If your organization has been planning a server refresh over the next 12 to 24 months, you may have already noticed something unexpected:
Infrastructure costs are climbing.
Servers, memory, storage, networking equipment, and other critical hardware are becoming more expensive as global demand for AI infrastructure continues to accelerate. The world’s largest technology companies are investing hundreds of billions of dollars in AI data centers, creating unprecedented demand for many of the same components businesses rely on to run their own IT environments. Industry analysts report that this demand is contributing to higher prices, tighter supply, and longer lead times for enterprise hardware.
For organizations running any ERP system, this creates an important question:
Is now the right time to invest in another generation of on-premises infrastructure?
Many organizations have ERP systems that continue to deliver tremendous business value.
Those investments don’t lose their value simply because technology evolves.
Instead of replacing the ERP they trust, many organizations are choosing a different path: moving their existing ERP environment to the cloud.
A traditional infrastructure refresh often requires significant capital investment.
With enterprise hardware prices under pressure from AI-driven demand, those investments may cost more than organizations anticipated just a few years ago.
ERP Cloud hosting offers another option.
Rather than purchasing, maintaining, and eventually replacing physical infrastructure, organizations can move their ERP into a professionally managed cloud environment that delivers:
One of the biggest misconceptions about cloud migration is that it requires replacing the ERP itself.
In reality, many organizations continue running the same ERP they’ve trusted for years.
The difference is where it runs.
By moving to a modern cloud environment, businesses can preserve the workflows, data, and processes they’ve built over time while eliminating much of the cost and complexity associated with managing on-premises infrastructure.
No one can predict exactly how long today’s infrastructure pricing pressures will continue. However, analysts expect strong demand for AI infrastructure and memory components to remain elevated for the foreseeable future, continuing to influence enterprise hardware costs.
For organizations already considering a server refresh, office expansion, hardware replacement, or disaster recovery improvements, now is a good time to evaluate all available options—not just another hardware purchase.
The question isn’t whether your ERP should change.
It’s whether the technology supporting it should.
Check out our The Legacy Modernization Blueprint to learn how organizations are taking trusted ERP systems to the cloud while modernizing the technology behind them.
A practical look at how distributors are using AI to move faster, gain visibility across operations, and keep pace with rising customer demands, and where it pays off first.
Most distributors have stopped asking whether to use AI and started asking where it actually pays off. For organizations running Infor CloudSuite Distribution (CSD), that conversation often starts with the operational data already flowing through the ERP. Spending is up across forecasting, fulfilment, and customer service, but the returns are uneven—and the difference usually comes down to where a distributor chooses to start.
For years, AI in distribution lived in pilot projects and conference keynotes. For distributors using Infor CloudSuite Distribution, that shift is especially important because AI can build on the data, workflows, and processes already managed within the platform. That has changed quickly.
In one multi-year industry benchmark, the share of distributors doing nothing with AI fell from roughly 62 percent in 2023 to about 29 percent in 2025, while the group using it across several parts of the business climbed to about a third.
The shift matters because it reframes the conversation: AI in distribution is less about automation for its own sake and more about keeping operations in step with the business around them.
Many distributors treat the presence of AI in their operations as the advantage, as though adopting it is what puts them ahead. The real advantage is not the technology itself, but what it does once it’s in use, such as giving the business the ability to respond faster and more accurately as order volume, SKU counts, and customer expectations rise.
For example, a distributor that forecasts demand a week sooner—or answers a customer in minutes instead of hours—wins on service without adding headcount, and this is the lens worth keeping as the use cases pile up.
The most useful way to understand AI in distribution is to look at where it already earns its place. Four areas stand out across supply chain and logistics operations:
This is the clearest win for most distributors. Within Infor CloudSuite Distribution, AI can analyze order history, seasonality, supplier trends, and demand signals to help planners forecast demand and recommend inventory decisions.
Research from McKinsey on distribution operations points to inventory reductions in the range of 20 to 30 percent, along with lower logistics and procurement costs, when AI strengthens demand planning. One building products distributor lifted fill rates by 5 to 8 percent after putting an AI-driven supply chain control tower in place.
AI capabilities complement Infor CloudSuite Distribution by helping customer service teams process orders faster, identify exceptions, and prioritize work before delays impact customers. When demand swings, it helps fulfillment teams hold service levels without scrambling, which keeps promises to customers intact during the periods that test them most.
Generative AI working alongside Infor CloudSuite Distribution can surface customer history, recommend next-best actions, and draft responses using current data. It drafts quotes, surfaces cross-sell and reorder suggestions, and handles routine post-sale questions, freeing people for the conversations that need a human.
Deloitte points to internal sales and customer service as one of the largest near-term opportunities for distributors to capture value from generative AI.
Pricing is where small improvements add up fast. When distributors use Infor CloudSuite Distribution as the operational system of record, AI can identify pricing and margin opportunities across thousands of line items far faster than manual analysis.
For all the momentum, results still lag enthusiasm. Research from MDM and NAW covering more than 400 distributors found nearly nine in ten companies active with AI in some form, yet far fewer are happy with what they are getting back. Roughly three-quarters expect meaningful value from AI, while fewer than one in five say they have actually seen it.
It all comes down to connected, trustworthy data. Infor CloudSuite Distribution gives distributors a strong operational foundation, but realizing AI’s full value still depends on data quality, governance, and consistent business processes.
