Infor Strengthens Enterprise AI Governance to Improve Security, Compliance and Accountability

Artificial intelligence (AI) is becoming an essential part of enterprise resource planning (ERP) and business operations. Organisations are increasingly using AI-powered applications to automate workflows, analyse business data, improve decision-making, and enhance productivity. However, as AI adoption expands, businesses must also address growing concerns around data security, regulatory compliance, transparency, and accountability.

Infor is strengthening its enterprise AI governance approach to help organisations adopt AI technologies responsibly while maintaining control over sensitive business information. The company’s strategy focuses on embedding security, governance, and accountability into AI-powered enterprise applications, allowing businesses to benefit from intelligent automation without compromising operational standards.

For industries such as manufacturing, healthcare, distribution, and financial services, responsible AI governance is particularly important because business decisions often involve confidential information, regulatory requirements, and complex operational processes.

Infor Extends AI Governance Through Its GRC Platform

A key part of Infor’s approach is the expansion of its Governance, Risk, and Compliance (GRC) capabilities. The company is extending existing governance controls to cover AI initiatives and autonomous agents alongside traditional business risks.

As AI agents gain access to enterprise applications and participate in business processes, organisations need visibility into what these systems can access, which activities they can perform, and who is responsible for their decisions.

Infor’s enhanced governance framework introduces several important capabilities:

AI Use Case Registry: Helps organisations register AI initiatives before production deployment, including ownership, data classification, risk categories, and regulatory impact.
Agent Permission Management: Ensures AI agents operate within defined access permissions and organisational policies.
Human Approval Workflows: Allows businesses to require employee approval for sensitive or high-impact decisions.
Audit Trails: Records AI activities to support transparency, traceability, and compliance reviews.
Risk Monitoring: Helps identify potential security, operational, and regulatory risks associated with AI adoption.

These controls are designed to make AI activities more visible and manageable while allowing organisations to introduce automation into business-critical processes.

Security and Accountability Across AI Operations

Infor is also focusing on security at the platform level. Its governance strategy combines Infor GRC, Infor OS Security, and the Infor Data Platform to establish a connected framework for managing AI-related risks.

Each component serves a different purpose:

Infor GRC provides governance policies, risk assessments, AI initiative registration, and audit management.

Infor OS Security manages identities, access permissions, and security policies to ensure AI agents operate within authorised boundaries.

Infor Data Platform provides trusted enterprise data through data classification, lineage, industry-specific data models, and traceability.

Together, these technologies help businesses understand how AI systems use enterprise information and maintain control over automated activities.

Infor also emphasises human oversight, explainable AI logic, and recorded agent actions. This approach is particularly important when AI systems are involved in financial approvals, procurement decisions, supplier management, and other sensitive business operations.

Industry-Specific AI Helps Reduce Operational Risks

Another important element of Infor’s strategy is its focus on industry-specific AI rather than relying entirely on general-purpose AI tools.

Infor Industry AI agents are designed around the business processes, terminology, and data requirements of specific industries. This helps AI systems understand operational context before recommending or executing actions.

For example:

Manufacturing: AI agents can monitor production performance, identify operational constraints, and support corrective actions.
Supply Chain: Agents can analyse inventory levels, supplier performance, and demand changes to support planning decisions.
Healthcare: AI-powered procurement processes can consider regulatory requirements and supply continuity.
Distribution: Intelligent agents can support purchasing, vendor management, product availability, and customer operations.

By combining industry-specific data models with governance controls, Infor aims to make AI-generated decisions more relevant, traceable, and reliable.

Enterprise AI Research Highlights Governance Challenges

Infor’s second Enterprise AI Adoption Impact Index, based on a YouGov survey of 2,111 business decision-makers across seven markets, highlights the growing challenges businesses face when scaling AI.

Some important findings include:

33% of respondents identified data security, data sovereignty, or compliance as their biggest barrier to advancing AI strategies.
15% said no individual or team had clear primary responsibility for AI governance.
23% identified CEO or executive leadership as responsible for AI governance.
22% assigned responsibility to CIO or CTO leadership.
73% of manufacturing respondents said off-the-shelf AI solutions did not adequately meet their industry’s requirements.

These findings highlight why organisations need stronger governance structures, clear accountability, and AI systems that understand industry-specific business requirements.

What Infor’s AI Governance Strategy Means for Businesses

Infor’s expanded AI governance capabilities represent an important development in enterprise software management. As organisations introduce autonomous AI agents into ERP, finance, procurement, and supply chain operations, managing security and accountability becomes just as important as improving productivity.

By integrating governance, identity management, trusted data, and human approval processes, Infor aims to help businesses scale AI adoption while maintaining operational control.

The company’s approach also highlights a broader shift in the ERP market. AI systems are moving beyond basic recommendations towards executing business activities, making transparent permissions, reliable data, and detailed audit records essential requirements.

For organisations planning to expand AI adoption, Infor’s strategy offers a framework for balancing automation with security, regulatory compliance, and human responsibility.

Overall, Infor is positioning AI governance as a foundation for enterprise AI adoption. Its focus on security, accountability, industry-specific intelligence, and auditability aims to help businesses build trust in AI while preparing for increasingly automated enterprise operations.