NetSuite showcases AI tools for ERP workflows & finance

NetSuite used its SuiteWorld product keynote to explain how its AI tools work within its ERP platform. The presentation focused on features already available in environments running NetSuite Next.

The session expanded on NetSuite's broader push around what it calls an autonomous suite, in which AI handles parts of finance and operations work while staff retain control over approvals and decisions.

A central message was that trust in AI depends on access to core business data and clear oversight. AI outputs, NetSuite argued, should sit within the same roles, permissions and customisations that already govern how staff use the system. It showed results alongside the reports, assumptions and records behind them.

Conversational interface

Much of the keynote centred on Ask Oracle, the conversational assistant NetSuite is positioning as a front end for interacting with the ERP system. Users can ask plain-language questions about profitability, cash flow or unusual trends. The assistant interprets the request, gathers data, runs analysis and returns an answer with supporting records.

The emphasis on context was notable. Ask Oracle works within existing reporting structures and access controls, so responses reflect the user's role and the company's own data without requiring specialist prompt writing.

NetSuite also outlined a pattern in how customers use AI tools across its platform. More than 15,000 businesses use AI through Ask Oracle in the product and through Claude and ChatGPT linked via its AI Connector, according to the company. Those interactions tend to move in stages, beginning with requests for insight, followed by suggested actions and then requests for automation.

Skills and agents

Another part of the presentation focused on SuiteSkills, which NetSuite described as a way to encode an organisation's preferred processes, approval rules and operating practices so AI can reuse them during routine tasks. Demonstrations covered employee onboarding, equipment provisioning and procurement.

The aim is to capture operational knowledge that often sits with a small group of experienced staff. In practice, NetSuite presented skills as a repeatable set of instructions that can be applied whenever a user works with the assistant.

SuiteAgents formed the second major building block. NetSuite described an agent as AI assigned to a specific purpose, with defined goals, instructions, permissions and business context. In the demonstrations, agents monitored projects, identified risks, recommended actions, drafted records and carried out routine tasks within set boundaries.

NetSuite also introduced a SuiteAgent Management Workspace, which gives administrators visibility over what agents are doing, what data they are using and where intervention might be needed. It also includes an option to switch an agent off.

Finance focus

Finance featured heavily in the keynote, with NetSuite arguing that the function stands to see some of the earliest gains from embedded AI. The company pointed to research showing that nearly two-thirds of Chief Financial Officers now play a leading role in technology and AI strategy.

Its answer is an operating model it calls "always be closing", designed to turn the financial close from a monthly event into an ongoing process. Some customers have reduced close cycles from about 20 days to as little as two or three, NetSuite said.

The Intelligent Close workspace is designed as the main control point for that process. It brings close activities into a single dashboard where teams can track progress, projected completion dates and the tasks most likely to affect the reporting timetable.

Teams can upload an existing close plan from a spreadsheet, after which Ask Oracle maps activities to NetSuite tasks, recommends further steps, assigns owners, sets dependencies and creates a reusable template, according to NetSuite. During the reporting period, AI agents can then assist with bank reconciliations, balance sheet reviews and exception management.

Broader use cases

Outside finance, the keynote showed how the same model could be applied to inventory, projects, sales and customer support. For product businesses, NetSuite highlighted tools for inventory optimisation, fulfilment performance and inventory movement insights. For project-led companies, it pointed to project intelligence, risk, resourcing and portfolio tools. For subscription and sales teams, it included cohort analysis, revenue leakage, lead management, returns handling and marketing review.

One demonstration showed a services business using a project portfolio view that flagged a high-risk project after a Solution Architect was allocated at 125 per cent and a milestone risked slipping by two weeks. Ask Oracle explained the issue, proposed staffing options, listed alternatives by utilisation and rates, and completed a reassignment only after approval.

Another example involved an inventory optimisation agent at a distributor with 30,000 parts. NetSuite said the agent identified USD $700,000 of slow-moving stock and highlighted a hydraulic pump assembly running 31 per cent below forecast with USD $175,000 of excess inventory, before tracing the shift in demand to a supplier's newer model.

For businesses in Australia and New Zealand, the presentation suggested NetSuite's AI strategy will rely less on standalone tools and more on embedding automation into existing ERP workflows. It also indicated that the regional rollout of NetSuite Next is behind North America, leaving local organisations to decide where these tools might fit before broader availability arrives.