Even organizations running Infor CloudSuite Distribution can struggle if data remains disconnected, poorly governed, or inconsistent across departments. Most projects break down for three reasons:
All three of these reasons are fixable, and none of them is an AI problem.
Given that gap, sequencing matters more than ambition. For distributors using Infor CloudSuite Distribution, the best AI projects usually begin inside existing operational workflows rather than as standalone initiatives. Once value is proven in one area, they expand from a win instead in phases of applying AI across the business on a single broad rollout.
The most common starting question is what data AI needs. Infor CloudSuite Distribution already captures much of the operational data AI needs—orders, inventory, purchasing, suppliers, customer activity, and financial information. The opportunity is often less about collecting more data and more about connecting, cleaning, and governing the information already inside your ERP.
The first move is making that data usable and trustworthy, not buying another tool. A focused effort to clean and connect the data you already own does more for an AI project than any single piece of software.
If you’re already running Infor CloudSuite Distribution, you may be closer to AI readiness than you think.
AI rewards distributors who know where their data and their best use cases line up. Before committing resources to implementing AI, it helps to take an honest look at what you already have and where AI would pay off soonest. For distributors using Infor CloudSuite Distribution, the best AI projects usually begin with existing business processes rather than standalone AI initiatives.
Watch AI in CloudSuite Distribution
Watch the full session with Infor experts, Nick Perry and Omar Jeelani, as they demo AI in CSD with a live procure-to-pay cycle, walk through AP invoice automation end to end, show generative AI running inside CSD, and cover the full Velocity Suite catalog, including the AI agent roadmap.
Many distributors continue to rely on Infor A+ as a stable operational foundation, but growing complexity across inventory, fulfillment, and reporting is prompting teams to assess whether existing systems still support current demands. Factors such as expanding product catalogs, faster fulfillment expectations, and increased reliance on real‑time data are driving this re‑evaluation.
Challenges often emerge gradually, such as increased manual coordination between purchasing, warehouse, and finance teams, delays in confirming inventory or order status, or difficulty aligning operational data across departments. These issues can indicate that systems were not designed to support the current level of coordination required.
Modern distribution systems are designed to provide real‑time visibility into inventory levels, order activity, purchasing status, and warehouse operations. By connecting this information within a unified environment, teams can respond more quickly to changes, identify issues earlier, and make decisions based on consistent, up‑to‑date data.
As operational complexity increases, purchasing, warehouse, sales, and finance teams depend on the same information to stay aligned. When workflows are disconnected, updates must be communicated manually, increasing delays and the risk of errors. Modern systems help reduce this friction by allowing updates in one area to flow automatically across the organization.
Automation helps streamline routine tasks such as order processing, inventory updates, and reporting. This reduces manual effort and allows teams to focus on exception management and higher‑value activities. Built‑in analytics also help leaders gain clearer insight into operational performance and trends.
Infor CloudSuite Distribution is designed to support more connected, data‑driven distribution operations by bringing purchasing, inventory, warehouse management, and financial reporting together in a single platform. This helps distributors improve visibility, reduce manual coordination, and build a more scalable foundation for future growth while leveraging existing operational knowledge.
AI has become one of the loudest conversations in distribution, and most of that noise is about what’s coming next. The more useful question for a distributor is simpler: what does AI do for the daily work of managing inventory, purchasing, fulfillment, and finance right now?
This is a look at where AI is used today in Acumatica Distribution Edition, and why a platform born in the cloud brings AI to the surface as a natural part of the system.
Distributors are running leaner than ever while the math gets tighter, and the nature of the pressure has shifted. Modern Distribution Management, tracking wholesale performance across late 2024 and early 2025, found that distributors’ top concerns have shifted from supply availability to cost control, inventory productivity, and margin protection.
The encouraging news is that these pressures are largely within the organization’s control. For distributors with the right operational data, AI is becoming a practical tool for improving inventory decisions, protecting margins, and increasing productivity..
For mid-market distributors, that pressure lands on operations. With thin margins and lean teams, how well the business runs day to day now does more to protect profit than any pricing move.
Picture this: a purchasing manager suspects a few SKUs have become dead weight, but inventory lives in one system, sales history in another, and margin details somewhere in finance. So she asks for a report, waits two days for the analyst to pull it, and by the time the numbers arrive, the supplier’s order window has passed. She places the buy based on the information she’s given, the way she usually does.
Whether or not she made the right call isn’t really the point of this story. If the decision turns out to be wrong, the company pays for it later through excess inventory, carrying costs, or missed sales opportunities. The actual point is that this is how margin quietly leaks out of a business—one (wrong) decision at a time.
What we describe above is just an example of one moment in one week, and most distributors can name their own version of it. What this is meant to illustrate is that when data sits in separate places, the answer tends to show up after the moment to use it has passed. Now if we multiply that error across different scenarios in purchasing, sales, and finance, it becomes obvious that errors from this type of manual work quietly drains margin. It’s the first thing built-in AI is meant to fix.
The way AI reaches a distributor depends a lot on how the underlying software was built. Acumatica was born in the cloud, so its AI features are woven into the workflows that teams already use rather than sold as a separate module to install and maintain afterwards. Acumatica describes this as an AI-first approach: building AI into existing workflows from the ground up instead of adding it onto features later.
That distinction matters for a practical reason. A cloud-native platform can deliver new AI capabilities through the same system your team already works in, with updates arriving as part of the product. There’s no separate tool to buy, connect, or train people on. For a distribution team, the benefit of AI shows up where the work already happens, not in yet another login.
