What does it take to build the right data foundation for your enterprise on M3, find the right partner to scale your data capabilities, identify where AI can address business gaps, and build the capability to drive your own AI innovation?
That was the focus of Fortude’s keynote at the Infor M3 and CloudSuite User Network (IMUN) Conference 2026, where we explored what it takes to move from AI experimentation to practical, enterprise-ready applications of agentic AI.
Our keynote, “Agentic AI on Infor M3: Why the Right Foundation Matters,” brought together a customer perspective, Fortude’s approach to building an agentic data platform, and real-world examples of how agents can support Infor M3 delivery and day-to-day business operations.
Building the foundation for AI
The keynote opened with the CIO of a leading Australian connectivity and communications technology group who shared the organization’s journey from ERP transformation and fragmented reporting to a more unified data foundation.
As the business modernized its ERP environment, it faced the challenge of bringing together data from different systems and creating a more consistent approach to reporting and analytics. Rather than treating AI as a separate initiative, the organization built its data foundation alongside its ERP transformation, starting with practical business needs across areas such as sales and finance.
As the platform matured, trusted, integrated, and governed data created a foundation for emerging AI capabilities.
The journey highlighted an important lesson for organizations looking to introduce AI into their ERP environments: AI readiness starts with a strong data foundation and the right partner to support the journey.
From analytics to action
Building on that customer story, Cameron Greening, Chief Revenue Officer – ANZ, Fortude, explored what comes next – moving from a unified data platform to an agentic data platform.
Not every business question needs an agent. Some questions are best answered through dashboards, while others require an agent that can take action.
This distinction is increasingly important as organizations move beyond traditional analytics and explore how AI can participate in business processes. A unified data platform provides the foundation for analytics and AI, while agents can be introduced where they can deliver practical value.
Our Lakehouse Accelerator helps build this foundation across three layers:
- Brings data together: Connects data from Infor M3 and other business systems in one central place, making it easier to access and use.
- Makes data useful: Organizes and cleans data so teams can use consistent information for reporting, analytics, and decision-making.
- Makes insights accessible: Turns data into easy-to-use views and business metrics, helping teams find the information they need without relying on technical teams for every question.
Building and running with agents in Infor M3
Surangana Sarathchandra, CTO, Fortude, then explored Fortude’s approach to agentic AI in Infor M3 across two areas: agents that support Infor delivery and agents that help run business processes.
On the delivery side, Fortude is using agents across implementation, upgrades, and ongoing support. These agents support activities including development, legacy code uplift, documentation, regression testing, release impact assessment, and issue analysis, while human review and quality controls remain part of the process.
The results from two live M3 development workstreams provided an early indication of the potential. One workstream recorded a 36% reduction in development effort across multiple SDK developments, while another recorded a 51% reduction for refactoring an existing interface.
The focus, however, is not simply on speed. Human review, architecture checks, quality gates, and governance remain built into the delivery approach.
On the business side, the conversation looked at how agents can support day-to-day operations through Infor Velocity Suite and agents built for Infor. One example from Fortude is the Order Capture Agent that can read purchase orders arriving by email or PDF, validate them against business rules and Infor master data, and create clean orders in CloudSuite, with exceptions routed to the appropriate team.
There are a few more agents that we have built to improve business processes; here are a few examples:
- Sales Agent: Gives sales reps and managers instant visibility into open orders, customer accounts, and pricing, while flagging at-risk orders before they become a problem.
- Inventory Agent: Gives planners and warehouse teams a clear view of stock levels and replenishment needs, while flagging stockout risks and recommending reorder quantities.
- Financial Planning and Analysis Agent: Helps finance teams understand budget variances and draft forecasts in plain language, rather than working through spreadsheets full of formulas.
Explore the full list of business process agents.
What CIOs and CTOs should consider
The keynote also brought the conversation back to the realities of enterprise AI adoption.
Drawing on customer experience and Fortude’s own learnings, the discussion highlighted the importance of security, IP protection, role-based access, observability, governance, and cost management when introducing agents at scale.
It also reinforced the importance of starting with practical use cases and understanding the full cost and operational implications of AI adoption. Complex agentic use cases can take time to implement and operationalize, while simpler use cases can sometimes provide a more practical starting point.
For Infor M3 organizations, the opportunity is to build on the ERP and data foundation they already have, introduce agents where they can solve meaningful business problems, and put governance in place at the beginning to scale responsibly.
Talk to our consultants about building a roadmap to scale AI across your Infor M3 environment.
