Infor Expands Industry AI to Help Businesses Overcome the Limitations of Generic AI

Key Takeaways

• Infor has unveiled an expanded Infor Industry AI architecture alongside the next evolution of its Infor Velocity Suite.
• New capabilities include industry-specific AI agents, personalized user experiences, enterprise-wide governance and improved coordination between AI agents.
• Infor’s research found that businesses across multiple markets believe off-the-shelf AI tools do not adequately address their industry’s specific requirements.
• The platform is designed to connect with third-party applications and existing AI orchestration tools.
• Infor reports that customers can process shipments up to 60% faster and achieve time savings of up to 90% across selected workflows.
• The announcement highlights the growing importance of industry-specific knowledge, security, governance and accountability in enterprise AI adoption.

Infor Strengthens Its Industry-Specific AI Strategy

Infor has announced an expanded version of its Infor Industry AI architecture, introducing additional AI agents, adaptive user experiences and enhanced governance capabilities designed to help businesses deploy artificial intelligence across their operations.

Announced on October 6, 2026, the expansion also includes the next evolution of the company’s Infor Velocity Suite. The initiative aims to help organizations move beyond isolated AI experiments and integrate intelligent automation into core business processes.

Infor’s announcement is supported by the second edition of its Enterprise AI Adoption Impact Index, which surveyed more than 2,000 business decision-makers across seven markets. The research indicates that many businesses believe generic AI solutions struggle to address the specialized workflows, data requirements and regulatory considerations of their industries.

According to Infor, enterprise AI must understand how a particular industry operates to deliver reliable and measurable business outcomes.

Four Pillars Define the Expanded AI Architecture

Infor Industry AI is organized around four core pillars designed to help businesses deploy and manage AI across their organizations.

1. Precise Outcomes Through Industry-Specific AI Agents

Infor is expanding its portfolio of AI agents with specialized capabilities grounded in industry processes and business knowledge. Rather than relying solely on general-purpose AI models, these agents draw on Infor’s Industry CloudSuites, Industry Process Catalogs and industry-specific language models.

This approach is intended to help AI agents interpret operational information more accurately and perform tasks relevant to specific sectors.

Infor reports that customers using this layer are processing shipments up to 60% faster. The company has also made its GenAI Knowledge Hub generally available, allowing customers to use Infor’s application and industry knowledge to build customized AI agents.

2. Open and Connected Enterprise Systems

The expanded architecture is designed to operate across an organization’s wider technology environment rather than being restricted to Infor applications.

It supports connections to non-Infor applications and existing orchestration and analytics tools, helping businesses integrate AI into their current systems without requiring a complete technology replacement.

Infor IQ provides a shared semantic layer that helps agents maintain a consistent understanding of business concepts and processes. Infor says its platform includes a catalog of more than 350 ready-to-use business use cases.

3. Personalized and Adaptive User Experiences

Infor’s Adaptive UX capability is designed to bring relevant information into a single, role-based experience.

Instead of navigating multiple applications and screens to collect information, employees can access the details required for a decision in a consolidated view. For example, a purchasing professional could review product information, quoted prices and delivery dates within one workflow.

Users can interact through Infor’s GenAI Assistant or AI assistants they already use. Infor reports time savings of up to 90% across selected procurement, supply chain, manufacturing and sales workflows. These figures are company-reported results and may vary by implementation and business process.

4. Governance, Security and Accountability

The fourth pillar focuses on helping businesses manage AI activity through built-in governance, risk and compliance capabilities.

The architecture incorporates permission structures, human-approval workflows and audit trails. These controls are designed to help organizations monitor AI decisions, understand the actions agents perform and maintain accountability for critical business processes.

Infor also reports that customers can achieve up to a 90% reduction in auditing costs associated with access management.

As AI agents take on more responsibility, these controls become increasingly important for organizations that need to balance automation with security, regulatory compliance and human oversight.

Research Highlights the Limitations of Generic AI

Infor’s Enterprise AI Adoption Impact Index identifies a gap between investment in artificial intelligence and the business value organizations expect to achieve.

The company’s research suggests that the limitations of generic AI become more visible as businesses expand beyond pilot projects and introduce AI into complex operational processes.

Industry-specific requirements can make a substantial difference. A food manufacturer may need to account for product specifications and supplier traceability, while an automotive business must handle vehicle identification data and specialized parts information. Generic AI systems may not understand these distinctions without the appropriate business context.

The research also highlights governance as a concern. As organizations give AI agents greater responsibility, they need clear accountability for decisions, defined permissions and reliable records of actions taken.

These findings reinforce the need to consider industry knowledge and operational controls alongside AI model capabilities.

What the Expansion Means for Enterprise ERP

Infor’s announcement reflects a broader shift in enterprise software, where AI is increasingly expected to execute tasks and coordinate workflows rather than simply generate recommendations.

For ERP users, this could mean more intelligent support for procurement, production, supply chain management, sales and distribution. AI agents with access to relevant business context could help reduce repetitive work, accelerate decisions and improve coordination across departments.

However, successful deployment will depend on data quality, integration, process design and governance. Organizations will also need to evaluate reported benefits against their own operational requirements.

Infor’s emphasis on an open architecture may appeal to businesses that want to introduce industry-specific AI while retaining existing applications and technology investments.

Conclusion

Infor’s expanded Industry AI architecture represents another step toward integrating AI agents directly into enterprise operations.

By combining specialized industry knowledge, connected systems, adaptive user experiences and built-in governance, the company aims to help businesses move from AI experimentation to practical, measurable results.

As enterprises explore increasingly autonomous workflows, the differentiator may not simply be access to advanced AI models. It may be how effectively those models understand industry processes, operate within business controls and deliver reliable outcomes.