The clearest way to judge AI is by what it changes in the daily routine. Inside Acumatica Distribution Edition, that shows up in three areas distributors deal with constantly.
The AI Assistant lets anyone on the team ask a plain-language question about business data and get a formatted answer back, without building a report or routing the request through an analyst. A finance lead can check how margin is trending on a product line, or a sales manager can pull an order status, in the moment they need it. The value is speed, and answers come in the flow of work instead of at the end of a reporting queue.
With AI Studio, operations, finance, and purchasing teams can build automated ERP workflows by describing them in plain English, with no coding and no IT ticket. An operations manager might set up a reorder trigger or an approval step that used to require a developer. Putting that capability in the hands of the people who own the process is part of a wider shift toward no-code tools in ERP, and it shortens the distance between spotting a bottleneck and fixing it.
For inventory, Acumatica pairs demand forecasting, automated replenishment, and anomaly detection to keep stock aligned with real demand. The payoff is direct for a distributor's balance sheet: fewer dollars tied up in dead stock, lower carrying costs, and a better chance the right items are on the shelf when a customer orders. Instead of reacting to stockouts and overstock once they've already happened, teams get an earlier, data-backed read on what to buy and when.
Security and control are the first questions most distributors raise about AI, and they’re fair ones. Acumatica’s approach keeps company data isolated from public training models by using private, native large language models, so your business data stays yours. Because the AI lives inside the ERP you already run, there’s no separate system to stand up or secure on the side.
That design also lets teams move at their own pace. You can start with one capability—such as faster reporting or a single automated workflow—prove the value, and expand from there. AI becomes something you adopt in steps rather than a wholesale change you commit to all at once.
Many distributors continue to rely on Infor A+ as a stable operational foundation, but growing complexity across inventory, fulfillment, and reporting is prompting teams to assess whether existing systems still support current demands. Factors such as expanding product catalogs, faster fulfillment expectations, and increased reliance on real‑time data are driving this re‑evaluation.
Challenges often emerge gradually, such as increased manual coordination between purchasing, warehouse, and finance teams, delays in confirming inventory or order status, or difficulty aligning operational data across departments. These issues can indicate that systems were not designed to support the current level of coordination required.
Modern distribution systems are designed to provide real‑time visibility into inventory levels, order activity, purchasing status, and warehouse operations. By connecting this information within a unified environment, teams can respond more quickly to changes, identify issues earlier, and make decisions based on consistent, up‑to‑date data.
As operational complexity increases, purchasing, warehouse, sales, and finance teams depend on the same information to stay aligned. When workflows are disconnected, updates must be communicated manually, increasing delays and the risk of errors. Modern systems help reduce this friction by allowing updates in one area to flow automatically across the organization.
Automation helps streamline routine tasks such as order processing, inventory updates, and reporting. This reduces manual effort and allows teams to focus on exception management and higher‑value activities. Built‑in analytics also help leaders gain clearer insight into operational performance and trends.
Infor CloudSuite Distribution is designed to support more connected, data‑driven distribution operations by bringing purchasing, inventory, warehouse management, and financial reporting together in a single platform. This helps distributors improve visibility, reduce manual coordination, and build a more scalable foundation for future growth while leveraging existing operational knowledge.
Palmer Brothers is a full service commercial painting and general
contracting company that has served the Washington D.C. Metropolitan
area since 1963. They provide a variety of painting services, maintenance,
and construction needs within the Maryland, District of Columbia, and
Virginia area. Projects completed include ones for local management firms
throughout the Tri-State area and outlying areas in Pennsylvania, Delaware,
Georgia, and Florida.
Industry: General Contractor
Headquarters: Silver Spring, MD
Solutions: Sage Paperless & Sage 300CRE
Website: www.palmerbros.com
Palmer Brothers has served the Washington D.C. Metropolitan area since 1963.
After implementing Sage Paperless, everyone at Palmer is enjoying the benefits of the solution.
Rachel Irish has been the Office Manager at Palmer Brothers for 19 years. She was a big proponent in implementing Sage Paperless and now everyone at Palmer is enjoying the benefits of the solution. Prior to Sage Paperless, Palmer Brothers processed all invoices manually. Invoices would come in by mail, get entered into their Sage accounting system and printed out. These paper documents were then distributed to the individual mailboxes of the project managers. Approval and further processing of the invoices was delayed until the PMs were back in the office.
Prior to Sage Paperless, Palmer Brothers processed all invoices manually. Invoices would come in by mail, get entered into their Sage accounting system and printed out. These paper documents were then distributed to the individual mailboxes of the project managers. Approval and further processing of the invoices was delayed until the PMs were back in the office. Once signed, they were given back to Rachel to finalize the pending invoices. This entire process could take anywhere from one to two weeks.
Now invoices are delivered right to Rachel’s email inbox, where she is able to route them to the appropriate project managers digitally via email. Digital routing has reduced the process time span significantly. The invoices are usually delivered a day or two after the expense is incurred, then further processed and approved in real time.
Once signed, they were given back to Rachel to finalize the pending invoices. This entire process could take anywhere from one to two weeks.
Rachel states, “It’s all about being more efficient. By moving to Sage Paperless, a number of time-consuming steps and processes have been eliminated.” This helps them save not only time, but money throughout the organization.
