In 2025, the enterprise technology landscape has been reshaped by the rise of agentic AI. Hyperscalers like Oracle, AWS, Microsoft, and Google Cloud have all made decisive moves to pivot from simple LLM-powered features to full-fledged autonomous software agents capable of handling complex business tasks.
Agent marketplaces, agent builders, orchestration layers, and “digital teammates” have become the new battleground. If every major cloud vendor now offers similar tooling, the obvious question is where the real moat lies.
Oracle believes it holds an answer and an advantage that others will find difficult to replicate. The company notes that where an agent lives matters as much as what it can do.
This became clear at its AI World 2025 conference in Las Vegas in October, where Natalia Rachelson, senior vice president of Fusion Applications Product Management division, articulated the company’s strategic shift.
While competitors race to build open agent ecosystems, Oracle has quietly turned its Fusion Applications suite into an engine of 600 embedded agents, treated as enterprise software rather than just automation tools.
At the event, Oracle expanded its AI Agent Studio for Fusion Applications and launched the Fusion Applications AI Agent Marketplace, a catalogue of pre-built, enterprise-grade agents that live inside Fusion ERP, SCM, HR, CX and other Oracle applications.
Unlike the horizontal agents marketplaces emerging across the industry, Oracle’s is purpose-built for the workflows and business objects of Fusion Applications. It stands in stark contrast to the infrastructural strategies of AWS, Microsoft and Google Cloud.
Rachelson, in an exclusive interaction with AIM, explained the rationale and said, “We’re treating every AI agent as a piece of enterprise software. It has to follow the same security rules, the same access control, the same auditing as anything else in Fusion.”
Behind that sits a network of over 32,000 certified agent builders, steeped in the specifics of Fusion’s data structures and workflows.
The Hyperscaler Race
In the weeks following Oracle’s announcement, AWS, Microsoft and Google all intensified their agentic AI narratives. At AWS re:Invent this month, CEO Matt Garman outlined a future driven not by LLM outputs but by “billions of agents” performing real operational tasks inside enterprises.
AWS Marketplace, which had originally targeted 50 agent listings at launch, quietly crossed 800 and surged beyond 2,100 before re:Invent even began.
AWS is now talking in terms of “frontier agents,” anchored by Amazon Bedrock AgentCore, a platform designed to construct, constrain, evaluate, and provide long-term memory for production-grade agents.
AWS also introduced three flagship frontier agents: Kiro Autonomous Agent, a virtual developer that maintains persistent context across sessions, learns your coding style, repositories, and review patterns, and can work for hours or days before surfacing changes; AWS Security Agent, an embedded security consultant; and AWS DevOps Agent, effectively an autonomous SRE already achieving nearly 86% root-cause identification inside AWS and collapsing mean time to repair (MTTR) from hours to minutes.
Check out AWS re:Invent coverage on Front Page by AIM Network:
At Ignite 2025, Microsoft reinforced this momentum by declaring that agents are “the apps of the AI era.” Its new Agent 365 control plane sits atop the Microsoft 365 and Dynamics ecosystems, designed to manage more than a billion enterprise agents by the end of the decade.
Microsoft, once dominant in enterprise software via Windows and Office, now aims to do so with managed, policy-aware digital workers.
Google Cloud, meanwhile, has taken a more interoperability-first approach. At the Cloud Next event, it introduced the Agent2Agent protocol, enabling agents from different vendors to collaborate across platforms such as SAP, ServiceNow, Box, and Vertex. Google’s marketplace is being built not merely to host agents but to allow them to discover and talk to one another through open standards.
Every hyperscaler now has some version of the same pitch: an agent marketplace, a builder studio, and an orchestration layer that promises to turn LLMs into “digital employees” inside your business.
Each major cloud provider now offers a similar comprehensive suite: a marketplace for agents, a dedicated builder studio, and a robust orchestration layer. This stack is designed to transform large language models (LLMs) into functioning “digital employees” within an enterprise.
The Real Deal
Rather than competing to host the most extensive inventory of general-purpose agents, Oracle is optimising for depth, governance, and domain specificity.
The company states that it is focusing on a more specific, yet more profound goal: developing application-embedded agents for mission-critical enterprise workflows.
AWS is developing a large-scale partner-led agent ecosystem on Amazon Bedrock AgentCore and AWS Marketplace, allowing users to subscribe to agents in the same manner as SaaS services. Its “AI Factories” and AgentCore runtimes focus on infra maturity, long-running workflows, and global procurement.
Microsoft is turning agents into the default way work happens across Microsoft 365 and Dynamics. With Work IQ and Agent 365, its focus is on managing agents as “digital teammates” across productivity apps, security tools, and business systems, all tied to a single control panel.
Google Cloud is betting on orchestration and interoperability. Vertex AI Agent Builder, AgentSpace, and the Agent2Agent protocol aim to make it easy to build multi-agent systems, let agents from different vendors work together over an open protocol, and then surface those agents through an AI Agent Marketplace.
All three are building broad, horizontal ecosystems.
Agents as Enterprise Software
Gartner recently warned that over 40% of agentic AI projects will be scrapped by 2027 because many are simply rebranded chatbots without robust governance, security, or clear RoI.
Rachelson’s answer to that risk is to treat agents less like fancy prompts and more like SAP-era enterprise software.
In Oracle AI Agent Studio, the company claimed that every agent is fully traceable, monitored in production, evaluated systematically, and bound to Fusion’s security and role-based access control.
The company said it is adding support for the Model Context Protocol (MCP) and Agent-to-Agent (A2A) cards, so Fusion agents can securely interact with third-party tools and even other vendors’ agents, while still preserving governance and guardrails.
Where some marketplaces offer agents as APIs, Oracle is pushing agents as governed enterprise systems.
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