Reinventing ERP With Event-Driven Agentic AI
ERP has been the backbone of business operations for a long time, but most systems still work in a reactive way—waiting for manual input or scheduled updates.
That’s starting to change. Event-driven design and agentic AI are pushing ERP into a more responsive model—one where autonomous agents can act on real-time events and coordinate across systems. Imagine your inventory levels drop, and without anyone stepping in, procurement kicks off and logistics adjust automatically. That’s not just convenient—it’s the kind of efficiency businesses have been waiting for.
It won’t change overnight, and issues like security, governance and data quality are still hurdles. But the move from static systems of record to adaptive, collaborative platforms is already in motion—and it has the potential to fundamentally change how businesses run.
The real question: are companies ready—and are vendors moving fast enough—to make this new ERP model a reality? Read more in my latest Forbes article as I explore event-driven agentic AI in ERP.
@MoorInsStrat@Microsoft@MSFTDynamicsERP@MSDynCRMOnline@SAP@Infor@Oracle@OracleCloudERP@OracleCloudSCM@OracleCloudHCM@Acumatica@Epicor@Workday@ifs@SageERP@SYSPRO@salesforce
#ERP #SCM #CRM
https://t.co/k9qFcPCtWO
Picking a data platform used to be the strategy. Now it is the starting point.
No single platform does it all. Ingestion, governance, transformation, analytics and AI have to work across multi cloud and on premises environments without breaking identity, metadata or data quality. Performance matters, but consistency across distributed systems is the real test.
The role of CIOs and CDOs has changed. You are not buying a platform. You are designing an ecosystem. The questions are operational. Can you onboard new data quickly. Are business definitions consistent across systems. Do insights actually drive action inside the business.
AI raises the stakes. Once models start influencing customer, operational and financial decisions, governance cannot be an afterthought. A weak semantic layer becomes an operational and regulatory risk. The vendors that build interoperability and governance into the core architecture will win. The ecosystem is what you are really buying now. Check out my latest @Forbes article "Beyond The Enterprise Data Platform: Why Ecosystems Win".
@MoorInsStrat@Snowflake@databricks@cloudera@awscloud@MicrosoftFabric@Microsoft@IBM@Oracle@OracleCloud@Google@googlecloud@SAP@Informatica@collibra@Alation@dremio
https://t.co/Yb9jV4NHx4
Picking a data platform used to be the strategy. Now it is the starting point.
No single platform does it all. Ingestion, governance, transformation, analytics and AI have to work across multi cloud and on premises environments without breaking identity, metadata or data quality. Performance matters, but consistency across distributed systems is the real test.
The role of CIOs and CDOs has changed. You are not buying a platform. You are designing an ecosystem. The questions are operational. Can you onboard new data quickly. Are business definitions consistent across systems. Do insights actually drive action inside the business.
AI raises the stakes. Once models start influencing customer, operational and financial decisions, governance cannot be an afterthought. A weak semantic layer becomes an operational and regulatory risk. The vendors that build interoperability and governance into the core architecture will win. The ecosystem is what you are really buying now. Check out my latest @Forbes article "Beyond The Enterprise Data Platform: Why Ecosystems Win".
@MoorInsStrat@Snowflake@databricks@cloudera@awscloud@MicrosoftFabric@Microsoft@IBM@Oracle@OracleCloud@Google@googlecloud@SAP@Informatica@collibra@Alation@dremio
https://t.co/Yb9jV4NHx4
.@Acumatica Summit was recently in Seattle, where I had the chance to join Acumatica’s ERP podcast with Lauren O’Hara. We had a great conversation about ERP modernization, the real role of data, the importance of strong implementation and change management, and where ERP is headed next.
If you’re interested in ERP modernization and want to gain additional insights, you'll find value in listening in.
https://t.co/JO5fRsQqj7
@MoorInsStrat@JohnCaseCEO
#acumaticasummit
https://t.co/NhAGpeNxNm
.@SAP's Analyst Innovation Council started today in Atlanta. Much of the discussion is consistent with what I’m hearing across the ERP landscape that there is a shift toward intelligent and autonomous operations. That vision makes sense to me.
What I keep coming back to is pace. Vendors are innovating quickly, as they should. But many customers are still working through foundational data, governance and change management challenges. New capabilities only create value when organizations are ready to implement and operationalize them, and when the ROI is clear. I am seeing there is a real gap between what these platforms can deliver and what companies can realistically absorb.
