From predictive analytics to generative content, executives are exploring how to apply AI across their operations. Yet one of the most strategic enablers of AI is hiding in plain sight—and it is neither a model nor a dataset.
It is your ERP system.
AI tools may promise transformation, but they can only amplify what already exists. When ERP systems are fragmented, outdated, or underutilized, AI compounds dysfunction rather than creating value.
The smartest AI move most companies can make right now? Modernizing their ERP system.
2026 Clash of the Titans
SAP, Oracle, Microsoft, and Infor each have a variety of systems that can support data-driven decision-making. We surveyed customers of these four vendors to find out what their selection and implementation process was like.
AI Effectiveness Is Tied to the Systems That Feed It
Every AI capability—whether embedded in a vendor solution, built internally, or delivered through copilots and agents—depends on trusted data and stable system context. ERP, alongside core systems like CRM and SCM systems, is intended to serve as the system of record for that context.
Before implementing AI, organizations need to ask:
- Are core workflows defined and executed consistently enough to support automation and AI-assisted decision-making?
- Are master data structures governed, secure, and aligned to shared business definitions?
- Can critical transactions be traced end to end in a way that supports transparency, auditability, and responsible AI use?
If the answer is no, then implementing AI won’t be the “game changer” you were promised.
ERP Modernization Creates the Foundation AI Requires
Moving to a modern ERP system prompts organizations to confront strategic decisions that simultaneously help them prepare for AI implementation. These decisions include:
1. How will data quality be governed across the organization?
ERP modernization typically requires organizations to assign data ownership, standardize definitions, and implement controls for quality and consistency. These same governance structures are essential for AI, especially when it comes to ensuring data privacy, security, and responsible use.
2. Which processes should be standardized to support reliable intelligence?
ERP implementation exposes process variation across sites, business units, and acquired entities. Standardizing processes enables more consistent data capture, which is also essential for AI.
For example, when the ERP system captures delivery timestamps in a consistent format, AI models can more effectively learn patterns in delivery delays. Over time, the system can reliably flag when a supplier is trending toward late shipments.
3. How will we prepare the organization to adopt new ways of working?
ERP modernization is often the first large-scale transformation employees experience. Leaders must decide how to use the ERP rollout to build organizational muscle around change: training users to interpret system outputs, reinforcing accountability for data accuracy, and embedding digital tools into daily work.
These same capabilities will determine whether future AI tools are embraced or ignored.
Reframing the AI Roadmap Around ERP Strategy
1. Baseline assessment
Evaluate ERP data quality, process maturity, system architecture, and governance controls to identify constraints that would limit AI success.
2. ERP modernization planning
Determine whether reimplementation, upgrade, or targeted remediation is required, and align this work with your broader business and technology strategy.
3. AI use case prioritization
Identify AI opportunities closely tied to ERP domains—such as forecasting or spend analysis—and assess them based on data readiness, value, and risk.
4. Pilot, validate, and govern
Run controlled pilots using governed ERP data, measure outcomes, and establish AI governance and oversight mechanisms in parallel.
5. Scale with confidence
Embed successful AI capabilities directly into ERP workflows, reinforcing data governance, security, and user adoption as AI scales.
Treat ERP as Your AI Enabler
AI integration depends on ERP discipline—trusted data, standardized processes, clear governance, and an operating model designed to support intelligent systems.
Panorama Consulting Group works with executive teams to move from experimentation to scalable, responsible AI. Contact us below to learn about our AI readiness services.
