TUG Connects 2026 brought Infor’s distribution ERP customer community to Nashville for a record-setting gathering centered on education, networking, product roadmaps and the fast-evolving role of artificial intelligence in distribution operations.

The event, built for users of Infor Distribution ERP products, featured more than 200 breakout sessions spanning the company’s offerings from enterprise ERP, to inventory management, pricing, order entry, reporting, analytics and beyond — and the AI capabilities for each. 

For Infor CEO Kevin Samuelson, who delivered a marquee keynote May 20, the first message to attendees was direct: Distribution remains core to Infor’s go-to-market strategy:

“Distribution is absolutely integral to the entire success of Infor. “You can never doubt how important you are in this community.”

Distribution Takes Center Stage

Samuelson said Infor focuses on eight industries overall, with distribution ranking as the second largest of those focus areas — a segment where the company intends to continue leaning in with investment, innovation and product roadmap development.

That emphasis landed in front of a record TUG attendance, with more than 800 attendees — and roughly 1,000 when guests were included. But the message quickly moved from the strength of the community to the technology question now dominating nearly every enterprise software discussion: how customers can move from AI experimentation to AI value.

Samuelson contrasted the AI conversation at the prior year’s event — when many companies were still working through pilots and limited conversion into business value — with the current environment, where he said AI is already generating material value. The challenge, he said, is that the landscape has become more complicated, with new products proliferating quickly and nearly every software company now claiming to be an AI company.

For distributors, Samuelson argued, the opportunity is especially large.

“Distribution is the perfect place for AI to create transformation,” he said. “You all have so much opportunity through the volume of transactions, so much is still done in legacy formats with fax or sales over the counter, things that really lend themselves to being able to use AI to drive value.”

That point aligns closely with the problems Infor says its distribution offerings are built to address. The company’s distribution software portfolio is positioned around industry-specific ERP and cloud suites for SMB and enterprise distributors, with capabilities that include eCommerce, warehouse management, AI-powered analytics, supply chain management and related applications.

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From AI Product to AI Service

Still, Samuelson cautioned that technology alone is not enough. Distributors may have abundant transaction data and process complexity, but they often do not have unlimited IT staff, capital or time to sort through every emerging AI tool. Infor’s role, he said, is to help customers cut through that complexity and deploy AI in ways that are practical for their businesses.

At the strategic level, Samuelson framed Infor’s AI approach around industry depth, openness, orchestration, security and partnership. Industry depth, he said, is the foundation: Distributors need more than organized data and access to the latest AI technologies. They need to understand where value can be unlocked inside their business and how to act on those opportunities.

That framing carried into a follow-up presentation by Rick Rider, Infor’s Senior Vice President of AI Innovation, who detailed how Infor is trying to operationalize that strategy through its Velocity Suite and what the company calls the “agentic enterprise.”

Both executives emphasized that Infor no longer sees AI as a discrete product deployment. Instead, Velocity Suite is meant to support an ongoing model of customer partnership and continuous co-innovation — a perspective that has changed as Infor has seen AI’s role in distribution evolve.

“Initially, we thought about AI as a product,” Samuelson said. “We need to get you the Infor Velocity Suite, you get up and going, we’re going to be in great shape. But our perspective here has changed a lot. And I think we feel now that AI is not a product, it’s a service.”

The distinction matters. In Samuelson’s view, AI is too dynamic for the traditional enterprise software model in which a vendor builds, tests, implements and supports a product in relatively linear fashion. Instead, Infor believes customers will need ongoing help identifying opportunities, deploying tools, adapting as technology changes and ensuring the burden of keeping AI useful does not fall entirely on distributors.

Building the Agentic Enterprise

Rider described Infor’s vision for the agentic enterprise as a journey from AI-assisted decision support toward semi-autonomous and eventually fully autonomous operations, with governance central at every stage.

That journey starts with industry agents that help users gain intelligence at specific decision points. From there, companies can move toward semi-autonomous processes, where humans remain in the loop but AI handles more analysis, recommendations and workflow support. Eventually, Rider said, companies may identify processes where outcomes are predictable enough to automate more fully.

But autonomy must come with controls. As AI agents become more capable, they begin to function like synthetic users inside enterprise systems, requiring new thinking around scopes, permissions, security and governance.

