OpenText World 2025: A practical path to secure, contextual AI at enterprise scale
OpenText introduced the AI Data Platform (AIDP), a framework built to connect data management with agent-based automation under strong governance. The pitch is simple: AI that runs on audited, contextual enterprise data will be more accurate, more compliant, and easier to scale.
The timing matters. As enterprise data multiplies, accuracy, risk, and ROI are under scrutiny. According to McKinsey's State of AI study, 51% of organizations using AI have experienced at least one negative consequence or inaccuracy - a clear signal that governance and context can't be optional (source).
Why leadership should care
AI without context is guesswork. OpenText's stance: start with governed content, metadata, identity, and access - then layer in AI agents. That approach can reduce error rates, simplify audits, and keep your teams aligned with compliance requirements.
It's also flexible. The platform is built to work across clouds, models, and enterprise apps you already own.
What's new from OpenText
- OpenText AI Data Platform (AIDP): An open, unified data and AI framework with a governance orchestration layer so agents operate on trusted, policy-aware data.
- Context-first foundation: Automated metadata tagging, lineage, data rights, retention, and identity/access control wrap your content - documents, trade data, IT tickets, and security signals.
- OpenText Aviator (agentic AI): Automates workflows with three core standards:
- Multi-cloud: on-prem, cloud, or hybrid
- Multi-model: any model (LLM/SLM), including bring-your-own
- Multi-application: deep integration with ERP, CRM, and more
- Aviator Studio: No-code tools to build, govern, and connect enterprise AI agents to accelerate time-to-value.
- Knowledge Discovery: Ingests structured/unstructured data, automates tagging, and connects to live sources.
- Data Compliance: AI readiness, redaction and PII controls, tokenization, encryption, privacy protections, threat detection and response.
- Aviator AI Services: Professional Services to move from discovery to deployment to adoption.
Ecosystem and integrations
OpenText is working across the enterprise stack (SAP, Microsoft, Google, Salesforce, Oracle, and others) to enable agent-to-agent workflows and industry-specific use cases. The company also announced an expanded partnership with Databricks to co-innovate on AIDP through technical integrations and Delta Sharing - unifying, governing, and analyzing data to produce trusted AI outputs.
Availability and cost notes
- Aviator entry tier is included with an upgrade to OT 26.1 for Content Management, Service Management, and Communications Management at no additional fee.
- On-prem support starting OT 26.1 for Content Management, Communications Management, Service Management, DevOps Management, and Application Security.
- Data sovereignty: OpenText will work with customers on region-specific requirements.
Use cases you can deploy now
- Fraud detection in high-volume environments
- Claims management with auditable reasoning
- Predictive maintenance across complex operations
What this means for executives
AI performance hinges on context. If your data isn't governed and your workflows aren't integrated, you'll see hallucinations, rework, and risk. The AIDP approach prioritizes accuracy and accountability so you can scale automation without losing control.
Questions to ask your team this week
- Do we have a complete inventory of the data sources agents will touch, including lineage and retention policies?
- What guardrails are in place for PII, encryption, and data residency?
- Which business processes are ready for agent automation, and what metrics define "good" (accuracy, handle time, auditability, cost)?
- What's our model strategy (vendor choice, BYO models, evaluation) and how do we swap models without rework?
- How will agents connect to ERP/CRM and other core platforms with least friction?
A 90-day rollout plan (pragmatic and measurable)
- Days 0-30: Data readiness audit; identify 2 high-impact, low-risk workflows. Define KPIs (accuracy, cycle time, compliance flags, per-transaction cost).
- Days 31-60: Pilot with Aviator on governed datasets via AIDP. Include human-in-the-loop review and audit trails. Document model choices and prompts.
- Days 61-90: Expand to a second department. Automate reporting for compliance and business outcomes. Lock in runbooks and change management.
Bottom line
OpenText is placing a clear bet: AI agents should be built on governed, contextual enterprise data - not guesswork. For leaders, that translates into fewer errors, faster audits, and automation that respects policies while delivering outcomes.
Learn more at opentext.com. For the broader market context, see McKinsey's State of AI study here.
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