Presented by Oracle NetSuite
When any company tells you that this is their biggest product release in nearly three decades, it’s worth listening to. When this man founded the world’s first cloud computing company by saying, it’s time to take notice.
At SuiteWorld 2025, Evan Goldberg, founder and EVP of Oracle NetSuite, did just that when he called NetSuite the company’s next biggest product evolution in nearly three decades. But behind that sweeping vision is a quieter shift — one focused on how AI behaves, not what it can do.
“Every company is experimenting with AI,” says Brian Chess, SVP of Technology and AI at NetSuite. “Some ideas hit the mark, and some don’t, but each one teaches us something. That’s how innovation works.”
For Chess and Gary Weissinger, SVP of application development at NetSuite, the challenge is to drive AI responsibly. Instead of revamping its systems, NetSuite is extending into the AI ​​era the same principles that have guided its strategy for 27 years — security, control and auditability. It aims to make AI actions actionable, permissions actionable, and results expressible.
The philosophy suggests what Chess calls a “glass box” approach to enterprise AI, where decisions are visible and each agent operates within human-defined defenders.
Built on the foundation of Oracle
NetSuite is the result of the next five years of development. It is built on Oracle Cloud Infrastructure (OCI), which is relied upon by many of the world’s leading AI model providers, and has AI capabilities integrated directly into its core rather than added as a separate layer.
“We’re building a fantastic foundation on OCI,” says Chess. “This infrastructure provides more than just compute power.”
Built on the same OCI foundation that powers NetSuite today, NetSuite Next gives customers access to Oracle’s latest AI innovations with the performance, scalability and security of OCI’s enterprise-grade platform.
Weissinger emphasizes the team approach because “first, technology needs second.”
“We don’t take a technology-first approach,” he says. “We take a customer-first approach and then figure out how to use the latest technology to optimize those needs.”
That philosophy permeates the Oracle ecosystem. NetSuite’s collaboration with Oracle’s AI database, fusion applications, analytics, and cloud infrastructure teams helps NetSuite deliver capabilities that independent vendors cannot match.
Advantage of data structure
At the heart of the platform is a structured data model that serves as a key advantage.
“One of the great things about NetSuite is that, because the data comes in and is structured, the connections between the data are obvious,” Chess explained. “This means that AI can start exploring the knowledge graph that a company is building.”
Where General LLM probes through unstructured text, NetSuite’s AI works with structured data, identifying precise links between transactions, accounts and workflows to deliver context-aware insights.
Wessinger adds, “The data we have spans finance, CRM, commerce and HR. We can do more for customers because we see more of their business in one place.”
Combined with built-in business logic and metadata, this framework allows NetSuite to generate recommendations and insights that are accurate and interpretable.
Oracle’s Redwood Design System provides the visual layer for this data intelligence, which Goldberg describes as a "Modern, clean and intuitive" Workspaces where AI and humans naturally collaborate.
Designing for accountability
A downside of enterprise AI is that many systems still operate as black boxes – they produce results but offer little visibility into how they were reached. NetSuite is different. It is designing its system around transparency, making visibility a defining feature.
“When users can see how the AI ​​reached a decision—finding a path from A to B—they don’t just confirm accuracy,” says Chess. “They learn what the AI ​​knew how to do.”
This visibility turns AI into a learning engine. As Chess puts it, transparency becomes a “fantastic teacher,” helping organizations understand, improve, and trust automation over time.
But Chess warns against blind trust: “What’s troubling is when someone presents something to me and says, ‘Look what AI gave me,’ as if that makes it authentic. People need to ask, ‘What did he base? Why is this true? ‘”
NetSuite’s answer is tracking. When someone asks, “Where did this number come from?” The system can show them the entire reasoning behind it.
Governance by design
AI agents within NETSUITE further follow the same governance model as employees: roles, permissions, and access rules. Role-based security embedded directly into workflows helps ensure that agents operate only within authorized boundaries.
Weissinger puts it bluntly: “If an AI produces a narrative summary of a report and it’s 80% of what the user would have written. That’s fine. We’ll learn from their feedback and make it even better. But booking a general ledger is different. It has to be 100% accurate and that’s where control and human review really matters.”
Auditing the algorithm
Auditing has always been part of ERP’s DNA, and NetSuite now extends that discipline to AI. Every agent action, workflow adjustment, and model-generated code snippet is recorded in the system’s existing audit framework.
As Chess explains, “It’s the same audit trail you can use to find out what humans did. The code is verifiable. When LLM creates the code and something happens in the system, we can trace it.”
This tracking transforms AI from a black box to a glass box. When an algorithm expedites a payment or flags an anomaly, teams can see exactly which inputs and logic produced the decision – an essential safeguard for regulated industries and finance teams.
Safe extension
The other half of trust is freedom – the ability to extend AI without risking data exposure.
The NetSuite AI Connector Service and Sutec Cloud Platform make this possible. Through standards such as the Model Context Protocol (MCP), customers can integrate external language models into Oracle’s environment while protecting sensitive data.
“Businesses are hungry for AI,” Chess says. “They want to start hiring it.” But they also want to know that those experiences can’t go off the rails. The NetSuite AI Connector service and governance model gives partners the freedom to deploy while maintaining the same audit and authorization logic that governs native features.”
Culture, experience, and conservation
Governance frameworks only work if people use them wisely. Both 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 the CEO, I would start by asking: What are you already doing, and what is working?”
Wessinger agrees that balance is key: “Some companies join a central AI team while others let everyone experiment independently. Neither works independently. You need the structure for big grassroots initiatives and freedom.”
He offers a simple example: “Write an email? Go crazy. Touch financials or employee data? Don’t go crazy with it.”
Experience, both emphasize, is essential. “No one should have to wait for us or anyone else.” “Start testing, learn quickly, and be intentional about making it work for your business.”
Why Transparent AI Wins?
As AI moves deeper into enterprise operations, governance will define competitive advantage as much as innovation. NetSuite’s approach—building on Oracle’s secure cloud infrastructure and structured data foundation, extending its ERP control heritage in an era of autonomous systems—positions it to lead in both.
In a world of fuzzy models and risky promises, winning companies won’t just build smart AI. They can trust you.
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