Annexa targets new AI opportunities at SuiteWorld 2026

Annexa is ramping up AI capabilities for Oracle NetSuite customers, utilising agents to automate repetitive and time-consuming ERP tasks across procurement, inventory management and sales.

The Australian NetSuite Solution Provider has been developing its Erstan platform to coordinate AI agents across business applications, allowing them to execute workflows that span ERP systems, CRM software and communications tools.

The upcoming SuiteWorld 2026 promises significant AI-infused improvements for multiple use cases across different industries, further enhancing what ERP will allow businesses throughout Australia and New Zealand to achieve, said Director of Sales & Marketing at Annexa, Matthew Owens.

SuiteWorld conference to feature improvements

SuiteWorld, taking place October 25-28 in Las Vegas, Nevada, will showcase multiple new developments in Oracle NetSuite's AI capabilities as the software provider continues investing in tools embedded within its ERP platform.

These native capabilities will offer businesses access to AI-powered functionality through their existing software environments, including reporting insights and anomaly detection.

"The biggest shift is AI moving from answering questions to actually completing tasks and running workflows across finance and operations and everything connected to it," Owens said.

"That matters well beyond NetSuite. Every mid-market business in ANZ is under pressure to grow without adding cost at the same rate. Agents that do real work across systems processes are absolutely enablers of that.

"What we're watching is NetSuite building AI into the core of the platform rather than bolting it on.

"Once AI is part of the infrastructure, partners and customers can build on it but also have flexibility to use external models for the right job, with NetSuite's MCP and integrations supporting this."

SuiteWorld will also provide the Annexa team an excellent opportunity to engage with product teams and gain even more insight into the NetSuite AI roadmap.

Owens cited native AI functionality, external system connectivity and NetSuite Next, an updated experience featuring a new user interface and integrated LLM capabilities as particularly exciting developments.

Agents cut procurement processing from hours to minutes

One of Annexa's key applications involves a procurement assistant developed for Australian fashion retailer Boody, which uses AI agents to process supplier orders and subsequent revisions.

Suppliers often send spreadsheets containing thousands of product lines, multiple worksheets and successive order revisions. Procurement teams must review the documents, identify changes, update purchase orders and ensure the revised information flows into demand planning processes.

This process can take between three and six hours when completed manually.

Annexa's AI agents can perform the work in approximately five minutes, including reviewing supplier workbooks, creating purchase orders, splitting orders where necessary, modifying individual lines and identifying product substitutions.

The agents can also process subsequent supplier revisions, allowing changes received overnight to be reviewed before procurement staff begin work the following morning.

Instead of automatically applying changes without oversight, the system can flag proposed substitutions and present recommendations to procurement managers for approval.

The automation is designed to reduce the amount of time employees spend comparing spreadsheets and updating systems, allowing them to concentrate on decisions that require human judgement.

Owens said businesses could find significant efficiency gains by targeting smaller, routine activities across procurement, inventory planning and sales, rather than focusing exclusively on larger processes such as monthly financial close or board reporting.

Automation creates new sales opportunities

Annexa has also developed AI agents for Boody to manage back-ordered products and identify opportunities to generate additional sales.

In a typical B2B retail scenario, customers may place orders containing products that are unavailable. Businesses can close the affected order lines instead of leaving them open while waiting for stock to arrive.

Traditionally, following up with those customers when products become available requires employees to identify the original orders, prepare new quotes and contact the customer.

Annexa's agents can monitor closed back-order lines and generate quotes when the products become available again.

The system then alerts employees, allowing them to review the opportunities and notify wholesale customers about the available stock.

Owens said the process had previously been difficult for the retailer to pursue because of limited staff capacity.

By automating the work, Annexa has helped create an additional opportunity to generate revenue from customers who had already demonstrated demand for the products.

The example highlights a broader objective for AI implementation: using automation not only to reduce operating costs but also to enable business activities that might otherwise be neglected.

For organisations operating with limited resources, Owens said, the ability to automate repetitive tasks helps employees focus on commercial decisions and growth opportunities instead of getting mired in repetitive or time-consuming activities.

Human oversight remains essential

Across sectors, businesses are facing pressure to improve productivity and remain competitive amid global economic uncertainty, rendering the ability to complete more work with existing resources increasingly important.

In this context, AI is viewed as a tool to augment human workers' capacity, not a silver bullet.

Owens argued that despite increasing agentic usage, humans will continue to be responsible for business decisions, particularly where financial or operational consequences are involved.

"People still need to make decisions," he said. "People will remain accountable for the decisions that businesses make."

AI agents are capable of managing tasks autonomously, provided companies maintain appropriate controls and records explaining what an agent is doing and why.

The distinction is particularly important as AI moves beyond summarising information and begins executing multi-step workflows across different applications.