May 13, Orlando, Florida, USA. At Sapphire 2026, SAP announced that enterprise AI has moved from "assistance" to the "autonomous execution" stage.
The weight of this announcement only gradually became apparent today (May 22)—because immediately afterward, Google I/O 2026 followed up in the early hours of May 20, upgrading Gemini from a "chat assistant" to an "all-day action agent." The two companies, a week apart, coincidentally shifted AI's role in enterprises from a "tool that helps you do things" to an "agent that directly completes tasks for you."
This is not an isolated move by two companies. It is a signal of the collective shift in the enterprise software industry in 2026.
What exactly does SAP's "autonomous enterprise" mean?
SAP Global CEO Christian Klein said something at the conference that is worth recording in full:
"For customers' critical business processes, 'almost right' is far from sufficient. By combining the SAP Business AI platform with the SAP Autonomous Management Suite, we deeply embed AI agents into business processes, data, and governance systems, ensuring they can deliver accurate, compliant, and secure results."
The key phrases in this sentence are "deep embedding" and "direct execution." What SAP released this time is not a specific AI function, but a complete "Autonomous Enterprise" architecture, consisting of three pillars:
| pillar | Content | Enterprise Value |
|---|---|---|
| Unified AI Platform | SAP Business AI Platform | Build and govern AI agents, providing business context |
| Self-management suite | Execute end-to-end core business processes | AI is no longer just suggesting, but directly executing |
| New User Experience | Joule Work (New Interaction Method) | The user describes the goal, and Joule automatically executes the entire process. |
50 smart assistants + 200 professional agents, what does this mean?
SAP has released over 50 Joule intelligent assistants dedicated to specific business areas, covering finance, supply chain, procurement, HR, and customer experience. Under each assistant, there are over 200 specialized AI agents responsible for specific tasks.
50 + 200, this number sounds like marketing. But there is a specific case to verify whether it is real: Autonomous Close Assistant.
What this assistant does is: autonomously handle journal entries, reconciliations, detect and automatically correct errors throughout the entire financial closing process. The result is—the financial closing cycle is reduced from weeks to days.
This case has customer validation: RWE (European energy giant) is already using SAP's autonomous asset management agent to analyze historical accident data and automatically generate work orders containing tool recommendations and repair plans.
This is not a POC in a demo environment. RWE is a real customer, the offshore wind turbine is a real scenario, and reducing unplanned downtime is real business value.
Noteworthy: SAP also announced that the workload for customers migrating to SAP ERP Cloud can be reduced by more than 35%. This is a direct result of the Agent-Driven Transformation toolset—AI automatically completes system analysis, code fixes, configuration, and testing.
Google I/O 2026: Gemini Transforms from Assistant to "Operating System Layer"
In the early hours of May 20, Google I/O 2026. The timing is exactly one week after SAP Sapphire, and this is no coincidence.
The core of this Google release is: Gemini is no longer an assistant you open a dialog box to ask questions. It has become an AI layer at the Android system level (Gemini Intelligence), and has launched Gemini Spark — a persistent action agent that can run in the background around the clock and continue working even when the computer is turned off.
Let’s take a closer look at a few key releases:
| Product | Core Competencies | Enterprise Significance |
|---|---|---|
| Gemini 3.5 Flash | 4 times faster, costs continue to decline | Economic feasibility of large-scale enterprise deployment |
| Gemini Spark | Background continues to run, works even when the computer is off | AI truly becomes a "digital employee" rather than a "tool" |
| Antigravity 2.0 | AI Programming Platform ($1,000 to Build an Operating System) | Reduce enterprise customization development costs |
| AI Search Agentization | Search changed from "return link" to "directly execute task" | The paradigm shift in enterprise knowledge management |
| $180-190 billion in infrastructure investment | Google's largest AI infrastructure bet in history | Long-term service capability assurance |
The Gemini Spark product is particularly noteworthy. Its core design is: you give Gemini a goal, and it can continuously work in the background without requiring you to stay online. This means the usage pattern of AI shifts from "conversational interaction" to "task delegation."
This is essentially the same direction as SAP's Joule Work: users describe the outcome, and AI autonomously orchestrates the process and executes it.
