With NetSuite Next, NetSuite seeks title of the top AI cloud ERP

The cloud is no longer enough. Oracle NetSuite showed off a wide range of AI features across its cloud ERP platform at its SuiteConnect event in Sydney to justify it's new tagline, #1 AI Cloud ERP.

The event, held on 23 March, drew NetSuite customers from across Australia and New Zealand to see the company's latest product direction. ANZ managing director Scott Wiltshire framed the announcements around three trends he said were shaping the region's business environment: the need to operate under persistent uncertainty, pressure to improve productivity without growing headcount, and demand for AI that delivers at the organisational level, not just for individuals.

"All of this leads to a simple reality. Businesses have become harder to navigate and that, in turn, changes what we need from technology. We're in the middle of a once in a generation shift where AI is changing what's possible," Wiltshire said.

NetSuite Next

The centrepiece announcement was NetSuite Next, a redesigned interface built on Oracle's Redwood design system that adds a natural language assistant called Ask Oracle throughout the platform.

The assistant lets users search, navigate and interrogate data in plain language without needing to know which report or menu to open. It is context-aware by role: a CFO asking about open purchase orders receives financial analysis, while a warehouse manager asking the same question gets inventory data.

Every response references the exact record, transaction or field it drew from. NetSuite Next will be available to ANZ customers within 12 months, with a preview period beginning within six months.

Finance close

The period-end close was a recurring focus. NetSuite demonstrated Exception Management, an AI agent that continuously scans financial data and flags anomalies as they arise during the month rather than at close. Working alongside it is the Intelligent Close Manager, a command centre view that tracks task completion, net income impact and a rising confidence level toward what NetSuite called a zero-day close.

A live walkthrough showed a finance team member reviewing flagged exceptions – including a sales order with an incorrect amount – approving accruals, completing reconciliations across subsidiaries and locking the period, with the agents handling the underlying work. Both Exception Management and the Close Manager are available now.

AI Bank Transaction Matching uses generative AI to interpret ambiguous bank descriptions, match them to general ledger records and reduce the manual investigation finance teams currently do around unclear entries. Advanced Pricing, also available now, lets businesses set pricing rules that respond dynamically to cost changes, customer segments and promotions without managing spreadsheet overrides.

Field service

The Field Service Management demo illustrated two sides of the same job: a coordinator receiving an AI-generated alert about a downed excavator at a VIP customer site. The AI identified which technicians in the field were closest to the site, weighed up trade-offs between proximity and expertise, and updated the schedule once a decision was made.

On the technician's side, a mobile app displayed an AI-generated asset history and diagnostic analysis before the technician arrived on site. When the job was done, the technician dictated notes in Italian; NetSuite translated them into English and reformatted them as a customer-facing service report automatically.

Narrative layer

The Narrative Insights feature – rolling out across more than 20 areas of the suite in the 26.1 release – places plain-language summaries directly on reports, including financial statements, inventory reports, project status and journal entries. A comparative balance sheet demo showed an AI-generated executive summary listing the top five findings, key risks and opportunities alongside recommended actions.

The AI Connector Service, built on the Model Context Protocol, lets external AI assistants interact with NetSuite data directly. A demo showed Claude querying 30 days of past-due invoices, generating an aging analysis and then constructing a risk assessment dashboard with payment pattern recommendations – all through conversational prompts.

A second example showed an NGO uploading a photo of a donated snow blower. Claude identified the model, checked existing inventory, assessed the item's condition, estimated its value and updated the inventory record with a memo.

Custom agents

The Suite Agents framework lets businesses build their own custom AI agents inside NetSuite using a prompt-based configuration tool. A credit approval demo showed an agent pulling NetSuite data alongside third-party credit information to recommend whether to approve or reject orders above a credit limit. When the company's credit policy changed, uploading a new policy document was enough to update the agent's behaviour with no redeployment needed.

Adoption signals

Brian Chess, Senior Vice President of AI, Product, and Technology, Oracle NetSuite, said it was clear which AI features were most popular among beta customers in the US. "The most successful AI features that we've ever released are the ones where it's just right there, and a lot of times a customer doesn't even know there's AI involved," he said. Narrative Insights was a key example. "Just right there on a report, you just say, what do you see, and you get an AI analysis of the report that you're looking at. It's really, really easy to adopt."

For the ANZ market specifically, Wiltshire said he expects early uptake with exception management. "Practically speaking, a lot of that work isn't happening today. So to be able to enable that, that's a value add straight away."

More adventurous customers are already going further.

"If I look at the early adopters, that's what people are doing – they're getting on board, particularly with the generative models connecting them to NetSuite and other systems, and starting to interact with those systems in new ways," Wiltshire said.