ERP in 2026: More AI, more best-of-breed add-ons

ERP (enterprise resource planning) systems are getting a serious AI upgrade in 2026—and they may look a lot less “all-in-one” than they used to.

In a recent article for CIO.com, senior writer Grant Gross explains how ERP platforms are evolving from transactional back-office systems into intelligent, data-driven engines. Leaders like Steve Bronson of Southern Glazer’s Wine & Spirits say AI and predictive analytics are becoming deeply embedded in core processes, transforming ERP into a real-time decision platform.

AI is the headline change. Experts predict ERP systems will increasingly automate invoicing, onboarding, reconciliations, and other routine finance tasks. Kirk Teal of Information Services Group says AI will go beyond analytics—detecting anomalies, forecasting outcomes, and even recommending or executing decisions within set guardrails. Lasse Kalkar of LiveFlow adds that finance teams are ready to offload repetitive work to AI agents, while keeping humans in the loop for final review.

At the same time, companies are rethinking the traditional monolithic ERP model. Some are embracing modular, best-of-breed apps layered onto a core system. Andy Sen of AppDirect sees AI making it easier to build custom ERP-related tools instead of relying only on bundled vendor modules.

Still, all-in-one platforms aren’t going away. Many organizations prefer their simplicity, and hybrid ecosystems—core ERP plus specialized add-ons—are emerging as the middle ground.

The takeaway? In 2026, ERP won’t just record what happened. It will help decide what happens next.

 

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Aurora MySQL InnoDB Overhead

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If you’ve ever loaded a few terabytes of raw data into MySQL and then scratched your head when the database footprint grew larger than your flat files, you’re not alone. This question came up recently in a real-world migration: flat files totaled about 2.0 TB, but once ingested into MySQL (with no secondary indexes), the database measured 2.24 TB.

So where did the extra 240 GB come from?

The InnoDB Overhead Story

The main culprit is InnoDB’s design. It’s not just storing your rows — it’s storing them with transactional guarantees, recovery mechanisms, and structures for efficient querying. Here’s what adds up:

  1. Page Structure and Fragmentation
  • InnoDB stores data in 16KB pages.
  • Pages aren’t always fully packed, leaving unused space (internal fragmentation).
  • Multiply that by billions of rows, and you’ve got gigabytes of overhead.
  1. Row Format Metadata

Every row comes with extra fields beyond your raw data:

  • Row headers (7–23 bytes).
  • MVCC metadata like DB_TRX_ID and DB_ROLL_PTR to handle concurrent transactions.

A small per-row overhead scales up dramatically in large datasets.

  1. Redo, Undo, and Temporary Logs

InnoDB maintains:

  • Redo logs (ib_logfile0, ib_logfile1) for crash recovery.
  • Undo logs for rollbacks and consistent reads.
  • Temp tablespace (ibtmp1) for operations like sorts.

Even when idle, these files persist on disk.

  1. Fill Factor / Page Utilization

To keep inserts efficient, InnoDB intentionally leaves free space in pages. This means some storage is held open for growth, rather than packed tightly like in a flat file.

  1. Data Type Inefficiencies
  • VARCHAR, TEXT, BLOB, and DECIMAL fields often take up more space in InnoDB than in a plain CSV.
  • Alignment and padding further contribute.
  1. Deleted but Not Reclaimed Rows

If you’ve done heavy deletes or updates, space may not yet be reclaimed. Running OPTIMIZE TABLE can help, though it’s resource-intensive.

How to Measure the Difference

You can check actual table storage in MySQL:

SELECT

table_schema,

table_name,

ROUND(data_length/1024/1024/1024, 2) AS data_gb,

ROUND(index_length/1024/1024/1024, 2) AS index_gb

FROM information_schema.tables

WHERE table_schema = ‘your_db’

ORDER BY data_gb DESC;

Or examine InnoDB tablespace allocation:

SELECT

table_name,

allocated,

file_size,

free

FROM information_schema.innodb_tablespaces;

Putting It Together

The 12% overhead (240 GB on 2 TB raw) is not unusual at all. In fact, it’s right in line with expectations:

Component Typical Contribution
InnoDB page + row overhead 5–15%
Undo/redo logs, temp files 1–5%
InnoDB system metadata <1%
Fill factor, alignment 2–10%

Flat files are lean but fragile. InnoDB adds the structures that make MySQL durable, transactional, and queryable — and that extra space is the price of those guarantees.

Final Takeaway

If your MySQL footprint is a bit larger than your flat file source, don’t panic. That overhead is just InnoDB doing its job. And in large-scale systems, a 10–15% increase is expected — and often well worth the trade-off for reliability and performance.