“Sage Paperless has made my job more streamlined from start to finish. With less paper cluttering up my desk, everything gets done faster.” Rachel can certainly appreciate being able to get more done in less time.”
Aktion Associates is a purpose‑built technology partner for professional services firms navigating growth, complexity, and change. With deep expertise in project‑based operations, cloud‑ready ERP platforms, and a proprietary data‑driven and lean implementation approach, Aktion delivers real‑time visibility across projects, people, and financials while reducing risk and accelerating time to value.
Beyond implementation, Aktion operates as a long‑term partner—supporting organic growth, geographic expansion, and M&A activity through integrated ERP, infrastructure, and industry‑aware support that drives sustained operational improvement and leadership confidence.
If you’re wondering what kind of impact a modern, cloud‑based ERP could have on your organization, Aktion brings the industry expertise, honest guidance, and technical depth to help you get there.
We don’t just implement software — we help you build the operational backbone that supports your next stage of growth.
AI has moved past the proof-of-concept stage for most manufacturers. The question is no longer whether it belongs in your ERP, but where it earns its keep and how to deploy it without exposing your data or chasing low-value use cases.
To dig into what this looks like inside Acumatica, we sat down with Doug Johnson, VP of Solution Architecture and Product Management at Acumatica. Doug leads product strategy for Acumatica’s cloud ERP platform and has been closely involved in the company’s AI roadmap since the start.
In this Q&A, Doug covers the two kinds of AI manufacturers should know about, how Acumatica protects your data when AI is in the mix, what anomaly detection looks like on the shop floor, what AI Studio unlocks, and where the roadmap heads next.
Doug: There are two kinds of AI worth knowing about.
The first is machine learning. A good example of this: someone emails you a bill as a PDF. The system reads it and pulls out the vendor’s name, the amount, and the date. If it gets the vendor wrong and you fix it, it learns — and next time, it gets it right.
The second kind is generative AI. That’s the more sophisticated. It can write, summarize, and create. Think of it as another way to interact with your ERP and business data. Instead of digging through reports and screens, AI can help surface information, answer questions, and automate routine tasks.
Doug: This is a big one. If you’re not careful, AI can blow right past your security settings.
Someone could ask it, “Show me everyone’s salary,” and it would just hand that over. Acumatica has always controlled who can see what, and we’ve built those same rules into our AI. Every request — going in or coming out — gets checked against your permissions first.
If you’re not supposed to see something, AI won’t show it to you. If AI tries to write something weird into a product description, that gets blocked too.
Acumatica’s AI capabilities respect the same user permissions already configured in ERP. Users can only access information they’re authorized to see, whether they’re viewing a screen, running a report, or interacting with AI-powered tools.
For organizations using AI Studio, administrators maintain control over how AI is configured and what business data can be accessed.
Doug: ERP systems hold a ton of data, and the hard part is knowing where to look. Anomaly detection does that for you.
Every night, it scans your data and flags anything strange. So when your production manager logs in, they can immediately see where something is off. They can click into the issue, pinpoint the cause, and understand what happened. For example, an employee may have taken twice as long as usual at one station. Maybe it was their first day. Modern anomaly detection can also identify unusual inventory movements, supplier delays, unexpected production costs, quality deviations, and demand shifts before they become larger issues.
It works the same way for production orders. If actual cost runs far above planned cost, it flags the job so you can investigate right away instead of finding out weeks later. And it is not limited to production. It can spot issues across sales orders, purchase orders, and almost anything else in the system.
Doug: AI Studio gives organizations a framework for building and deploying AI-powered workflows inside Acumatica. Manufacturers can create automations, connect AI services, and apply AI to specific business processes without building custom applications from scratch.
The value isn’t simply connecting an AI model. It’s giving organizations a controlled way to put AI to work inside the systems employees already use every day.
Doug: AI Studio can automate repetitive business processes that typically require employees to review information manually. Manufacturers might use it to summarize production exceptions, identify inventory risks, prioritize support requests, draft supplier communications, or surface recommendations based on operational data.
Doug: Today, manufacturers can take advantage of capabilities such as anomaly detection, AI-powered content generation, workflow automation, and AI Studio.
Looking ahead, ERP systems are becoming more conversational. Users increasingly expect to interact with business systems using natural language, ask questions about operations, and receive insights without manually building reports.
The trend isn’t toward replacing employees. It’s toward helping employees spend less time searching for information and more time acting on it.
Three things guide how we build it:
→ Responsible — your data stays your data. We won’t ship anything that puts your security at risk.
→ Practical — there’s no point spending $40,000 on AI to catch a $1,000 mistake. The math has to work.
→ Easy to use — for the built-in stuff, you shouldn’t have to fiddle with anything. You flip it on and it works.
The bigger picture: whether it’s anomaly detection you can use today or voice control coming next year, the point is the same. Use AI to remove repetitive work, surface insights faster, and help employees focus on higher-value decisions.
This recap highlights the headlines, but the full webinar gets to the questions CEOs and CFOs are asking now: where AI can create measurable operational value, how to approach it without increasing risk, and what manufacturers should prioritize before making larger investments.
In the on-demand session, Doug goes deeper into anomaly detection using a live production order, walks through practical AI Studio prompts, and explains how Acumatica applies security controls across its AI capabilities. Joined by Tanner MacDonald from Aktion, the discussion also explores what manufacturers can do today to prepare their ERP environment for the next wave of AI adoption.