The question I keep asking: should vendors keep pushing ahead at full speed or align more closely with where customers are in their readiness journey? That balance will play a role in shaping the next phase of ERP.
Stay tuned for more insights from the SAP Analyst Innovation Council.
@MoorInsStrat
Vision correction isn’t just about basic measurements anymore. It’s about how well complex data gets interpreted. What once relied on standard formulas and limited inputs now draws from detailed imaging and biometric data. The real shift is happening in the predictive layer, where advanced modeling helps reduce variability and sharpen outcomes without sidelining clinical judgment. It doesn’t replace the surgeon’s expertise; it gives them a clearer, data-backed view of each decision point.
In my latest @Forbes piece, I look at how advanced analytics and AI are changing LASIK and other refractive procedures through more precise modeling, deeper imaging, and larger datasets that help surgeons plan and predict results with greater consistency. I also walk through how platforms like Alcon’s Wavelight Plus use detailed eye measurements, ray tracing, and digital eye “avatars” to simulate thousands of potential treatment paths so surgeons can choose the best option to deliver stable, high-quality vision for each patient.
@MoorInsStrat@SeeAlconScience
https://t.co/XJtfsoaIES
.@NetSuite’s SuiteConnect NYC: Meeting Businesses Where They Are
Evan Goldberg opens #SuiteConnect NYC with his vision for NetSuite Next and how connected intelligence can help turn ERP data into real decisions. @cdubitsky of happy coffee joins @rangabodla of Oracle NetSuite to talk through how NetSuite gives his team the visibility to grow and control his business.
Read more as I discuss my thoughts in my latest LinkedIn article. https://t.co/OpH6O8jfap
@MoorInsStrat@Oracle@OracleCloud@OracleCloudERP@OracleCloudSCM
@NetSuite is hosting a chat with @cdubitsky (Craig Dubitsky), the founder and CEO of Happy Coffee, and @rangabodla Ranga Bodla, the VP of Field Engagement and Marketing at @Oracle NetSuite. Dubitsky shares his journey and how he put NetSuite into action, highlighting the benefits it brings to the business.
Implementation is key and having the right data is what really makes the difference for long-term success.
@MoorInsStrat@robertdowneyjr
.@NetSuite#SuiteConnect begins now with Founder and EVP of @Oracle NetSuite, Evan Goldberg. Goldberg dives into NetSuite Next, and the connected intelligence of the system turning information into action.
The real success of ERP isn’t about swapping out the system of record. It’s about extending it in a way that connects data and decisions without breaking trust.
The goal is to move from static systems to ones that help people act with greater confidence, using automation and insights where they actually add value. Progress comes from people-first, reliable systems that strengthen decisions, not from rushing into autonomy before teams are ready.
@MoorInsStrat@OracleCloud
.@Acumatica Summit Day 2 is live and the keynote is hosted by the product team.
The product team showed how AI can cut down manual work, make everyday tasks easier, and pull performance data into one place so teams can see what’s going on. The focus was on improving existing processes, increasing productivity, and using AI directly within core workflows, with differences by industry taken into account. The hard part is execution (which is a big deal) as results depend on data quality, clear processes, and helping people actually use the system instead of working around it.
@MoorInsStrat
.@Acumatica Summit — here we go! Rain or shine or ice or snow. @JohnCaseCEO kicks off day 1.
I like Acumatica’s direction. The real value isn’t just AI, but a shift toward event-driven ERP, where systems react to what’s happening instead of waiting on batch processes or manual intervention.
More to come.
@MoorInsStrat
.@Commvault SHIFT 2025 happened in NYC before the holidays, where the company introduced its new Commvault Cloud Unity platform. Enterprise environments now range across cloud, SaaS, ERP, edge, and AI workloads, but many teams are still relying on recovery models built for much simpler times.
Cloud Unity brings backup, identity, cyber recovery, and AI protection together within a single operating model. The goal is to simplify daily operations and make it easier to identify trusted recovery paths when something goes wrong. The recovery mindset is also shifting from restoring everything quickly to restoring only what’s verified as clean. That is becoming critical in the face of ransomware, identity-based threats, and AI-driven workloads, where a small issue can quickly escalate.
My thought from SHIFT is that resilience is becoming a core part of IT architecture. As AI and automation reshape how teams work, the organizations that treat resilience as a discipline rather than a toolset will be the ones that stay stronger through 2026.
