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Shared from Saga · AI signal
Operating modelRelevance · high2026-07-14
Oracle Newsroom / TechRadar Pro·6 min read

Enterprise vendors show what ‘autonomous’ workflows really look like – and their hidden dependency: core systems

TechnologyManufacturingRetailProfessional Services

Oracle announced an AI‑native builder experience for ‘Fusion Agentic Applications’ on July 14, 2026, describing orchestrated teams of specialized agents that can reason, coordinate, and execute actions across Fusion business workflows. Around the same time, reporting on SAP’s ‘autonomous enterprise’ vision highlighted more than 200 specialized agents tied into ERP processes like finance and supply chain, illustrating that credible agentic AI in the enterprise is anchored in deep integration with transaction systems, not just a chat interface.

Why it matters for leaders
As a technology leader, you are competing in a world where “AI features” are increasingly defined by how well they understand and act within business systems like ERP, CRM, and billing. Your first AI MVP will succeed or fail based on how well it sits on top of – or inside – your existing core platforms and data models, not on the sophistication of the language model alone.
Opportunity signal

Use the Oracle and SAP examples as a blueprint to pick one end‑to‑end workflow in your product – for example, quote‑to‑cash or incident resolution – and design an agentic MVP that reads rules and approvals from your own systems and can complete closed‑loop actions safely.

high
Risk signal

If your core systems and data models are fragmented or legacy, attempts to build ‘autonomous’ AI layers on top may stall, turning into expensive proofs of concept that never reach production because they cannot reliably execute or be audited.

medium
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