From Hype to Infrastructure — AI Agents Are No Longer Optional
If we had to answer which AI technology enterprises worldwide are most likely to adopt in real operations in 2026, the answer is becoming clearer every day: AI Agents — AI systems that do more than answer questions. They can think, plan, and execute tasks across systems on their own, without waiting for instructions at every step.
A March 6, 2026 report from Robotics and Automation News brings together signals from multiple directions that reinforce this picture — from Gartner’s forecasts to proven results from ServiceNow and the major partnership between Snowflake and Anthropic.
Gartner: From 5% to 40% in One Year
The most striking figure right now comes from Gartner, which predicts that by the end of 2026, 40% of enterprise applications will embed AI agents into business workflows — up from less than 5% in 2025.
A jump from 5% to 40% in a single year is highly unusual in the technology industry. If this forecast is even close to reality, it means organizations that have not yet started thinking seriously about AI agents are falling behind the trend at speed.
A major force behind this acceleration is that leading software vendors are embedding AI agents directly into products enterprises already use — whether CRM, ERP, ITSM, or communication platforms. In other words, organizations will "receive" AI agents automatically simply by continuing to use their existing software stack.
ServiceNow "Autonomous Workforce" — Metrics That Validate the Concept
The clearest proof point so far comes from ServiceNow, the leader in IT Service Management, which launched "Autonomous Workforce" in early 2026.
The reported results are highly impressive:
- More than 90% of IT support requests are resolved automatically without human involvement
- 99% faster than employee-led resolution
- The system can diagnose issues, identify solutions, and execute remediation end to end
Consider this: if your IT helpdesk receives 500 tickets per day and 90% are handled automatically, that means your IT team no longer needs to touch 450 of them — and can instead focus on the 50 cases that are truly complex and require human judgment.
This is not a lab experiment. It is a system already operating inside real organizations today.
Snowflake + Anthropic: $200M for Agentic AI in the Data World
Another closely watched development is the partnership between Snowflake, the global data platform, and Anthropic, the developer of Claude AI, backed by a $200 million investment.
The goal of this collaboration is to develop Agentic AI for enterprise data workflows — building AI agents that can work with enterprise-scale data, from analysis to taking action directly on databases, without requiring analysts to be involved in every step.
What makes this deal important is not just the dollar amount, but the signal behind it: data and AI are becoming one and the same. Snowflake sees the future of the data platform as one where AI works directly on data — not merely helps write queries.
For organizations that already keep their data in Snowflake, this partnership means Claude AI will soon be able to "read and work with" that business data directly.
Enterprise Connect 2026 — The Stage Where Major Vendors Show What Works
From March 10-12, 2026, Enterprise Connect 2026 in Orlando, Florida will become one of the most important stages for showcasing enterprise Agentic AI progress.
Zoom, Amazon Connect, and RingCentral are all preparing demos of Agentic AI systems for customer experience and enterprise communications — AI that does more than transcribe meetings, acting instead as an agent that can manage follow-ups, summarize outcomes, and carry work forward autonomously.
A notable signal is that all of them are shifting to the term "agentic" instead of "generative." That suggests the industry has moved beyond the chatbot era and is now advancing toward AI that can actually perform work.
The "Prove It or Cancel It" Era — A Healthy Pressure for the Industry
Amid the excitement, many experts point out that enterprise AI is now entering its most critical phase — the period known as "Prove It or Cancel It."
After 2024-2025, when many organizations broadly piloted AI initiatives, the time has come to demonstrate real results — or shut projects down. Gartner’s estimate that more than 40% of Agentic AI projects may be canceled before the end of 2027 reflects this reality clearly.
The main reasons for failure include:
- No clear success metrics from the start — organizations launched AI projects out of fear of missing the trend, not because they had a real use case
- Lack of governance — AI operates without a system to review what it did or what decisions it made
- Compute costs rising faster than expected — API and infrastructure costs escalate before ROI is proven
But for organizations that choose the right use case and can measure outcomes, the "Prove It" phase is a major opportunity — because it provides the hard numbers needed to justify investment and scale with confidence.
What This Means for Thai Enterprises in 2026
These figures and case studies are not distant or abstract for organizations in Thailand. Many of the software platforms already used by Thai enterprises — whether ServiceNow, Microsoft 365, Salesforce, or Google Workspace — are embedding AI agents into their quarterly updates.
The real risk is no longer deciding whether to use AI agents, but whether to use them with a plan. Organizations that adopt them without a governance plan risk data security issues, decisions that cannot be audited, and costs that spiral out of control.
What enterprises should prepare now:
- Assess AI readiness — understand how prepared the organization’s data is, what skills the team has, and which use cases are most likely to deliver value first
- Choose a measurable first use case — not the one that sounds the most impressive, but the one that solves a real problem with a clear baseline
- Establish governance from day one — define what AI is allowed to do, who reviews it, and what the escalation path should be
Enersys’ Genesis AI Platform is designed specifically to address these challenges — with a governance-first architecture where every agent action has an audit trail, every decision has explainability, and the platform connects directly to the ERP and CRM systems enterprises already use. This reduces risk at exactly the points where most AI projects fail.
Conclusion: It’s Time to Move Beyond Observation Mode
2025 was an appropriate year for observation and experimentation. But 2026 is the year that demands real results. Gartner’s forecast, ServiceNow’s case study, and the Snowflake-Anthropic deal all send a clear message: AI agents are becoming standard infrastructure, not a special competitive advantage anymore.
For Thai executives, the key question now is no longer "Should we use AI agents?" but rather, "How do we get started the right way?"
Start with the AI Readiness Assessment to see how prepared your organization is, or contact the Enersys team to build an AI strategy tailored to your business context.
Source: Robotics and Automation News | Gartner: AI Agents in Enterprise Apps | ServiceNow Autonomous Workforce | Snowflake x Anthropic Partnership
