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How Infor prepares its customers for AI success

A N A L Y S T

Cameron Marsh

The Bottom Line As organizations move from AI experimentation to enterprise-scale execution, the real differentiator is no longer the sophistication of the model, but the quality and consistency of the data feeding it. Nucleus found that organizations operating across multiple point solutions face persistent accuracy gaps, delayed insights, and higher integration spend, often 30 to 40 percent of total project cost, because AI must reconcile fragmented, inconsistent information before it can generate value. Infor’s unified ecosystem flips this model. By consolidating data captured from different enterprise applications such as ERP, WMS, WFM, CPQ, PLM, MES, supply chain, and operational workflows onto a single data fabric, customers unlock cleaner signals, faster deployment cycles, and stronger predictive performance. Organizations consolidating on Infor report 37 percent lower integration costs, AI deployments up to 30 percent faster, and 10 to 20 percentage point gains in model accuracy, supported by embedded analytics and preconfigured industry templates that reduce implementation timelines by as much as six months. For enterprises seeking repeatable ROI, not isolated wins, Infor’s integrated architecture and domain-specific design offer a more reliable path to sustained AI impact, reduced operational drag, and a foundation capable of scaling intelligence across every corner of the business.

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Overview As organizations accelerate AI adoption, many find that results fall short not because of the algorithms themselves, but because of the fragmented data and disconnected workflows feeding them. Most enterprise environments still rely on a patchwork of point solutions, with separate ERP, WMS, CRM, CPQ, and supply chain systems each storing partial, inconsistent, or outdated information. When AI models attempt to draw insight from these disparate sources, they inherit the noise: mismatched definitions, missing context, and manual data reconciliations that introduce latency and erode accuracy. The result is AI that fails to reflect real operational conditions and automation initiatives that deliver limited or unreliable value.

Infor approaches this challenge differently. Rather than asking customers to overlay AI onto existing silos, Infor embeds intelligence within a single, integrated ecosystem. The Infor Industry Cloud Platform provides a common Data fabric, Machine Learning models, Agent builder, a Workflow orchestration engine, and event models to deliver rapid ROI grounded in industry-specific use cases. Infor’s CloudSuite ERP, along with strategic complementary solutions, including CPQ, MES, WMS, HCM/WFM, PLM and more, as well as third-party systems, all use this common infrastructure. This enables AI to act on consistent, near real-time business data spanning financials, production, quality, logistics, and customer interactions. Predictive and prescriptive models for pricing, maintenance, or supply risk, for example, are trained on the same governed data that drives day-to-day decisions, improving both precision and trust.

By consolidating these core business functions under one roof, organizations eliminate the cost and complexity of synchronizing multiple vendors’ systems while establishing a foundation for scalable and high-quality AI output. The benefits compound over time, with fewer integration points to maintain, faster deployment of new use cases, and higher model performance due to cleaner, continuously updated data streams. Infor’s industry-specific and feedback-driven strategy positions its customers to achieve tangible, repeatable AI value rather than isolated experimentation.

AI fails when data is fragmented. Infor’s shared data fabric ensures every prediction is powered by the same real-time operational truth.

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Why Organizations Choose Infor Infor’s differentiation lies in its ability to enable customers to translate AI potential into everyday business value, tailored for customer’s industry and business processes. The vendor doesn’t treat AI as a technology experiment, but as a practical tool for solving real operational problems. Its approach combines three defining characteristics: a focus on practical, results-driven AI, technology built around the way customers actually work, and a partnership model that keeps innovation aligned with user needs.

A Practical Approach to AI Infor prioritizes deployable intelligence over experimentation. Rather than selling AI as an abstract concept, the company focuses on operational use cases including recasting, pricing, production planning, and supplier collaboration, where value is measurable and repeatable. Customers benefit from AI that is easy to activate, trained on real business data, and aligned with KPIs that executives already track. This practical approach translates to faster adoption and clearer ROI visibility, making AI an enabler of productivity rather than an IT project.

Purpose-Built Solutions Infor has invested in building technology that reflects the daily operations of users across Infor’s focus industries. Each Infor product is designed with domain-specific workflows, data models, terminology, and compliance standards already embedded, enabling teams to start with tools that fit their processes rather than force new ones. The vendor’s user-driven design philosophy, shaped through direct engagement with its customer base, ensures that enhancements and AI features address real bottlenecks, not hypothetical ones. The result is higher user satisfaction, less resistance to change, and a smoother path to realizing AI-driven improvements.