Microsoft, SAP, Google: The Three Kingdoms Battle for Enterprise AI Control
Looking at the events of the past month together, the strategies of the three parties have become very clear:
Enterprise AI Platform Three Kingdoms (May 2026 Situation)
| Manufacturer | Core Products | Governance Strategy | Differentiation |
|---|---|---|---|
| Microsoft | Agent 365 (Observe/Govern/Secure) | Independent control plane, non-human entity identity management | Deeply integrated with M365, $15/user/month |
| SAP | Business AI Platform + Joule Work | Data governance system embedded in business processes | Deeply cultivate core ERP processes, industry solutions (7 major industries) |
| Gemini Intelligence + Spark + AI Control Center | Embedded into Workspace daily tools (Gmail/Drive/Meet) | System-level integration, Android ecosystem |
The three companies have distinctly different approaches: Microsoft focuses on the "control plane," emphasizing governance; SAP focuses on "business process embedding," emphasizing accuracy and compliance; Google focuses on "system-level integration," emphasizing a seamless experience.
For enterprise customers, this means the choice is not just about "which model to use," but rather "what is your AI governance philosophy": Do you want strict control (Microsoft), deep business integration (SAP), or seamless daily integration (Google)?
Can domestic manufacturers keep up?
Shift the focus back to China. Kingdee held an AI summit on May 20, while Yonyou released its BIP enterprise AI product matrix in March; both are promoting their own AI-native strategies.
But there is a hard gap: SAP's 200+ professional agents are backed by the accounting standards, tax rules, and industry best practices of 142 countries accumulated over the past 40 years. This data moat cannot be caught up with simply by training a large model.
The breakthrough point for domestic manufacturers lies in:
- Industry depth: Kingdee has localized expertise in manufacturing, while Yonyou has it in finance — areas where SAP lacks such accumulation. If the AI-native architecture can solidify this localized knowledge into intelligent agents, it will create differentiated value.
- Price: SAP Joule agents are billed based on usage, which poses a high barrier for small and medium-sized enterprises. If local vendors can reduce the price to one-third of SAP's, they can capture a large portion of the mid-range market.
- Compliance: Once the National AI Agent Evaluation Standards (submitted for review on May 21) are released, local vendors will be faster than SAP in compliance alignment.
This is not a narrative of "domestic substitution," but a real evolution of the market landscape. SAP's advantage in the high-end market (large groups, multinational corporations) will not be shaken in the short term; however, competition in the mid-range market will become very intense in the second half of 2026.
Real advice for enterprise CIOs
First, distinguish between "AI demonstration" and "AI implementation".SAP's closing assistant has RWE verification, Google's Gemini Spark has just been released and no customer cases have been seen yet, and Kingdee's AI-native product has just held its launch conference. The maturity levels of the three are different. The specific question to ask when purchasing is: "Are there any customers in the same industry already running this intelligent agent in a production environment?"
Second, governance is more important than functionality. IDC predicts that by 2028, there will be 1.3 billion intelligent agents in enterprises. Companies without a governance system will have 1.3 billion out-of-control intelligent agents by then. When selecting an AI platform, governance tools (Microsoft's Agent 365, SAP's Business AI Platform governance framework, Google's AI Control Center) must be one of the decision factors.
Third, don't wait for the "perfect moment." The benchmark for 2026 is "whether it can replace a corporate functional department" (as Kai-Fu Lee stated at the AMD Developer Day on May 19). If your AI deployment is still stuck at "improving efficiency" without touching business process restructuring, you are already falling behind.
Things to Watch Next
In the next three months, there are several things worth continuously tracking:
- The official release timeline of the National AI Agent Evaluation Standards (expected June-July) — this will directly impact domestic enterprises' AI procurement standards
- Among SAP RISE/GROW customers, the actual activation rate of the Joule intelligent assistant—currently free for the first year—whether the data is real or fake depends on the activation rate.
- Customer feedback on Kingdee's AI-native product — the summit mentioned that "on-site experience" is available, meaning the product is ready for delivery, and the first batch of customer cases should be released around August.
- Actual adoption rate of Microsoft Agent 365 — GA on May 1, first batch of usage data should be available by August
In 2026, the competition for enterprise AI has shifted from "whose model is stronger" to "whose intelligent agents are actually running business operations." This is a transformation from a technology race to a value race. Those who run fast will eat those who run slow.