The Enterprise AI Revolution Is Boring, and That Is What Makes It Work

When people talk about the artificial intelligence (AI) revolution, they usually imagine flashy chatbots or Super Bowl–ready demos. But as Mark Talbot,  Director of Architecture and AI at Appian, points out inhis article on ERP Today, the AI that’s truly transforming businesses is… boring. Quiet, reliable, and deeply embedded into core workflows, this is where real ROI happens.

Talbot calls it “boring AI” because it focuses on the back-end processes that actually run the business: enterprise resource planning (ERP) systems, scheduling, billing, and cross-platform coordination. The flashy AI pilots—generative chat tools or marketing-focused bots—are failing 95% of the time because they aren’t integrated into daily work. Employees rarely use them, and executives end up measuring hype instead of measurable outcomes. The magic of boring AI is that it works where it counts. In ERP environments, it reconciles data across systems, automates financial reporting, streamlines supply chain operations, and handles repetitive administrative tasks. For example, a healthcare provider using AI to automate patient intake and documentation reduced waitlist times by over 80%—all without dramatic fanfare. Talbot emphasizes that the real value of AI comes from embedding it into existing processes, not forcing users to adopt separate tools. Governance, audit trails, and compliance should be built in from day one, making AI trustworthy and risk-free. Low-code platforms often make this easier, letting organizations maintain transparency and human oversight without slowing adoption.

The takeaway for IT leaders: the AI worth investing in isn’t flashy—it’s operational. It quietly accelerates ERP-driven finance, HR, and supply chain processes, reduces errors, ensures compliance, and frees teams to focus on higher-value work. In other words, boring AI is the AI that works.

 

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Infor Named a Leader in 2026 Gartner Magic Quadrant for Configure, Price, and Quote Applications

Infor was recently named a Leader in the 2026 Gartner Magic Quadrant for Configure, Price, and Quote (CPQ) Applications. According to their press release and the report by Gartner, Infor was recognized for both its “completeness of vision” and its “ability to execute.” Gartner defines Leaders as vendors that successfully deliver on their vision through strong products and services, proven large-scale deployments, solid financial performance, and consistently high customer satisfaction. Infor’s CPQ solution is designed to provide an intuitive, visual user experience that enables companies to configure complex products quickly and accurately. Built on the Infor cloud platform powered by Amazon Web Services and Infor OS technology, the solution offers industry-specific capabilities without requiring extensive customizations or integrations. This foundation allows organizations to streamline sales processes, reduce errors, and accelerate deal closures. Ron Eismann, Vice President and General Manager of Infor CPQ, said the recognition reflects the company’s continued focus on innovation and excellence in CPQ solutions. He emphasized Infor’s commitment to enhancing configuration, pricing, and quoting capabilities to help customers across industries optimize sales operations and drive growth. The company also highlighted the growing importance of how products are sold, noting that modern buyers expect personalized offerings delivered quickly, accurately, and affordably. Infor CPQ supports sales teams, partners, and distributors by automating manufacturing instructions, increasing quote volume, improving upsell opportunities, and accelerating new product introductions. Overall, the announcement positions Infor as a leading provider helping businesses modernize and scale complex sales processes.

 

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PCARD issue- GL165 error file missing

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Problem:

I was able to access the QA site and see the JE, however there is an issue.  I am not seeing the “error” report for GL165 that we would normally see in v9 production. This is the report that tells us which records have an error and what the error is.

How do we see the error report?  Is this a setting somewhere?

 

Below is an example from v 10 QA.  The test JE has an error, and the GL165 report shows that there is an error, but it doesn’t tell me which record has the issue:

 

Resolution:

To resolve this, simple give your user access to the role which gives access to the IFTR.1 files that generate the error files. Then have the user run the job again.

How ERP, AI Can Improve Logistics and Operations Efficiency

 

Artificial Intelligence (AI) is no longer just a “nice-to-have” in logistics—it’s becoming a core driver of operational efficiency when integrated with enterprise resource planning (ERP). In a recent ERP Today article, Chris Vavra explains how manufacturers and distributors are combining AI with ERP to reduce costs, improve delivery performance, and stay resilient amid supply chain disruptions.

Companies like Aptean are embedding AI directly into transportation, warehouse, and demand management workflows, moving operations from reactive problem-solving to continuous optimization. For example, a midmarket food and beverage producer saw a 12% drop in empty miles, 9% lower fuel spend, and 20% better on-time delivery within six months by integrating AI-driven route optimization into its ERP. Similarly, warehouse management systems with AI are reallocating labor dynamically, boosting picking productivity.

For IT leaders, this shift changes daily responsibilities. Teams focus less on reconciling siloed data and more on validating AI recommendations, fine-tuning constraints, and managing exceptions that require human judgment. Early adopters emphasize the need for disciplined data governance, master data standardization, and phased rollouts—starting with high-impact areas like route optimization before scaling to predictive inventory and warehouse orchestration.