@MoorInsStrat
https://t.co/OUvRTJV7Fy
.@salesforce's latest State of Data and Analytics research lines up with what I see in the field. A lot of enterprises talk about being data-driven and ready for AI, but the foundations often aren’t there. When 84% of data leaders say their data strategy needs a reset for AI to work, that’s not a tooling problem, it’s a structure and trust problem. Fragmented systems, inconsistent governance, and questionable data quality are showing up directly as inaccurate or unreliable AI outputs, even in live environments.
My thought is that AI isn’t failing, data is. Most organizations are still running hundreds of applications that barely talk to each other, with valuable context stuck in silos or unstructured sources. The companies making real progress aren’t chasing more pilots or models. They’re fixing integration gaps, assigning clear ownership, improving data quality, and treating governance as ongoing operational work. I like Salesforce's message; that the speed of AI development depends on the willingness of enterprises to clean and trust their data.
@MoorInsStrat
https://t.co/qwEkCubQR4
.@QAD_Community made some recent news for the ERP industry as @TennecoLLC has gone live on QAD Adaptive at its first manufacturing site. This isn’t just about upgrading ERP systems; it emphasizes that cloud-native, adaptable ERP platforms can handle live production and make real-time decisions on a large scale.
The QAD press release features a quote from me explaining why this is important for the ERP industry, as I'm seeing a transition from transaction systems to platforms designed for execution, resilience, and continuous adaptation.
@MoorInsStrat
https://t.co/cXpvqpi2aC
.@Snowflake planned acquisition of @Observe_Inc points to where enterprises may be stalling or running into difficulties. The challenge isn’t building AI models or running pilots. It’s keeping those systems stable, predictable, and affordable once they’re expected to run every day in production.
It’s interesting that Observe is built on Snowflake. It seems more like Snowflake is enhancing what customers are already doing, rather than creating something entirely new. It gives teams a way to pull logs, metrics, and traces into the same environment they’re using for data and AI, which makes it easier to see what’s actually happening when something slows down, breaks, or behaves unexpectedly. OpenTelemetry and Apache Iceberg treat observability data like any other enterprise dataset, following the same governance rules, queryable with familiar tools, and living alongside analytics data instead of being isolated in a monitoring system.
There are tradeoffs to work through. Observability data grows quickly, and storing large volumes of it inside Snowflake can get expensive if retention and access aren’t managed carefully. Governance also gets more complicated when operational data, application data, and AI models all come together. Another open question is how cleanly Observe ties in with TruEra and Snowflake’s other recent acquisitions, and whether this ends up feeling like one environment or multiple tools under the same brand.
@MoorInsStrat
https://t.co/M1KS5JsQ56
.@IBM plan to acquire @confluentinc for about $11 billion is a positive move to close a long-standing gap in its data platform. Confluent brings IBM a reliable way to handle real-time data, which has become essential for anyone trying to move AI from pilot projects to real-world operations.
I’ve said many times that without consistent and trustworthy data in motion, the rest of the AI stack doesn’t get very far. This deal gives IBM a chance to unify its data, integration, and AI capabilities instead of continuing with a collection of separate tools.
The real question is whether IBM can turn all of this into a cohesive platform. Integrating Confluent into IBM’s broader portfolio will take time, and some customers will want to understand how the technology evolves once it sits inside a much larger enterprise stack. The competitive pressure is also intense. @Microsoft, @googlecloud, @awscloud, @OracleCloud, @Snowflake, @databricks, @cloudera and @Teradata are all building their own real-time, AI-focused data architectures, and many of them are moving faster or offer tighter cloud integration.
I like this acquisition and it makes sense, but everything still comes down to execution. IBM can turn this into a modern data platform, more of a clear, end-to-end strategy across data, integration, and AI. Customers are looking for platforms that reduce complexity and give them a straighter path to operational AI, and IBM should have the pieces to potentially deliver that.
The real test is whether IBM can make the data environment easier to work with and reduce the hurdles between streaming, governance, and AI workflows. Customers need that simplicity to move their AI plans from ideas to real operations. If IBM can deliver, organizations get a platform that’s easier to manage and more aligned with how they want to use AI. If not, this risks becoming another large acquisition that doesn’t change IBM’s direction or its competitive position.
@MoorInsStrat@IBMNews@ibmconsulting
https://t.co/EP40a1mWQh