End users in 2025 stopped seeing AI as a futuristic buzzword for enterprise planning. What had long been pitched as a future differentiator finally began delivering measurable operational benefit this year. According to ERP Today’s reporting on the manufacturing sector, 82% of companies increased technology budgets specifically to build AI-ready ERP capabilities. It is a clear sign that competitive pressure is now tied directly to intelligent automation and decision support.
At the same time, ERP vendors shifted strategies. Rather than layering AI on top of long-standing workflows, they redefined the role ERP plays inside the business. ERP systems now extend beyond recording what has happened to guiding users toward what should happen next. From mid-market players outlining “assist, advise, act” frameworks to large vendors positioning ERP as an AI-first solution, AI has evolved from a feature into the core of how ERP delivers operational value.
This year’s trends made it clear that organizations realizing value treated AI adoption as an operational and a governance shift. They understood that automating decisions demands the same rigor as automating transactions. Here is how AI in ERP moved from promise to performance through four drivers that shaped the market in 2025:
- Vendor strategy positioning ERP as the system where AI creates business value
- User experience transforming as conversational and agentic interactions replace traditional navigation
- Gaps in execution maturity showing how readiness determines which AI investments deliver outcomes
- Operational responsibility shifting as AI decision-making requires new governance and confidence controls.
AI is redefining how ERP operates today. The priority heading into 2026 is not simply to scale adoption, but to mature the structures that ensure AI improves performance without compromising trust.
Vendor Strategy Shifted
In 2025, ERP vendors reshaped their positioning around AI. Enterprise providers spoke openly about reorienting their platforms around intelligence-led operations. In interviews and product briefings, senior leaders described ERP not as an administrative system but as the place where AI can interpret business context, anticipate changes, and guide users toward the next best action. The emphasis moved from process automation and compliance to decision quality, speed, and resilience.
No longer just a feature that enhances the platform, AI now justifies having the platform in the first place. Automation can reduce effort, but AI can elevate performance. An ERP system must therefore guide end users through scenarios, highlight risks before they materialize, and surface opportunities while decisions are still fluid.
ERP Today’s coverage also showed how quickly mid-market vendors internalized this shift. Throughout the year, providers presented AI-first roadmaps with workflows designed around intelligence from the outset. Unit4 illustrated this with a maturity model built on “assist, advise, act,” positioning AI as a partner in operational decision-making rather than simply a tool for task reduction. This framing resonated because it translated AI adoption into a sequence that organizations could execute: start by supporting the user, progress to informed recommendations, and ultimately allow the system to complete actions on the organization’s behalf.
This reframing pushed decision makers to reexamine ERP’s role in governance and productivity. Vendors set new expectations: improved insight quality, reduced process latency, and the ability to operate at enterprise speed even during disruption. ERP now competes on intelligence. With the market aligning around this vision, ERP buyers enter 2026 asking a new question—not which ERP will automate best, but which ERP will decide best.
User Experience Transformed
Another development in 2025 was a shift in how users interacted with ERP systems. Conversational access and embedded AI assistants began functioning in live environments, changing the basic expectations of how ERP can be leveraged. Historically, users needed deep process knowledge to locate transactions and assemble insight from data. That burden is fading. Users increasingly issue requests in natural language, and systems interpret intent, execute steps, and confirm results.
ERP Today’s Sapphire coverage offered tangible examples of this transition. Agent-based automation surfaced exceptions to planners before they initiated any search, prompting early intervention. Vendors also showcased generative capabilities able to translate large data sets into concise explanations of causes, risks, and recommended actions. What previously required dashboards, filters, and reports now is delivered as guidance at the moment when decisions need to be made.
As insight moved closer to action, the structure of work also changed. Teams spent less time collecting data and more time evaluating outcomes and validating judgments. Decisions accelerated not because users worked faster, but because systems eliminated delays between recognizing a problem and responding to it. ERP Today documented multiple scenarios where AI-driven recommendations replaced static processes, allowing parameters such as supplier disruption or demand variability to dynamically influence workflows.
With ERP becoming less visible to users but more influential in their daily work, new expectations emerge. When systems proactively suggest, execute, or escalate, the user’s responsibility shifts from task completion to oversight. In other words, accountability still matters. Effective use of AI-driven ERP depends on understanding how the system reaches its conclusions and when human intervention is needed. This marks a fundamental change in the human–system relationship, and it places new expectations on leaders to ensure confidence in the decisions AI generates.
