Infor today announces new capabilities across Infor Velocity Suite and the limited availability of an enhanced Infor Agentic Orchestrator, designed to deliver the industry specificity, precision and governed execution that enterprises need to close the gap between AI ambition and AI value. The release is backed by findings within the Infor Enterprise AI Adoption Impact Index, a new proprietary research surveying 1,000 business decision-makers across the US, UK, Germany, and France on the barriers preventing businesses from deploying and scaling AI.
The research points to persistent, shared barriers preventing enterprises from launching complex AI initiatives, even among companies with strong ambition to scale. While 80% of business decision-makers globally believe their organisation has the internal capability to manage an AI implementation, significant structural barriers like data security, sovereignty, and compliance (36%), lack of internal AI talent (25%), and unclear ROI (23%) remain as major obstacles and prevent organisations from advancing their AI strategy.
“At Infor, agentic AI isn’t a feature we bolted on. It’s the culmination of two decades of deliberate foundation building. Our industry-specific platforms, multi-tenant architecture, and deep process intelligence give our agents a level of contextual precision that generic AI simply cannot replicate. A purchasing agent at a healthcare provider and one at a discrete manufacturer aren’t the same agent; they shouldn’t be,” said Kevin Samuelson, CEO, Infor. “That specificity is what allows us to clearly articulate the ROI, and deliver on it. We’re not selling automation for its own sake. We’re selling measurable outcomes for the industries by meeting our customers where they are with AI and providing a clear, simple, and efficient path to where they want to be.”
“It is very clear that Infor’s clients are finding sustained economic value with their path to the agentic enterprise, and they love the journey with Infor,” said Mickey North Rizza, Group Vice-President, Enterprise Software for IDC.
Infor Velocity Suite and Infor Agentic Orchestrator
Despite widespread confidence in capability, nearly half of organisations globally (49%) are still in the early stages of AI deployment, with many yet to move beyond pilots or partial rollouts. The path to AI value demands best-in-class technology, paired with industry context, governed execution, and a transparent governance approach. Infor’s new and expanded capabilities are built precisely to deliver that approach.
Infor Velocity Suite: expanded agents and use case library
One in four businesses cites a lack of internal AI talent as a top barrier to scale AI. Infor Velocity Suite is the simplest path for customers to realise value from their AI investment. As a full-suite package combining precise AI solutions, tools, technology, and industry expertise, Infor Velocity Suite now includes all Infor Industry AI Agents, tailored to provide a faster, connected route between go-live and business impact. This release delivers several key updates, including:
Industry AI agents: Infor Industry AI Agents, Agent Orchestration, and Agent Factory are now included in Infor Velocity Suite, giving customers access to agents built for their industry that recognise the right moment to act and deliver value.
Value+ Solutions: Infor Value+ solutions, a catalogue of pre-built automations customised to diverse industry needs, are now discoverable directly from within Infor CloudSuites – enabling quick and easy access and improving an enterprise’s time to value.
CareFor Managed Services: every implemented Infor Velocity Suite solution is now paired with a year of complimentary CareFor Managed Services post go-live, providing critical expertise for customers to ensure their AI investments are on the path to value from day one.
Prescriptive AI use case packs: Infor Velocity Suite now includes recommended and curated sets of ML and AI use case packs organised by role, process, and industry. Each pack gives everyday users a clear starting point for adoption to show where organisations can immediately benefit from Velocity Suite within their own critical business processes.
Additionally, Infor is introducing a new Velocity Suite add-on for Infor Warehouse Management System (WMS) focused on improving day-to-day warehouse operations. The pick path optimisation use case leverages machine learning to guide warehouse workers along the most efficient routes when picking items for orders. By reducing unnecessary walking and equipment travel, customers have achieved up to a 25% decrease in travel distance, helping warehouses operate more efficiently and fulfil orders faster.
Infor Agentic Orchestrator: now in limited availability
Thirty-two per cent of business leaders rank the ability for AI to perform tasks autonomously as a top three priority for AI success. Within Infor Industry Cloud Platform, Infor’s Agentic Orchestrator acts as the trusted, transparent infrastructure layer that enables Industry AI Agents to move from isolated tasks to coordinated workflows. Today, Infor is announcing the limited availability of a newly enhanced update, which will operate across three critical capability areas:
Orchestration: advanced coordination between Supervisor Agents enables Infor GenAI Assistant to perform complex, multi-step workflows – integrating specialised task agents from planning to deployment. Supervisor Agents maintain context across relevant tools and are pre-trained to flag anomalies, freeing up employee time while ensuring a human remains in the loop where needed.
Interoperability: enterprises currently spend an estimated 30-40% of their total budget on integration. With Infor Agentic Orchestrator, customers don’t have to choose between cost and time savings: Infor’s Model Context Protocol (MCP) servers standardise how AI models securely access data and take action across Infor applications, and because MCP is an open standard, they work alongside connections to non-Infor applications too. Additionally, third-party MCP tools and agents can be accessed through the Infor ecosystem.
Observability: new visibility features are divided into three updated capabilities – Inline Thoughts, Evaluation Framework, and Focus Mode – that allow users full control and oversight.
These updates directly address the common barriers enterprises face, giving businesses the technology-backed confidence to deploy, scale, and iterate their AI-powered workflows across their organisations.
Enterprise AI Adoption Impact Index: findings in detail
The Enterprise AI Adoption Impact Index polled 1,000 C-Suite, VP, Director, and Head-of-level professionals across retail and wholesale, food and beverage, industrial manufacturing, automotive, and logistics and distribution. Across industries and roles, the trend is clear: enterprise operational and executional infrastructure isn’t meeting the standard of enterprise leaders’ AI ambitions.
Finding 1: AI confidence is high, but structural barriers persist
- 80% of respondents believe their organisation has the internal capability to manage an AI implementation
- However, that confidence isn’t necessarily converting into results: 49% are still stuck in the AI early stages – running pilots only, paused, or yet to start
- When asked to name the single greatest barrier to advancing their AI strategy, respondents ranked data security, sovereignty/privacy, or compliance (36%) first, followed by lack of internal talent to configure and maintain AI (25%) and unclear business benefits or return on investment (23%)
Finding 2: Data and agent distrust are slowing the path from deployment to value
- 27% of respondents were unsure or disagreed that their organisation’s data is mature and well-governed enough to support reliable AI
- 31% were very or slightly uncomfortable with autonomous agents executing critical business processes
- On average, nearly half (49%) of AI-generated insights and workflows require manual review by a subject matter expert to ensure accuracy against industry regulations and processes
Finding 3: Security, agents, and industry fit top the AI wish list
- When asked about their top three priorities for ensuring long-term AI success, respondents ranked enhanced data security and sovereignty (37%), the ability for AI to perform tasks autonomously (32%), and industry-specific AI use cases (28%) the highest
- 87% of respondents say fixed and predictable AI pricing is important, meaning cost transparency ranks highly as a capability when committing to long-term AI investment
