Presented by Oracle NetSuite
When any company tells you it’s their biggest product release in almost three many years, it’s value listening. When the person saying it founded the world’s first cloud computing company, it’s time to take note.
At SuiteWorld 2025, Evan Goldberg, founder and EVP of Oracle NetSuite, did just that when he called NetSuite Next the corporate’s biggest product evolution in nearly three many years. But behind that sweeping vision lies a quieter shift — one centered on how AI behaves, not only what it might do.
“Every company is experimenting with AI,” says Brian Chess, SVP of Technology and AI at NetSuite. “Some ideas hit the mark, and a few don’t, but each teaches us something. That’s how innovation works.”
For Chess and Gary Wiessinger, SVP of Application Development at NetSuite, the challenge lies in governing AI responsibly. Relatively than reinventing its system, NetSuite is extending the identical principles into the AI era which have guided its strategy for 27 years — security, control, and auditability. The goal is to make AI actions traceable, permissions enforceable, and outcomes auditable.
The philosophy underpins what Chess calls a “glass-box” approach to enterprise AI, where decisions are visible and each agent operates inside human-defined guardrails.
Built on Oracle’s foundation
NetSuite Next is the results of five years of development. It’s built on Oracle Cloud Infrastructure (OCI), which is relied on by most of the world’s most vital AI model providers, and has AI capabilities integrated directly into its core slightly than added as a separate layer.
“We’re constructing a improbable foundation on OCI,” Chess says. “That infrastructure provides greater than compute power.”
Built on the identical OCI foundation that powers NetSuite today, NetSuite Next gives customers access to Oracle’s latest AI innovations together with the performance, scalability, and security of OCI’s enterprise-grade platform.
Wiessinger emphasizes the team's approach as “needs first, technology second.”
“We don’t take a technology-first approach,” he says. “We take a customer-needs-first approach after which work out find out how to use the newest technology to resolve those needs higher.”
That philosophy extends across Oracle’s ecosystem. NetSuite’s collaboration with Oracle’s AI Database, Fusion Applications, Analytics, and Cloud Infrastructure teams helps NetSuite deliver capabilities that independent vendors can’t match, he says — an AI system that’s each open to innovation and grounded in Oracle’s security and scale.
The information structure advantage
At the center of the platform is a structured data model that serves as a critical advantage.
“One among the nice things about NetSuite is, because the information is available in and it gets structured, the connections between the information are explicit,” Chess explains. “Meaning the AI can start exploring that knowledge graph that the corporate has been increase.”
Where general LLMs sift through unstructured text, NetSuite’s AI works from structured data, identifying precise links between transactions, accounts, and workflows to deliver context-aware insights.
Wiessinger adds, “The information we’ve got spans financials, CRM, commerce, and HR. We will do more for purchasers because we see more of their business in a single place.”
Combined with built-in business logic and metadata, that scope allows NetSuite to generate recommendations and insights which are accurate and explainable.
Oracle’s Redwood design system provides the visual layer for this data intelligence, creating what Goldberg described as a "modern, clean and intuitive" workspace where AI and humans collaborate naturally.
Designing for accountability
One downside of enterprise AI is that many systems still function as a black box — they produce results but offer little visibility into how they reached them. NetSuite is different. It’s designing its systems around transparency, making visibility a defining feature.
“When users can see how AI reached a call — tracing the trail from A to B — they don’t just confirm accuracy,” Chess says. “They learn the way the AI knew to do this.”
That visibility turns AI right into a learning engine. As Chess puts it, transparency becomes a “improbable teacher,” helping organizations understand, improve, and trust automation over time.
But Chess cautions against blind trust: “What’s disturbing is when someone presents something to me and says, ‘Look what AI gave me,’ as if that makes it authoritative. People must ask, ‘What grounded this? Why is it correct?’”
NetSuite’s answer is traceability. When someone asks, “Where did this number come from?” the system can show them the complete reasoning behind it.
Governance by design
AI agents inside NetSuite Next follow the identical governance model as employees: roles, permissions, and escalation rules. Role-based security embedded directly into workflows helps be certain that agents act only inside authorized boundaries.
Wiessinger puts it plainly: “If AI generates a narrative summary of a report and it’s 80% of what the user would have written, that’s superb. We’ll learn from their feedback and make it even higher. But booking to the final ledger is different. That must be 100% correct and is where controls and human review really matter.”
Auditing the algorithm
Auditing has all the time been a part of ERP’s DNA, and NetSuite now extends that discipline to AI. Every agent motion, workflow adjustment, and model-generated code snippet is recorded inside the system’s existing audit framework.
As Chess explains, “It’s the identical audit trail you may use to work out what the humans did. Code is auditable. When the LLM creates code and something happens within the system, we are able to trace back.”
That traceability transforms AI from a black box right into a glass box. When an algorithm accelerates a payment or flags an anomaly, teams can see exactly which inputs and logic produced the choice — a necessary safeguard for regulated industries and finance teams.
Protected extensibility
The opposite half of trust is freedom — the flexibility to increase AI without risking data exposure.
The NetSuite AI Connector Service and SuiteCloud Platform make that possible. Through standards just like the Model Context Protocol (MCP), customers can connect external language models while keeping sensitive data secure inside Oracle’s environment.
“Businesses are hungry for AI,” Chess says. “They need to start out putting it to work. But in addition they need to know those experiments can’t go off the rails. The NetSuite AI Connector Service and governance model give partners the liberty to innovate while maintaining the identical audit and permission logic that govern native features.”
Culture, experimentation, and guardrails
Governance frameworks only work if people use them correctly. Each executives see AI adoption as a top-down and bottom-up process.
“The board is telling the CEO they need an AI strategy,” Chess says. “Meanwhile, employees are already using AI. If I were a CEO, I’d start by asking: what are you already doing, and what’s working?”
Wiessinger agrees that balance is essential: “Some firms go all-in on a centralized AI team while others let everyone experiment freely. Neither works by itself. You wish structure for major initiatives and freedom for grassroots innovation.”
He offers an easy example: “Write an email? Go crazy. Touch financials or worker data? Don’t go crazy with that.”
Experimentation, each emphasize, is imperative. “Nobody should wait for us or anyone else,” Wiessinger says. “Start testing, learn quickly, and be intentional about making it work for your corporation.”
Why transparent AI wins
As AI moves deeper into enterprise operations, governance will define competitive advantage as much as innovation. NetSuite’s approach — extending its heritage of ERP controls into the age of autonomous systems, built on Oracle’s secure cloud infrastructure and structured-data foundation — positions it to guide in each.
In a world of opaque models and dangerous guarantees, the businesses that win won’t just construct smarter AI. They’ll construct AI you may trust.
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