Execution and Readiness Merged
As AI capability expanded, execution maturity became the clearest determinant of business impact. Organizations that prepared for AI as a change in operations (rather than a feature rollout) saw the strongest outcomes. Those already operating in the cloud, with aligned data structures and clear ownership of processes, were able to embed intelligence into planning and execution cycles with ease.
Others struggled to progress beyond pilot stages. Deployments stalled when ERP data lacked coherence across functions or when automated guidance conflicted with entrenched workflows. In these cases, AI did not expose flaws in technology as much as lack of preparedness in governance and accountability. The difference between value realized and value anticipated came down to whether leaders treated AI as a workflow enhancement or a shift in how decisions are made and measured.
ERP Today’s transformation coverage highlighted the need for preparation across multiple dimensions: data quality and integration, clarity about when AI augments judgment versus takes primary responsibility for the decision, and alignment on who owns outcomes. Those that framed AI adoption within this lens advanced quickly; those that treated AI as a technical upgrade faced rework and hesitation.
This divide will deepen as AI continues to reveal operational gaps. In 2025, that revelation became a forcing function for ERP leaders to standardize data, simplify processes, and strengthen cross-functional governance before expanding autonomous capabilities any further.
Operational Responsibility Shifted
ERP has long been accountable for data accuracy and process compliance. In 2025, it became accountable for performance outcomes as well. Agentic AI—highlighted in supply chain and service operations coverage—began to act directly, not merely prompting users for approval. Systems responded to conditions dynamically, adjusting plans or routing work while situations were still unfolding.
This development raised strategic questions documented in ERP Today interviews, such as:
- How are decisions reviewed when humans did not make them?
- What constitutes a “business-approved” risk tolerance for model-driven actions?
- Which roles are responsible for retraining or overriding automated behavior?
Organizations that invested in guardrails such as clear escalation paths, auditability of model decisions, and transparency into the rationale behind recommendations advanced automation with confidence. Meanwhile, others had to slow deployment to preserve oversight.
The shift is subtle but deeply felt. ERP is no longer a passive system invoked by the business; it is an active participant in running the business. That requires leaders who are prepared to manage digital judgment, not just digital workflow.
ERP’s AI Shift: A Business Performance Imperative
Decidedly, 2025 marked a turning point in ERP evolution. AI integration matured from isolated proofs of concept to operational capabilities with measurable influence on enterprise performance. ERP Today’s reporting throughout the year showed:
- Vendors reimagining ERP as a decision engine
- Users engaging less in navigation and more in judgment
- Technical readiness dictating progress
- Governance structures adapting to maintain trust in automated actions.
These changes position ERP at the center of business execution. As organizations head into 2026, acceleration alone cannot define AI strategy. Leaders must reinforce accountability, transparency, and performance measurement in step with expanding intelligence. Companies prepared both architecturally and culturally will turn AI progress into operational advantage.
Looking to 2026, three priorities stand out:
- Copilot-embedded ERP workflows moving from dashboards to live operational support
- Composable ERP architectures enabling plug-in specialized AI modules without full platform upgrades
- Enhanced governance and explainability ensuring transparency, auditability, and ethical compliance.
With AI reshaping ERP faster than many expected, successful AI integration demands this mindset shift: ERP is not a system to modernize, but a system that continuously modernizes the business.
What This Means for ERP Insiders
The shift to AI-first ERP means the competitive edge now comes from how well the system can guide decisions. The focus heading into 2026 is not which platform automates the most workflows, but which one improves judgment and resilience under pressure. Due diligence must focus on how AI evaluates scenarios, escalates risk, and ensures oversight when recommendations become automated actions. AI readiness is a business capability; clean data structures, cloud operating models, and shared accountability are now prerequisites for ROI.
Agentic ERP is changing daily work fast. ERP Today coverage showed AI interventions surfacing disruptions and prompting corrective actions before users intervened, whether through SAP’s agentic workflows or Oracle’s supply chain AI agents. Conversational access, proactive exception handling, and agent-led automation mean less time navigating screens and more time validating the right call. Training must now cover when to trust automation and when to challenge it. Trust grows when end users understand why the system recommended a path; ERP leaders should ask vendors how explainability and escalation are built into their design.
Discipline around testing, data, and governance is the new differentiator. Transformation leaders learned in 2025 that readiness determines returns. ERP Today stories on automated testing and the urgency around cloud-native GRC reinforced one message: AI amplifies the state of the estate it enters. Strong data foundations and continuous validation produce momentum, while fragmented processes and audit gaps slow everything down. Heading into 2026, success depends on control and confidence; on the ability to scale AI-enabled ERP without losing stability or accountability.
