Surprisingly Useful AI Article Enhancements
Procurement software company JAGGAER has launched JAI, an AI-powered assistant built into its platform that allows employees to ask procurement questions in plain language and receive policy-compliant answers without raising support tickets.
Early results from customers already using the tool point to a 50 per cent reduction in support tickets expected in the first year, time savings across more than 40 different workflows and adoption growing by as much as 1,000 per cent week-on-week in some cases.
JAI is available now and can be deployed quickly once an organisation decides to adopt it.
How it works
Employees type questions in plain language – such as whether they need approval for a purchase or who a preferred supplier is for a particular category – and JAI returns an answer immediately. It supports 28 languages.
The assistant is grounded on each customer’s own documents and data rather than the open internet, meaning responses are based on the organisation’s actual policies, contracts and supplier information. It also respects the existing security and access controls within the JAGGAER system, so users only see information they are authorised to access.
Beyond answering questions, JAI can analyse spending data to surface insights that would typically require hours of analyst work. Use cases include identifying spending outside approved channels, flagging suppliers that carry elevated risk and highlighting areas where costs could be reduced.
Addressing a common pain point
JAGGAER frames JAI as a response to a problem common across procurement teams: employees asking routine questions like “Do I need approval to buy this?” or “Who is our preferred supplier for office equipment?” that currently require opening a ticket, waiting for a response and interrupting another team member’s workflow.
JAGGAER Chief Executive Officer, Andrew Roszko, described the tool as a shift in how procurement teams access information.
“Procurement has always been about making smart decisions with limited time and information. JAI changes that equation entirely,” Roszko explained. “It is embedded into the core platform and actually earns trust – it knows your business, respects your rules and gives you answers you can act on. This is just the beginning.”
Early customer feedback
A large financial institution participating in the early access phase described how JAI addresses the challenge of navigating complex internal standards.
“As a financial institution, we’re beholden to very high standards from both a regulatory and a contractual standpoint,” the institution noted. “In practice, this means that supply chain teams need to reference and adhere to a complex set of principles. These are set out across different guides that range from risk standard handbooks to sourcing guides, often located in different places or outside the internal system, making the reference process difficult.”
“JAI changes that. By creating a unified view of all these standards, users can find the answers to their questions rapidly and efficiently without exiting the system,” the institution continued. “We’re confident in improvements on ticketing times and audit preparation in the future. But the time savings and accuracy of the detail we’re seeing in the early access phase is already a huge win.”
AI governance certification
Alongside the launch, JAGGAER has achieved ISO/IEC 42001:2023 certification for its Artificial Intelligence Management System. The company claims to be the first source-to-pay vendor to attain this international standard.
The certification covers JAGGAER’s approach to managing AI across ethical implications, data governance, security and continuous improvement. It applies to all AI-driven features within the platform, including JAI.
About JAGGAER
JAGGAER is a procurement and supplier collaboration software company with 1,200 employees globally. The company has operated for 30 years across direct and indirect procurement, offering source-to-pay solutions. More information is available at www.jaggaer.com.
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Last Updated on May 15, 2026 by Nick Ross