Note: The webinar below was recorded in September 2025. Product capabilities may have evolved since recording. The Q&A above reflects current capabilities at the time of publication.
Doug Johnson has over 30 years of product management and marketing experience and is currently the Vice President of Solution Architecture and the Vice President of Product Management at Acumatica, where he defines business requirements for flexibly deployed ERP business management software using SaaS and Cloud technologies.
Before choosing an ERP system, organizations must first understand how their current systems and processes operate today. A clear evaluation reveals inefficiencies, exposes system limitations, and helps identify the kind of ERP capabilities your business actually needs.
This guide walks through the essential steps of evaluating systems and processes so your team enters ERP planning with alignment, clarity, and a lower risk of implementation surprises.
A systems and process evaluation helps you:
This evaluation sets the foundation for selecting the right ERP platform—whether you ultimately choose Acumatica, Sage, Infor, or Deltek.
Document every system your organization uses, including:
For each system, assess:
Job cost tools don’t sync with accounting
WMS lacks forecasting and automation
Disconnected tools across Billing, projects, and financials
Legacy MRP cannot handle scheduling
Document every system your organization uses, including:
Most ERP systems reduce manual tasks, especially in:
Effective data drives better decision-making.
Modern ERPs like Acumatica, Sage Intacct, Infor CSD, or Deltek Vantagepoint provide real-time dashboards, with the caveat that your data foundation is solid.
ERP modernization is an opportunity to reduce risk, not just improve operations.
It’s a structured review of your technology tools and business workflows to identify inefficiencies, risks, and readiness for ERP.
Aktion works with Acumatica, Infor CloudSuite Distribution, Sage (CRE + Intacct), and Deltek Vantagepoint.
Aktion works with Acumatica, Infor CloudSuite Distribution, Sage (CRE + Intacct), and Deltek Vantagepoint.
Organizations typically evaluate systems every 12–24 months or before any major modernization project.
Siloed data, manual processes, inconsistent reporting, or systems that cannot scale.
Implementing an ERP system is one of the most important transformations a growing organization will undertake. A modern ERP improves visibility, strengthens reporting, streamlines operations, and positions your business for its next phase of scale. But ERP success doesn’t happen by accident: it happens through careful planning.
If you’re feeling a mix of excitement and anxiety about beginning an ERP project, that’s normal. In fact, it’s a sign you understand how significant this decision is. ERP failures usually don’t occur because of a software flaw. It is more often caused by organizations jumping in without a plan, skipping discovery, underestimating the power of data, or choosing a partner who doesn’t understand their industry.
At Aktion Associates, we’ve helped thousands of organizations modernize with ERP across Construction, AEC, Distribution, and Manufacturing. Through that experience, we’ve identified the proven steps every organization should take before implementation begins.
This guide outlines eight essential steps to building an ERP plan that reduces risk, accelerates adoption, and sets your team up for a successful go-live.
ERP failures make headlines. The root causes are consistent:
The good news?
Every one of those risks can be prevented with proper planning.
Let’s walk through how to build an ERP plan that drives measurable success.
ERP success begins with assembling a team that represents your entire operation — not just IT.
Core roles typically include:
Beyond these roles, include representation from the departments most impacted:
ERP is a company-wide initiative.
The people who use the system should have a voice in designing it.
Clarity is one of the strongest predictors of ERP success.
Your team should collaborate with your ERP partner to define:
Your ERP partner will guide you, but your team knows your business best. The more clearly you define expectations upfront, the smoother your implementation will be
ERP should create measurable impact. Before implementation begins, define the KPIs that will prove your investment was worthwhile.
Common ERP KPIs include:
Every organization has unique goals; define the KPIs that matter most to yours.
ERP software selection is important — but the implementation partner really determines your outcome.
Look for a partner who brings:
Industry expertise
Construction, AEC, Distribution, Manufacturing — each has unique needs. Your partner must understand your workflows.
Technical and functional depth
ERP is interconnected. Your partner should understand:
A proven methodology
Aktion’s Lean Implementation framework reduces project risk and accelerates go-live.
Cultural alignment
Your partner should feel like an extension of your team — transparent, honest, and proactive.
Long-term support
As the living source of your organizational data, ERP isn’t “set it and forget it.”
Be sure your partner offers:
The right partner will guide you not just through go-live, but through your next stage of growth.
Data migration is one of the most crucial — and most underestimated — steps of ERP readiness.
Before importing data into your new system, validate for:
ERP systems are only as strong as the data inside them. Clean data accelerates go-live, improves reporting, reduces rework, and provides the ideal basis for touchless automation.
Even well-planned ERP implementations evolve over time. Measure progress frequently and stay aligned with your partner.
Best practices include:
Regular measurement ensures small issues don’t become major problems.
Technology doesn’t make an ERP successful. People do. Without a user adoption plan, even the best ERP systems fall short.
Strong change management includes:
Change resistance is normal. With the right approach, teams feel empowered, not overwhelmed.
ERP implementation requires focused attention. Avoid launching ERP during peak workloads or major competing initiatives.
Schedule ERP around:
A focused team = a faster, safer implementation.
ERP planning can feel overwhelming, but with the right structure and guidance, it becomes a powerful opportunity to modernize your business. Aktion Associates brings the industry expertise, proven methodologies, and cloud + ERP + IT capabilities needed to help organizations reduce risk and accelerate results.