Strong Vendor - Customer Partnership Infor maintains a strong hands-on relationship with its customers, working collaboratively through implementation, industry councils, community-led user groups, and ongoing releases. This partnership model ensures that new AI capabilities reflect evolving customer needs and market conditions. Continuous updates deliver incremental innovation without disruption, while advisory programs and Infor’s Process Intelligence solution help organizations identify where automation and AI can create the most value. Many Infor customers reported a feeling of confidence in long-term alignment between Infor’s

From advisory councils to co- developed features, Infor’s close customer collaboration turns feedback into continuous improvement.

Infor’s strength lies in deployable intelligence. AI built for execution, not experimentation.

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product evolution and their own business strategy, an important factor in sustaining competitive advantage as AI matures.

Primary Benefit Areas Infor’s unified ecosystem delivers measurable business value by consolidating multiple operations under a single platform. Customers that expand their Infor footprint, or replace disconnected point solutions, consistently report lower integration costs, faster deployment timelines, and stronger AI outcomes.

Lower Integration Costs

Infor’s connected architecture eliminates many of the hidden expenses associated with integrating and maintaining separate vendor systems. Through the Infor Industry Cloud Platform, data flows automatically across applications, including ERP, SCM, PLM, HCM, MES, WMS, and more, without the need for extensive middleware or custom code. Nucleus found that organizations consolidating on Infor reduce integration and maintenance costs by 37 percent on average, while also lowering long-term risk tied to third-party dependencies. The platform’s prebuilt industry frameworks and shared data fabric simplify deployment and governance, enabling IT teams to focus resources on strategic AI and automation initiatives rather than constant system upkeep.

Faster Time To Value

Infor customers reported that they achieved measurable business results in as little as nine weeks, approximately 54 percent faster than the industry average for comparable projects. This accelerated timeline stems from Infor’s modular design and preconfigured industry templates and industry data models that shorten implementation cycles and streamline user adoption. The shortened timelines stem from Infor’s modular design and preconfigured industry templates, which shorten implementation cycles by up to six months while expediting user adoption.

These same principles apply to AI adoption. Infor’s embedded approach, where predictive models and AI Agents operate within the same data fabric that supports daily operations, enables customers to move from pilot to production far more efficiently than those using disconnected point solutions. Nucleus expects early adopters of Infor AI Agents to scale AI-driven automation and insights up to 30 percent faster across adjacent business areas such as pricing, forecasting, and

Organizations consolidating on Infor cut integration and maintenance costs by an average of 37%, freeing IT to focus on innovation instead of upkeep

Early adopters of Infor AI Agents scale new use cases up to 40 percent faster, turning early wins into enterprise-wide impact.

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supplier collaboration. By leveraging a shared data foundation and pre- trained, industry-specific models, organizations can extend successful use cases without rebuilding integrations or retraining models from scratch.

Stronger AI Performance

Infor’s single data fabric ensures that AI models are trained and executed on clean, consistent, and context-rich information spanning finance, sales, production, quality, and logistics. This eliminates one of the most common causes of AI underperformance: fragmented, incomplete, or duplicated data across systems. Organizations leveraging Infor’s unified data structure report a 10 to 20 percentage point improvements in model precision and accuracy compared with those using federated data from multiple vendors. Many customers have reported increased accurately in models identifying true positives, for example, correctly predicting a delayed shipment or maintenance failure, versus false alarms. Embedded AI and predictive analytics within the Infor ecosystem enable models to continuously learn from live business events, improving relevance over time while reducing maintenance effort by up to 30 percent annually. For customers, this means better predictions as well as greater confidence in acting on them, turning AI from a proof-of-concept into a sustained performance advantage.

Looking Ahead As AI matures from experimentation to execution, enterprises are discovering that technology fragmentation, not model capability, is their greatest barrier to scale. Nucleus expects the next wave of ROI will not come from adding more tools, but rather from simplifying the environment they operate in. Platforms that unify data orchestration across multiple business functions under one roof are positioned to lead this shift. In this environment, Infor’s model aligns closely with where the market is heading, prioritizing integrated intelligence, faster iteration cycles, and measurable productivity gains.

For software vendors, this trend redefines competition. Success will depend less on offering the most advanced standalone model and more on delivering an environment where AI can perform consistently. Vendors that can control the data foundation, workflow context, and user interface will own the full feedback loop that makes AI both scalable and self-improving. Infor is positioned advantageously here: its industry-specific CloudSuites, unified data architecture, and embedded AI framework create a defensible ecosystem where value compounds

Embedded AI trained on governed, real- time data boosts accuracy and cuts model maintenance effort by up to 30% annually.

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over time. As the market shifts from isolated innovation to operational integration, vendors that can deliver both will lead the race towards enterprise AI ROI.