pause and wait for a human to step out and consult a separate data system. That gap — between what the agent can orchestrate and what it can know — is where agentic automation stalls. The Experian-ServiceNow partnership is engineered to close exactly that gap.
The Architecture: Ascend Natively Connected to ServiceNow AI Platform
The technical core of the partnership is a native connection between Experian's Ascend Platform and the ServiceNow AI Platform. Rather than requiring organisations to build new AI infrastructure or engineer custom integration layers, Experian's decisioning capabilities become available natively within the ServiceNow workflow environment where enterprise AI agents already operate.
Experian's Ascend Platform brings proprietary data assets, analytics capabilities, and decisioning logic — built across decades of work in credit, identity, fraud, and risk — directly into the agent's operational context. With this access, AI agents can pull real-time risk signals, cross-reference identity data, and surface decisioning outputs as part of the same workflow step that routes approvals or triggers actions — without any human stepping out to consult a separate system. This is qualitatively different from an agent that can only manage process logic while leaving data access to humans.
"We see agentic AI as a fundamental change in how intelligent services are delivered, and this partnership brings together complementary strengths and a shared vision for building them the right way. By connecting our intelligence and decisioning capabilities in Ascend directly into ServiceNow's workflow, businesses can operate with confidence at scale, while extending the impact of our capabilities into new industries and enterprise workflows."— Keith Little, President, Experian Software Solutions
Three Launch Use Cases — and the Commercial Logic Behind Each
The partnership launches with three initial use cases, each targeting a distinct category of high-frequency enterprise workflow where trusted data access is the critical bottleneck:
- →Employee Onboarding — AI agents handling onboarding workflows can now access identity verification, background screening data, and compliance checks in real time as part of the onboarding sequence itself, rather than waiting on manual data lookups that introduce delays and create compliance gaps
- →Third-Party Risk Management — Agents managing vendor and supplier onboarding or monitoring can pull real-time risk signals, credit and financial stability data, and fraud indicators from Experian's data assets as part of the same automated step that routes an approval or flags a review, replacing a process that historically required human analysts to manually query external systems
- →Model Lifecycle Governance — Particularly relevant to financial services and other regulated industries, this use case supports the ongoing monitoring, validation, and governance of AI and analytical models in production — an area where regulators are intensifying their scrutiny and where trusted data lineage is a compliance requirement, not an operational preference
"Unlocking the potential of agentic AI requires a foundation of trusted intelligence. This partnership with Experian means our customers can leverage data-powered decisioning directly within ServiceNow workflows, enabling AI agents to act faster, and more consistently across critical processes."— Rohit Bhargava, SVP Strategy & Corporate Development, ServiceNow