If you’re considering an ERP project — or ready to build a full ERP plan — our team is here to help you move forward with clarity and confidence.
An ERP implementation plan outlines the steps, resources, decisions, and timelines required to successfully deploy a new ERP system across your organization.
Your plan should define scope, project team roles, KPIs, change management strategy, data preparation, and timelines.
Typically: a project manager, analyst, developer, QA lead, finance lead, operations lead, and executive sponsor.
Most organizations spend several weeks to several months preparing, depending on complexity and resource availability.
Define scope early, involve the right stakeholders, clean your data, measure progress, prioritize change management, and choose an experienced ERP partner.
Yes. Construction, distribution, manufacturing, and AEC firms each have unique workflows, data structures, and compliance needs.
We know that AI is no longer a question of “if” for most distributors. The question is where it pays off and how to roll it out without breaking what already works.
To dig into what that looks like inside CloudSuite Distribution, we sat down with Nick Perry, Account Manager for Technology at Infor, and Omar Jeelani, Solutions Consultant at Infor. Both led customer demos for Velocity Suite, Infor’s cloud-based AI and automation package built for its Infor CloudSuite Distribution ERPs.
In this Q&A, they cover what Velocity Suite includes, how process mining and AP automation work in CSD, what generative AI is live today, and what AI agents will do next.
Nick: When we started building this about two years ago, we talked to our customer base and heard the same three things:
→ They didn’t know where to start with AI.
→ They didn’t have the staff — most don’t have machine learning engineers sitting around.
→ And they had tried AI before and didn’t see the return.
Velocity Suite is our answer. It’s a package, all-inclusive, with unlimited use. Whether one person or fifty are running it, the price is the same.
It has three parts: process mining to diagnose how work moves through your business, automation to handle the manual steps, and generative AI to optimize.
The key thing to know is that Velocity Suite is built by Infor specifically for our cloud ERPs, with use cases tailored for CSD. It’s not a third-party add-on. It runs inside CloudSuite Distribution.
Nick: About 80 percent comes out of the box. We built the use cases based on what CSD customers told us they wanted to fix. The remaining 20 percent is for your configuration, because every distributor is a little different. So you’re not reinventing the wheel — you start with something that already works.
Omar: Process mining is our north star. It pulls data from how your team uses CSD day to day, and it surfaces two things: where users are straying from the best path, and where they are getting stuck.
Take procure-to-pay, as an example. We can show every variation of how users complete the process — where they skip steps, add steps, or do things out of order. We attach a time metric, so you see the average end-to-end cycle for your whole company. In one demo, it was 35 days. From there you can drill in by buyer, vendor, warehouse, or company.
The best part is the conformance analysis. It maps every variant path against the best practice and shows the cost. If a buyer is creating a back-order line where they shouldn’t, the system flags it and tells you how much time it’s adding.
That’s the input that tells you where to automate next.
Omar: Let’s say a vendor sends an invoice as a PDF to your AP inbox. Behind the scenes, the bot reads that inbox, finds the unread email, and downloads the PDF for you. From there, it pulls out the key fields — invoice number, PO, line items, and so on — using generative AI. The nice part is there are no templates to maintain. It adapts to different invoice formats on its own, so you’re not setting up rules for every vendor.
Once the data is extracted, the system checks it against CSD. For example: Does the PO exist? Has it been received? Are the quantities in tolerance? Those are checks that an end user might normally spend a few minutes on per invoice. Now the system handles them automatically.
If everything checks out, the invoice flows straight into CSD and Infor Document Management. Anything that fails a check is sent to a workspace where your AP team can review it.
Nick: And you set the schedule — hourly, daily, whatever fits your operation. Your team gets a notification when invoices come through and only steps in for the exceptions. Everything AP-related lives in one workspace, so they’re not jumping between screens to track it down.
Nick: We call them embedded experiences — a chat panel inside CloudSuite. The difference between this and a ChatGPT is that it has access to your ERP data. So instead of clicking around to find what you need, you can prompt it to write a dunning letter, summarize a vendor, or translate an invoice that came in another language.
Omar: Two quick examples—a credit manager can pull up a customer with a past-due balance and generate a dunning letter with one click. The system uses the balance, the risk category, and the history to draft it. You can edit it if you need to, but you’re not starting from scratch.
The product advisor is another one. Say you’re newer on the customer service team and a customer asks about a PVC pipe. The advisor pulls the product details and gives you a summary — common installation issues, defects, limitations. It gives you a leg up on the call.
Behind the scenes, everything runs over a secure connection, and your data is never used to train the AI model.
Nick: Two big things. First is the GenAI Assistant with Knowledge Hub. Today, finding a specific document in Infor Document Management is still a manual hunt. With the Knowledge Hub, you can prompt the system — “show me all invoices over a certain amount from this vendor in the last three months” — and it surfaces them.
The second is AI agents. Instead of prompting AI and waiting for an answer, agents go out and act on your behalf. They gather information, reason through it, make decisions, and come back with the result.
We’re also rolling out an agent factory. We’ll ship pre-built agents, but if your use case isn’t covered, you can build your own. It’s more hands-on, better suited to a technical user, but it’s there if you need it. Infor is moving fast in this space, and we’re open to co-innovating with customers who bring us a specific use case.