Rider laid out four guiding principles behind Infor’s AI strategy: precision, cohesion, agility and governance. Precision starts with Infor’s industry context — the idea that its systems are designed to reflect differences between verticals and microverticals.

“We believe at Infor that we have the foundation to be the most precise in the age of AI than all of our competition out there,” Rider said. “We’ve talked about industry context for so long, and it’s almost like as we moved into this era of AI, the context is king.”

For distribution, that means understanding the differences between electrical, HVAC, plumbing, building supply and other microverticals, and embedding those distinctions into the product. That context is then used by AI to improve decisions, speed outcomes and reduce hallucinations or variability in results.

Cohesion, the second principle, is tied to Infor OS and the need to orchestrate outcomes across multiple systems, tools and agents. Rider noted that even when customers use external AI tools, those tools still need to interact with enterprise systems, data sources, workflows and security layers. Without orchestration, administration and security can become difficult to manage.

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Process Intelligence as the Starting Point

Rider’s third principle, agility, is where the keynote moved from AI strategy to business execution. He described Infor’s approach as a cycle of diagnose, automate and optimize.

The starting point is process intelligence — using technology to examine workflows and identify bottlenecks, cycle-time issues and areas of opportunity. Rider used procurement and payables in distribution as an example, noting that those processes span multiple personas and activities, from vendor analysis to purchase order creation, goods inspection and invoice processing.

Process intelligence, in that model, helps identify where AI and automation should be applied first. But Rider emphasized that the goal is not only efficiency.

“Everyone talks about AI in terms of efficiencies today,” Rider said. “That’s not the way we think about it. We think about how can you increase your market share through the use of these intelligent applications. So that’s what process intelligence is not just about the efficiency, but about the areas of opportunity where we can increase market share against your competition.”

From there, Infor can apply existing tools from its Velocity Suite catalog or co-develop new use cases with customers. Rider cited examples such as vendor compliance checks, purchasing agents that automate parts of the purchase order process and invoice processing — an area he said has generated significant ROI for customers.

Rather than treating each use case as a one-off project, Rider positioned the Velocity model as an ongoing practice: find opportunities, deploy solutions quickly into production environments, measure ROI and repeat that process across additional workflows. In procurement and payables, that could mean reducing cycle time, lowering cost per invoice, improving capture rates and shortening cash cycles.

A More Adaptive ERP Experience

Rider also pointed to a changing user experience as AI becomes embedded into enterprise software. Historically, ERP users have needed to understand where to go inside the system, which screens to navigate and how to complete each step — a challenge for newer employees without deep domain knowledge or years of ERP experience.

Infor’s answer, Rider said, is an “adaptive experience” that delivers the right information at the right time and can generate forms, workflows and recommendations without requiring users to move through traditional ERP screens step by step.

In one example, Rider described using process mining to investigate late deliveries and identify abnormalities in the purchase order-to-shipment cycle. From there, the system can drill into impacted products, surface a stock optimization analysis and recommend immediate configuration changes tied to measurable business impact.

The key, Rider said, is that users may not need to work from a traditional CloudSuite Distribution or CloudSuite Distribution Enterprise screen to make those changes. Instead, the system can abstract the experience up a level, enabling employees who have never seen an ERP screen to complete meaningful work.

Governance Remains a Prerequisite

The final piece is governance. Rider said Infor is making significant investments in governance, risk and compliance capabilities to account not only for traditional users, but also for AI agents and agentic profiles.

That means applying scope control to what agents can do, aligning permissions to specific users or personas and ensuring Infor OS security respects those boundaries. The point is to give customers confidence that AI-generated outcomes are trustworthy and that companies can move toward greater autonomy with appropriate controls.

That message is especially relevant for distributors, where AI opportunities may be broad but tolerance for operational disruption is limited. Purchase orders, inventory decisions, invoice processing, customer service and replenishment workflows all have significant downstream implications if automated poorly.

The Final Word

The TUG takeaway for distributors was clear: Infor sees distribution as central to its business, and it sees AI as a major lever for distributors that can turn high-volume transactions, legacy workflows and operational complexity into value. But Samuelson and Rider’s combined message was not that distributors need another AI product to manage. It was that they need industry-specific software, governed automation, a more adaptive user experience and a partner willing to stay engaged as AI keeps changing.