Infor has introduced new capabilities across its AI portfolio, alongside research suggesting many businesses are still struggling to scale artificial intelligence beyond pilot stages.
The company’s April release includes updates to its Infor Velocity Suite and the limited availability of an enhanced Infor Agentic Orchestrator.
The announcement is supported by findings from the Infor Enterprise AI Adoption Impact Index, which surveyed 1,000 business decision-makers across the US, UK, Germany, and France.
According to the research, while 80 percent of organizations believe they have the internal capability to implement AI, nearly half – 49 percent – remain in early deployment stages, often limited to pilots or partial rollouts.
Key barriers cited include data security and compliance concerns (36 percent), lack of internal AI talent (25 percent), and unclear return on investment (23 percent).
Kevin Samuelson, CEO of Infor, said: “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. 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.”
Mickey North Rizza, group vice-president for enterprise software at IDC, added: “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.”
The updated Velocity Suite expands access to Infor’s Industry AI Agents and introduces curated AI use-case packs, pre-built automation tools, and managed services aimed at accelerating deployment.
The company also highlighted a warehouse-focused add-on for its warehouse management system, where machine learning-driven pick path optimization has delivered up to a 25 percent reduction in travel distance in some cases.
Infor’s Agentic Orchestrator, now in limited availability, is designed to coordinate multiple AI agents across enterprise workflows.
The system supports orchestration of complex tasks, interoperability across applications using an open Model Context Protocol, and new observability tools to improve transparency and control.
Customer feedback included Zoaib Saifuddin, general manager of IT at AMADA America, who said: “Since moving to Infor’s multi-tenant cloud, we see improvements appear in the system without having to request them.
Infor Agentic Orchestrator is the next step in that evolution: instead of our service engineers searching for answers, the intelligence comes to them.”
Vera Janssens, supply chain analyst at Coram International, said: “With Infor’s AI driven Pick Path Optimization, we have elevated our warehouse operations to the next level.
“By intelligently leveraging real time data, we achieve 15 percent faster picking and 25 percent less travel distance. This leads to better utilization of our workforce and reduces our dependence on temporary staff.”
Jamarl Scace, digital and IT lead at Kattsafe, added: “With Infor Velocity Suite, we can grow rapidly without expanding resources at the same pace.
“Starting with customer order entry as our first automation, it provided a simple, practical path to AI – freeing our team to focus on higher-value customer engagement. We’re excited to expand AI across more processes to drive even greater efficiency.”
The findings also suggest broader concerns around trust and readiness. Around 27 percent of respondents questioned whether their data is mature enough for AI, while 31 percent expressed discomfort with autonomous agents handling critical business processes.
On average, nearly half of AI-generated outputs still require manual review.
Infor said the latest updates are designed to address these challenges by providing more industry-specific AI capabilities, improved governance, and clearer pathways from deployment to measurable business outcomes.