This six-question Q&A only scratches the surface of what’s available and to come. In the full session, Omar demos process mining on a live procure-to-pay cycle, walks through AP invoice automation end to end, and shows generative AI running inside CSD. Nick covers the full Velocity Suite catalog and the AI agent roadmap.
Nick Perry is a diligent and results-driven sales leader with over 12 years of experience across a variety of industries and business domains. He is proficient in navigating complex sales cycles and effectively communicating the value of innovative solutions to diverse prospects and clients.
Omar Jeelani is a Solutions Consultant on the Technology & Innovation team at Infor. He works closely with customers to demonstrate how Infor’s suite of advanced technologies can help transform their businesses. Omar has a strong passion for technology and has developed deep expertise across Infor’s technology platform, including the API Gateway, Data Fabric, Robotic Process Automation, Artificial Intelligence, and related capabilities.
Artificial intelligence is rapidly changing the cybersecurity landscape, and not just for defenders.
While AI is helping organizations improve threat detection, automate response times, and strengthen security operations, it’s also giving cybercriminals new tools to launch faster, smarter, and more convincing attacks. What once required advanced technical expertise can now be automated, scaled, and personalized in ways that are reshaping how breaches happen.
The result is a new era of cyber risk where traditional warning signs are disappearing, attacks are becoming harder to detect, and organizations are being forced to rethink what a modern cybersecurity strategy looks like.
For years, phishing emails were relatively easy to identify. Poor grammar, generic messaging, suspicious links, and awkward formatting often exposed malicious intent before damage was done.
AI has changed that completely.
Today’s attackers can use Large Language Models (LLMs) to generate highly polished phishing campaigns that mimic real communication styles, reference current projects, and personalize messages using publicly available information gathered from websites, LinkedIn profiles, and social media accounts.
Instead of sending one generic email to thousands of recipients, attackers can now create thousands of unique, highly targeted messages in seconds.
This trend is extending beyond email as well. AI-driven “vishing” attacks (voice phishing scams) are becoming increasingly common. Using only a small amount of publicly available audio, cybercriminals can clone voices and impersonate executives, coworkers, vendors, or even family members over the phone.
The goal is no longer simply to trick users with suspicious links. The goal is to build trust quickly enough to manipulate decisions before victims realize something is wrong.
One of the most alarming developments in AI-driven cybercrime is the rise of deepfake technology.
AI-generated video and voice cloning tools are becoming more realistic, more accessible, and easier to deploy. Criminals can now recreate a person’s facial movements, tone, speech patterns, and voice with startling accuracy.
In one widely publicized 2024 case, an employee at a multinational company joined a video conference call with what appeared to be several coworkers and executives. During the meeting, the employee was instructed to process a large financial transaction.
Believing the call was legitimate, the employee transferred $25 million. The individuals on the call were AI-generated deepfakes.
Cases like this demonstrate how AI is eroding traditional forms of trust and verification. Organizations can no longer rely solely on visual confirmation, caller ID, or familiar voices as proof of legitimacy.
Phishing and impersonation are only part of the problem.
AI is also accelerating the development of adaptive malware and automated cyberattack tools. Emerging “Crime-as-a-Service” platforms like WormGPT and FraudGPT are lowering the barrier to entry for cybercriminals by helping generate phishing kits, malicious code, attack scripts, and social engineering content automatically.
Some forms of AI-assisted malware can even modify portions of their own code to avoid detection by traditional antivirus software. These polymorphic threats are harder to identify because they continuously change their appearance and behavior.
This creates a dangerous shift in the threat landscape:
You no longer need to be an expert programmer to launch sophisticated cyberattacks. AI is increasingly doing the heavy lifting for attackers.
While AI is creating new challenges, it is also becoming one of the most important tools available to modern cybersecurity teams.
Organizations are increasingly using AI-powered security solutions to:
Instead of relying solely on manual monitoring, AI can analyze millions of security events, endpoint activities, login attempts, and network behaviors simultaneously. This allows security teams to identify anomalies and respond to threats far more quickly than traditional methods allow.
Behavioral identity verification is another growing area where AI is strengthening defense strategies. Modern security tools can analyze “micro-behaviors” such as typing patterns, navigation habits, login timing, and device usage to identify suspicious activity, even when valid credentials are being used.
In many cases, AI helps organizations move from reactive security models to proactive threat prevention.
The reality is that AI is benefiting both attackers and defenders at the same time.
Cybercriminals are using AI to automate attacks, improve impersonation, and scale phishing campaigns. Meanwhile, organizations are using AI to improve visibility, accelerate response times, and strengthen threat detection capabilities.
This has created a cybersecurity environment where speed matters more than ever.
Organizations that rely on outdated tools, limited monitoring, or manual processes may struggle to keep pace with increasingly automated threats. At the same time, companies that combine intelligent security technologies with experienced human oversight are often better positioned to reduce risk and respond quickly to incidents.
The future of cybersecurity will not be about replacing people with AI. It will be about empowering security experts with AI-driven visibility, automation, and insight.
As cyber threats continue to evolve, organizations need more than basic antivirus software and periodic monitoring. Modern cybersecurity requires visibility across endpoints, networks, users, and infrastructure, along with the ability to respond quickly when threats emerge.
Aktion Managed Security Services helps organizations strengthen their cybersecurity posture through a combination of:
Our approach focuses on helping organizations identify vulnerabilities earlier, improve response times, and reduce the operational burden on internal IT teams. Most importantly, we recognize that effective cybersecurity is not just about technology. It’s about combining intelligent tools with experienced experts who understand how threats are evolving and how businesses can adapt.
