Infor releases global study on AI adoption barriers and introduces key platform features.

Infor has published the results of its Infor Enterprise AI Adoption Impact Index, new proprietary research. The study surveyed 1,000 business decision-makers across the US, UK, Germany, and France on the barriers preventing businesses from deploying and scaling AI. As a result of the research, Infor has launched new features across Infor Velocity Suite. It has also announced limited availability of an enhanced Infor Agentic Orchestrator, designed to deliver the industry specificity, precision and governed execution. Infor says this will help enterprises close the gap between AI ambition and AI value

The research suggests persistent barriers preventing enterprises from launching complex AI initiatives, even among companies with a 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 exist. These include data security, sovereignty, and compliance (36%), lack of internal AI talent (25%), and unclear ROI (23%).

“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 industries by meeting our customers where they are with AI. Thereby providing a clear, simple, and efficient path to where they want to be.”

Infor Velocity Suite and Infor Agentic Orchestrator

49% of businesses are still in early AI deployment, with most only running pilots or limited rollouts. Achieving value from AI requires leading technology, industry knowledge, effective execution, and transparent governance. Infor says its new capabilities are designed to meet these needs.

Expanded Agents and Use Case Library

One in four businesses state a lack of internal AI talent as a top barrier to scaling AI. The company says its Infor Velocity Suite is the simplest path for customers to realise value from their AI investment. Infor Velocity Suite now offers all Infor Industry AI Agents as part of its comprehensive package, designed to accelerate business impact after go-live. The latest release features several important updates:

• Industry AI Agents: Infor Industry AI Agents, Agent Orchestration, and Agent Factory are now included in Infor Velocity Suite. This gives customers access to agents built for their industry that recognize the right moment to act and deliver value.
• Value+ Solutions: Infor Value+ solutions, a catalogue of pre-built automations customised to diverse industry needs, now discoverable directly from within Infor CloudSuites. This enables quick and easy access and improves 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. This provides critical expertise to help customers 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.

New Warehouse Management System features

Infor is launching a new Velocity Suite add-on for its Warehouse Management System (WMS) to enhance daily operations. Using machine learning, pick path optimisation directs employees along efficient routes. This can reduce travel distance by up to 25% and speed up order fulfilment.

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. Infor has also announced 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. These include integrating specialised task agents from planning to deployment. Supervisor agents maintain context across relevant tools and are pre-trained to flag anomalies. This is expected to free 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. The company says that 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 access data securely and act across Infor applications. Since 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: key findings

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 standards set by enterprise leaders’ AI ambitions.

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 converted 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. This was followed by lack of internal talent to configure and maintain AI (25%) and unclear business benefits or return on investment (23%).

Data and agent distrust are slowing the path from deployment to value

• 27% of respondents were unsure or disagreed that their organization’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.

Security, agents, and industry fit the top of 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, predictable AI pricing is important, indicating that cost transparency ranks highly as a capability when committing to long-term AI investment.

Enterprise Times: What this means for businesses

Infor’s research follows a common thread from other similar industry studies and analysts’ reports. Essentially suggesting that enterprises, irrespective of size, sectors and geographies, are failing to maximise their initial investment in AI. Enterprises don’t struggle with ideas about AI. They tussle with making AI work effectively inside the systems and processes that run their business. Hence, Infor’s April release, which includes Industry AI Agent updates and the limited availability of Infor Agentic Orchestrator. These solutions are tailored to help customers close persistent AI execution gaps uncovered by the research. AI is a revolutionary technology that enables businesses to address difficult problems and create lasting competitive edges. However, the operational and execution infrastructure within enterprises is falling short of the expectations set by leaders’ ambitions for AI. The main challenge lies not in the technology itself but in how enterprises choose to implement it.

Unfortunately, Infor’s research does not provide any guidelines or AI best practices. This may be too premature for new technology, which is still rapidly evolving and impacting industries and sectors. However, understanding from the ‘lessons learned’ of organisations may be a means of accelerating that shared learning needed to mature AI.

The post Infor releases global study on AI adoption barriers and introduces key platform features. appeared first on Enterprise Times.