Why enterprise AI struggles to scale and how Infor changes the equation

The conversation around enterprise AI is shifting. Across industries, organizations are no longer asking if they should adopt AI, but why so many initiatives still struggle to deliver measurable, repeatable value at scale.

According to new research from Nucleus Research, the answer has less to do with algorithms and far more to do with the foundation beneath them. As Nucleus Research puts it, "the real differentiator is no longer the sophistication of the model, but the quality and consistency of the data feeding it."

This insight sits at the heart of why Infor™'s approach to AI is resonating with customers, and why the findings in Nucleus' latest research matter.

The hidden cost of fragmented AI

Many enterprises enter AI initiatives with strong intent, only to encounter unexpected friction. Nucleus found that organizations running disconnected ERP, supply chain, manufacturing, workforce, and customer systems face persistent challenges: delayed insights, inconsistent results, and rising costs just to make AI work across silos.

In fact, the research highlights that integration alone often consumes 30 to 40 percent of total AI project costs, as models must reconcile fragmented and inconsistent data before generating value.

The result? AI that looks promising in pilots but struggles to reflect real operational conditions or scale beyond isolated use cases.

As the report states: "AI fails when data is fragmented."

A different foundation for enterprise AI

Rather than layering AI on top of existing silos, Infor takes a fundamentally different approach. Intelligence is embedded directly into a unified ecosystem designed around how industries actually operate.

Nucleus points to the Infor Industry Cloud Platform as a key differentiator, bringing together ERP, supply chain, manufacturing, workforce, and advanced solutions and technologies on a shared data fabric. This allows AI to operate on governed, near real-time data across financials, production, quality, logistics, and customer interactions.

As Nucleus Research notes, "Infor's shared data fabric ensures every prediction is powered by the same real-time operational truth."

The impact is immediate and compounding. By consolidating data from different enterprise applications onto a single data fabric, customers unlock cleaner signals, faster deployment cycles, and stronger predictive performance.

Measurable outcomes that matter

The Nucleus findings reinforce that Infor's approach isn't just architectural—it's economic.

Organizations consolidating on Infor reported:

• 37 percent lower integration and maintenance costs
  
• AI deployments up to 30 percent faster
  
• 10–20 percentage point improvements in model accuracy
  
• Implementation timelines shortened by as much as six months using preconfigured industry templates

These gains translate directly into business outcomes: more accurate predictions, faster decisions, and greater confidence in acting on AI-driven recommendations.

Infor Velocity Suite customers consistently validate this pattern.

• Endries International (Distribution): Saved 9,000 hours annually by combining AI-powered parts matching with automated document processing—achieving ROI in less than 90 days.
• Grosfillex (Manufacturing): Generated a 10% revenue increase within one week using AI-driven customer profitability insights, while reducing sales meeting prep time by 83% (from 3 hours to 30 minutes).
• Miller Industries (Automotive): Automated sales order creation processes, saving 3,000+ hours annually and achieving 98% faster order execution in under 60 days with AI-driven document processing.

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

From insight to action with Industry AI Agents

This integrated foundation is what enables Infor Industry AI Agents to move beyond insight and into execution.

Unlike generic AI assistants, Industry AI Agents are purpose-built for specific industry workflows—project management, production planning, maintenance, supplier collaboration, and more. Because they operate within the same data fabric and workflow context that supports daily operations, agents can act with speed, data accuracy, and industry relevance.

Nucleus Research emphasizes this distinction: "Infor's strength lies in deployable intelligence. AI built for execution, not experimentation."

Nucleus highlights that early adopters of Infor Industry AI Agents are able to scale AI-driven automation and insights up to 30 percent faster across adjacent business areas, without rebuilding integrations or retraining models from scratch.

This matters because enterprise AI success isn't defined by a single breakthrough, it's defined by how quickly and confidently organizations can extend value across the business.

Why this matters as AI scales

As AI matures from experimentation to execution, Nucleus argues that simplification, not additional tools, will define the next wave of ROI. Vendors that can unify data, workflows, and user context will be best positioned to deliver AI that improves continuously over time.

Infor's industry-specific CloudSuites backed by a unified cloud platform with precise, value-guided AI experiences, align closely with this shift. By controlling the full feedback loop, from data capture to action, Infor creates an environment where intelligence and value compound, rather than stall.

Or, as Nucleus puts it, "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."

Learn more

The full Nucleus Research white paper dives deeper into the findings, benchmarks, and real-world implications behind these results.

Read the full report to see how Infor is helping customers move from AI experimentation to enterprise-wide impact.