AI is changing cybersecurity rapidly, for both attackers and defenders. The organizations that succeed will be the ones prepared to evolve with it.
If you’d like to discuss your current cybersecurity environment, evaluate potential risks, or explore ways to strengthen your security strategy, the Aktion team is here to help.
Modern Finance and IT teams are under pressure to deliver more with fewer resources. Keeping systems stable, ensuring accurate reporting, supporting audits, and advancing digital initiatives often stretch mid-market organizations thin. Pain compounds when they rely on disconnected tools, manual workarounds, or aging technology.
These inefficiencies don’t just slow the business down. They increase risk, reduce visibility, and keep talented people focused on low‑value work instead of strategic initiatives. Traditional custom development isn’t always realistic. It requires time, budget, and specialized technical skills many teams simply don’t have.
That’s where low code business process automation can have immediate impact.
Modern ERP platforms such as Acumatica include low‑code/no‑code capabilities through the xRP framework, giving organizations built‑in tools to automate and modernize processes without purchasing additional software. With Aktion’s support, organizations strengthen controls, reduce manual work, and align automations with compliance and long‑term operational goals.
Finance and IT teams today face growing workloads and rising expectations. Manual processes, spreadsheets, and siloed systems pile on friction and introduce avoidable risk.
Low-code business process automation gives teams the ability to improve workflows without heavy coding or full custom development.
Low‑code business process automation lets businesses create, improve, and scale workflows using visual tools rather than building everything through custom code. Teams can digitize and improve processes using templates, conditional logic, and drag‑and‑drop components.
This approach reduces development time, minimizes errors, and accelerates modernization — especially for organizations with lean IT departments.
Most mid‑market organizations operate with lean teams, rising digital expectations, and limited resources. Low‑code automation helps close the gap between what the business needs and what current systems can support without requiring full custom development or large technical teams.
By automating repetitive, rules‑based workflows, teams can:
Low‑code automation doesn’t replace people; it frees them to focus on higher‑value, more satisfying work.
Because automation is embedded within the ERP, Finance teams can configure approvals, reconciliations, or reporting schedules without disrupting the processes they rely on. With Aktion as your partner, every workflow is aligned to financial controls, compliance standards, and long‑term modernization goals.
Low‑code automation is accelerating in mid‑market organizations for a few key reasons: speed, control, and impact.
At Aktion, we focus on principles that ensure automation is deployed effectively and sustainably:
Let’s move from theory to real‑world application.
Low‑code automation is ideal for workflows that are repetitive, high volume, data‑heavy, or dependent on spreadsheets.
Across distribution, manufacturing, construction, project‑driven services, and the mid‑market more broadly, some of the highest‑value use cases include:
Finance teams feel process bottlenecks more than almost any other department. Low‑code tools streamline high‑volume workflows such as:
These automations reduce manual entry, enforce controls, and strengthen reporting accuracy.
Operational teams benefit from real-time speed and consistency:
Low‑code automation helps customer-facing teams maintain consistent follow‑through:
These workflows reduce administrative overhead and elevate the customer experience.
You don’t need a full transformation effort to see value from automation. Many mid‑market organizations start small, gain confidence, and scale from there.
Here’s a practical roadmap:
Start with processes that are:
Strong initial candidates include expense approvals, invoice matching, commission tracking, and quote or purchase request workflows.
Involve:
A small pilot team ensures the workflow matches business needs, control requirements, and user expectations. Early feedback helps identify gaps before broader rollout.
Track:
Low‑code tools make iteration fast, so refinements can be made without disrupting operations.
Once you’ve proven value, expand to higher-impact workflows and connect automations across ERP, CRM, supply chain, or financial systems.
With Acumatica’s xRP platform, teams can build and maintain automations natively within the ERP, ensuring:
With Aktion as your partner, expansion stays aligned with regulatory requirements, internal controls, and long‑term modernization goals.
A phased roadmap allows organizations to:
Low‑code automation becomes a scalable, strategic way to strengthen your operational foundation.
Acumatica enables organizations to automate processes directly inside the ERP, with drag‑and‑drop workflow tools, built‑in logic, and robust integration capabilities.
This helps teams streamline processes without bolting on extra tools or introducing data silos.
With Aktion’s modernization and ERP expertise, organizations gain a structured, low‑risk path to:
Aktion brings:
It means your team can streamline and digitize complex workflows without hiring developers or building custom software. The result is time savings, reduced manual work, and stronger operational consistency.
Low‑code platforms offer drag‑and‑drop tools plus optional scripting for more advanced users. No‑code platforms rely entirely on visual tools. Most modern ERP platforms blend both approaches so organizations can scale safely.
Yes. Modern solutions—like Acumatica’s xRP platform—include robust APIs, connectors, and real-time data capabilities designed specifically for ERP‑to‑process automation use cases.
Absolutely. Enterprise-grade platforms offer granular permissions, audit trails, encryption, and governance features that align with U.S. compliance and reporting standards.
Start with processes that are repetitive, rules‑based, and manual—such as expense approvals, invoice matching, recurring reports, or onboarding workflows.
Ideally both. Business users contribute process knowledge, while IT ensures performance, data integrity, and long‑term scalability.
Most companies see value within weeks when automating high‑frequency tasks in functions like Finance, Operations, and Customer Service.
