ERP evolved over decades through the combination of technology, industry knowledge and the realities of running a business. Vendors built the applications supporting finance, procurement, manufacturing, supply chain and HR, while customers shaped those systems around their processes, data, business rules, industry requirements and operational needs. Implementation partners connected the pieces, addressing complexities and exceptions that rarely fit neatly into standard software. Together, they built the ERP fabric that companies still rely on today.

That fabric was built for a different rhythm. Major implementations and upgrades were followed by stabilization and years of use. Cloud changed the cadence. Vendors now deliver capabilities continuously, with AI and automation moving into everyday workflows. Customers still have to clean data, change processes, train employees and decide which capabilities they are ready to trust.

Neither side is necessarily moving at the wrong speed. Vendors have to keep their products relevant, while customers cannot casually change how finance, manufacturing or supply chains operate. The problem is the widening gap between what ERP can do and what companies are ready to adopt. Disclosure: KramerERP provides paid research, advisory and consulting services to technology companies, including ERP and data vendors listed in this article.

I have been following this progression because it changes ERP’s role in the business. In a Forbes analysis of ERP as the execution layer , I wrote about AI, APIs, workflows and automation recognizing changing conditions and initiating authorized action. My ERP Today analysis of event driven agentic ERP looked at what happens when a business event can start the next step without someone having to find the problem first.

A supplier misses a delivery, inventory falls below plan or production capacity changes. In many ERP environments, employees still have to connect the information and coordinate a response. An event driven environment can identify the affected process and begin an authorized workflow. Faster action, however, raises the stakes for data quality and controls. As I argued in my InfoWorld work on trusted context , AI decisions depend on consistent definitions, permissions and the business meaning behind the data.

The opportunity is not more AI. It is trusted execution. That requires vendors and customers to work together on readiness, adoption and measurable business outcomes.

The pace difference is real. A vendor can release new capabilities in weeks, while a customer may need months to resolve data ownership, simplify customizations, change approvals and prepare employees without disrupting operations.

Some companies also operate across acquired businesses, multiple ERP generations and processes that were tailored over many years. That history cannot just be discarded. Some customization protects an important industry requirement. Some is an old workaround nobody wants to own. Knowing the difference requires people who understand the operation, not just the application.

Vendors know which ERP capabilities they offer, but may not see where customers still depend on spreadsheets or manual workarounds. Customers know where the work gets stuck, but may not realize what their existing ERP can already do. Closing the gap means connecting that knowledge to better decisions and measurable outcomes.

The ERP fabric is both an asset and a constraint. Longstanding processes and controls need another look as ERP evolves. The question is what to preserve, standardize or automate, and where people should keep authority.

What Adoption Looks Like In Practice

ERP vendors are tackling the gap at different points in the customer relationship. SAP’s Foundational, Advanced and Max Success Plans and IFS Success focus on ongoing engagement. FastTrack for Microsoft Dynamics 365, Epicor’s Signature Methodology and QAD Champion Pace address implementation. Oracle’s AI Success Navigator connects implementation guidance with release planning and ongoing AI adoption. Infor uses forward deployed engineering supported by its AI Adoption Hub architecture. These approaches are not interchangeable, but each addresses part of the adoption challenge.

That distinction matters. Getting ERP live and turning new capabilities into operating results are different responsibilities. Implementation methods can reduce project risk. Customer success needs to help organizations decide what to adopt next and how to measure the results.

Customer examples help show what adoption looks like in the operation. Infor reports that Team Air Distributing reduced time spent resolving credit inquiries and sourcing inventory. QAD reports that Amtico improved overall equipment effectiveness by 14 percent after connecting QAD Redzone Connected Workforce with ERP. Epicor says Tilton Group reached 99 percent forecast accuracy using Epicor Kinetic Cloud and Epicor Inventory Planning & Optimization. IFS reports that TOMRA North America improved first time fix rates and operational efficiency.

These are results reported by vendors, not proof that a specific support or customer success program delivered them. But they show what matters most: how the business performs. For manufacturers, that may be throughput and quality. For distributors, sourcing and fill rates. For field service, first time fixes. For professional services, utilization and project margins. The measure of success is not how many features customers use, but what improves in their business.

Traditional support still matters. ERP must run reliably, integrations must work and technical issues need to be resolved. But a company can have excellent uptime and still use only a fraction of the system. It can move to cloud without simplifying its processes or license AI without putting it to work.

In my Forbes work on the enterprise operating model , I made a related point. A project can meet its technical milestones while decisions remain slow, data stays disputed and manual handoffs continue. The software changed, but the business did not. Part of that adoption gap is tied to the ERP fabric built over decades. Established processes, customizations and workarounds do not disappear with a new release.

Support teams often see the symptoms through recurring issues and tickets. Customer success needs to connect those problems to what is holding adoption back and help customers decide what to change next. Sometimes that means making better use of existing capabilities. Other times, it means waiting until the data, processes and people are ready.

That is where the Success Advisor can make a greater impact. Support teams see recurring issues, while implementation teams understand how the system was configured and why. The Success Advisor needs to work closely with both teams, connecting their knowledge of the customer’s ERP fabric with the business priorities, readiness and adoption challenges that need attention.

Where are employees still relying on workarounds? Which customizations are necessary and which should be reconsidered? What business outcomes need to improve? If AI starts recommending or taking action, is the data ready and who owns the decision? These are the questions that help determine what customers can trust and put to work.

Customers are also at different stages. Some are still stabilizing ERP, others are simplifying years of customization and some are ready for automation or limited AI authority. The Success Advisor helps bring the right people and expertise together, identify the next step and measure whether it improves how the business operates.

How Vendors And Customers Close The Adoption Gap

Closing the gap calls for a shared plan built on trust. I would focus on five areas.

First, start with the business outcome, not the release calendar. Agree on the process to improve, how progress will be measured and who owns the result. More feature use means little if the business does not improve.

Second, confirm readiness before expanding authority. Data, integration, security, governance, process ownership and workforce preparation all matter. If those are not ready, saying not now may be the right answer.

Third, bring industry knowledge into customer success. Manufacturers, distributors, field service companies and professional services firms measure performance differently. Vendor teams need to understand those operations and connect software adoption to business measures.

Fourth, expand AI authority in stages. Begin with assistance, move to recommendations and controlled execution, then grant more authority only after consistent results. Trust is earned in production. Results set the boundary for what AI can do next.

Fifth, make success continuous. Vendors and customers should review what changed, what worked, what caused friction and what comes next. Adoption does not end at go live.

The ERP fabric is evolving, not disappearing. Vendors will keep releasing capabilities while customers move at different speeds. Customer success should connect the two, with a Success Advisor helping set priorities, address readiness and measure outcomes as ERP takes on more execution.

Customers also need an AI strategy of their own, not one defined by a vendor roadmap. It should establish business priorities, trusted data requirements, decision rights, security, governance and accountability for work AI can recommend or execute. Without that direction, individual AI features can accumulate without a consistent operating model.

That strategy will need to evolve as AI receives more authority and employee responsibilities change. In the next part of this series, I will explore the customer AI strategy needed to manage those decisions over time.

Both vendors and customers helped build the ERP fabric we have today. Closing the gap between innovation and adoption is their next shared responsibility.

Technology enables transformation. People determine the outcome.