Vavra also notes that vendor evaluation is critical: leaders should prioritize transparent AI models, ERP integration, industry-specific accelerators, and continuous model tuning. Ultimately, ERP platforms that unify logistics data and embed AI natively will define the next wave of competitive advantage, while organizations that delay data cleanup or integration risk falling behind.

 

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How to reorganize or modify Columns in LBI Maintain Reports

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Follow the steps below to learn how to reorganize or modify your columns in (Lawson Business Intelligence) LBI Maintain Reports.

 

Problem:

You’re an admin for Lawson LBI but you want to reorganize the Maintain Reports columns like the ones shown below:

 

Solution:

There is a simple way to do this. Just follow these steps.

  1. First, log in to LBI and open your Report Administrator:
  2. Next, go to My Reports on the side bar:
  3. Make sure “ALL” is selected under the left column under Report Lists
    1. Click “Edit List” on the top right and reorganize the columns, then click save.

Go back to Maintain Reports and you should see your new columns!

Enterprise resource planning: AI driven tools to meet today’s changing financial services landscape

AI-driven (aftificial intelligence) ERP (enterprise resource planning) is quickly becoming a strategic necessity for financial services firms navigating volatility, regulation, and rising expectations for speed and insight. In an article from Verdict.co.uk, author Lara Williams recaps a recent GlobalData executive roundtable that explored how AI-powered enterprise planning tools are reshaping finance operations across the sector.

The discussion—held in London with senior finance leaders and supported by Workday—highlighted a familiar tension in financial services. Firms are often early adopters of advanced technology, yet they operate in highly regulated, risk-averse environments. With AI conversations shifting from hype to hard ROI, finance directors are now tasked with identifying which AI-driven ERP tools deliver measurable value and how to implement them amid uncertainty around both human and financial capital.

A central theme in Williams’ reporting is the growing importance of adaptive planning. Market volatility, regulatory pressure, and evolving customer expectations have made real-time budgeting, forecasting, and scenario modeling a competitive differentiator. While executives broadly agreed on the value of unified, AI-powered data platforms, Williams notes that organizations are at very different stages of adoption.

Legacy system integration and data silos remain major obstacles. According to Williams, finance leaders see AI-driven adaptive planning as a way to streamline the monthly close, automate consolidations, and enable faster fraud and anomaly detection—especially for multinational organizations.

Williams also points out an interesting side effect of greater visibility: uncovering more fraud can strain resources, even if it’s ultimately a positive outcome. The takeaway is clear in her analysis—AI-driven ERP can unlock real agility and insight, but only when built on strong data foundations and supported by the right enterprise technology partners.

 

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Three Trends Changing Manufacturing ERP in 2026

Manufacturing ERP is shifting from passive recordkeeping to active execution. ERP Today’s senior editor Chris Vavra explains in a recent article how new technologies and regulatory pressures are redefining ERP’s role—from system of record to system of action.

Vavra identifies three converging trends reshaping ERP strategy and day-to-day operations:

  • Agentic operations replace AI copilots
    ERP systems are moving beyond recommendations to autonomous action. Software agents can reroute production, issue purchase orders, trigger maintenance, and resolve routine exceptions without human prompts. Leaders spend less time entering transactions and more time setting policies, guardrails, and approval thresholds. Early adopters report reduced downtime and productivity gains as agents handle predictive maintenance, scheduling, and high-volume transactional work.
  • Composable and headless ERP architectures
    Instead of large, disruptive upgrades, organizations are adopting modular, API-driven ERP stacks. This allows teams to add or swap capabilities—such as demand planning engines or MES functions—without destabilizing core systems. Executive focus shifts toward integration design, vendor orchestration, and data governance rather than monolithic customization.
  • The rise of the sustainability ledger
    With new regulations taking effect in 2026, sustainability data is becoming as critical as financial data. Emissions, waste, and resource usage must be accurately captured, auditable, and tied to every batch and shipment. Poor data quality now represents a compliance risk, not just a reporting issue.

The message for ERP insiders is clear: success in 2026 will depend on governing autonomous systems, managing modular ecosystems, and treating sustainability data as a first-class ERP workload.

 

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How to correct a name change for Inbasket

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Each Process Automation user has an Inbasket that is accessible through Infor Smart Office. Your Inbasket contains tasks that have been assigned to you, as well as the user’s information.

 

Problem:

Users’ name changed but is not reflected in Inbasket. (See screen shot below for example)

 

Resolution:

In Infor Security Services (ISS), the Preferred Given Name is listed as “Linda”. The value can be updated in this section if the person has changed their name (or if for some reason the name is wrong or misspelled).

Once you edit the “Given Name” field, save your changes. The name displayed should now be the correct one.