For many B2B companies, the order-taking process is a mix of emails, phone calls, forms, and follow-ups. It works — until it doesn’t. Slow turnaround times, input errors, and unclear requests all introduce friction. AI offers practical ways to clean this up, reduce costs, and improve service.

McKinsey reports that companies using AI in customer operations have seen an average 35% drop in operating costs and a 32% increase in revenue. These gains come from better efficiency, fewer mistakes, and faster response times.

Here are six ways AI is being used to improve the order-taking experience:

1. Freeform Input → Structured Orders: Customers often describe what they need in loose, informal language. AI can translate that input into structured data — matching product specs, confirming details, and reducing back-and-forth.
2. Dynamic, Contextual FAQs: Rather than relying on static FAQ pages, AI can provide real-time answers based on your documentation. Customers can ask specific questions and get accurate, product-level responses.
3. Visual Input for Instant Identification: With AI, customers can upload photos or schematics to identify parts, find compatible alternatives, or check for fit. This helps when exact part numbers aren’t available or when visual recognition is faster.
4. Guided Configuration Conversations: For configurable or complex products, AI can guide users through decision points. It asks relevant follow-up questions and narrows options based on use case — similar to how a sales engineer would.
5. Preemptive Error Detection: AI can detect issues before an order is submitted — like unusual combinations, missing values, or specs that don’t match historical orders. It adds a layer of quality control early in the process.
6. Auto-Generated Order Summaries: Before an order is finalized, AI can summarize it in clear, readable language. This helps ensure alignment between what the customer described and what’s being delivered.

These tools are already in use. Manufacturers like Siemens, Faurecia, and Hitachi already use AI to improve workflow, maintenance, and supply chain planning. A recent survey of manufacturers showed that they plan to dedicate 44% of their recent tech budgets to AI initiatives.

The takeaway: AI isn’t replacing your team — it’s helping them work smarter and deliver a better customer experience.

About apHarmony

apHarmony is a Chicago-based custom software development firm specializing in manufacturing and industrial automation. With over a decade of experience and ISO 9001 certification, we help companies streamline complex workflows, modernize legacy systems, and integrate AI-driven tools that deliver measurable business results. From real-time order dashboards to customer portals and advanced configurators, our solutions are built to drive efficiency, reduce risk, and support growth. If you’re exploring how software can elevate your operations, we’d love to hear from you. Talk to you soon!

The AI landscape in 2025 is flooded with potential—and false starts.

Across industries, companies have launched initiatives with high hopes. But many stall before they ever deliver real value. The pattern is consistent: early excitement, a flashy demo, and then… nothing. The model can’t scale. The results aren’t consistent. The data isn’t usable. The project dies quietly.

And this pattern is accelerating.
This year, S&P Global reports that 42% of companies have shut down the majority of their AI initiatives—nearly triple the rate from the year before. MIT adds another layer: 95% of generative AI pilots fail to exit the testing phase.

These aren’t growing pains. They’re signs of a deeper design flaw.

What’s going wrong?

The core problem is this: most AI projects fail because they aren’t designed with operational realities in mind.

If you want AI to work at the heart of your business, you need to architect it like infrastructure.

That begins with Retrieval-Augmented Generation (RAG). Instead of trying to embed all your knowledge into the model—which becomes brittle and outdated—you keep your source of truth in structured documents, databases, and wikis. The model retrieves information as needed. It doesn’t “know” your policy—it looks it up.

Once that layer is in place, the next step is action. You don’t want AI that just talks. You want it to do things. That’s where Model Context Protocol (MCP) comes in. MCP lets the AI interact with your systems—pulling real-time order data, escalating tickets, or updating records—with transparency and control.

Finally, when your use case demands high-volume context-heavy prompts, fine-tuning locks it in. Instead of performing lookups each time, you embed that information directly into the knowledge base of the model.

This layered approach is not only more resilient—it’s safer, more maintainable, and more scalable. It’s also the path that reliably leads to production success.

The best AI projects combine these solid architectural foundations with your unique business value proposition, to take your customer experience to new heights, and deliver your brand promise on every aspect of the customer journey.

And it works.
We’ve built systems where frontline staff ask questions in plain language and get answers sourced directly from their documentation. Where AI reads incoming forms and routes them instantly. Where dashboards don’t just report problems—they recommend next steps.

The best AI projects don’t start with the flashiest ideas.
They start with the most useful ones.

About apHarmony

At apHarmony, we don’t chase trends—we build systems that work. Whether you’re looking to stabilize your AI stack, connect operations to real-time data, or integrate automation that actually delivers, our team is here to help. Contact us
to get started.

If you’re still processing orders manually, you’re paying a price; andnot just in dollars.

Manual order entry drains time, inflates costs, and invites mistakes. According to McKinsey, businesses that rely on manual processing spend 30% more on operational costs than those that automate. That’s money lost to inefficiency — time spent on repetitive tasks, corrections, and rework.

And it’s not just the cost. It’s the risk. Manual data entry has an average error rate of 3% — that’s 3 mistakes for every 100 orders. In fast-moving sectors, those mistakes ripple out: botched deliveries, frustrated customers, and lost trust. In a market where speed is currency, even one wrong digit in an order can turn into a reputation problem.

Automation doesn’t just reduce errors — it rewrites the entire process. One manufacturer, for example, cut their order processing time from 2–3 days down to just 1–2 hours using AI automation. That’s not just faster. It’s transformative — freeing up team bandwidth, increasing order accuracy, and accelerating cash flow.
And speed isn’t optional anymore. 90% of B2B customers now expect an immediate response when they submit an inquiry or support ticket. That means the bar for responsiveness isn’t being set by your industry. It’s being set by Amazon, Uber, and AI-driven service.

Manual processes were built for a different era. In today’s market, they’re a liability. If your customers are waiting hours — or days — for confirmation, updates, or delivery timelines, they’re already looking elsewhere.

Order entry is one of the easiest places to start automating. The ROI is fast. The lift is light. And the upside is enormous.

If you’re still on the fence, consider this: doing nothing is no longer neutral. It’s a decision to stay behind.

About apHarmony

apHarmony is a Chicago-based software development firm specializing in custom automation, workflow optimization, and real-time operational tools for manufacturers and industrial businesses. With over a decade of experience and 400+ successful projects, we help teams eliminate manual tasks, reduce errors, and dramatically increase efficiency through tailored solutions like order entry automation, customer portals, and production dashboards. If you’re still relying on manual processes, it’s time to explore what automation can do for your bottom line. Contact us to talk about how we can help.

Site speed is rarely the loudest voice in a product meeting. It’s easy to put off in favor of a feature improvement or customer request. But speed is revenue. It’s one of the few levers you can pull today that will pay you back this quarter.

Look at Swappie, the online phone marketplace: they cut their mobile page load time in half and saw a 42% increase in mobile revenue. For them, that translated to millions in additional quarterly sales without adding a single new product. Vodafone trimmed load times by 31% and booked an 8% jump in online sales — that’s equivalent to adding weeks of holiday traffic overnight.

Why? Because speed determines whether customers stay long enough to buy. One to five seconds of extra load time can cut conversions by 70%. A third of customers don’t return after a slow experience. If you run a $50M e-commerce business, that’s potentially $15M of annual revenue gone because pages lag.

The fixes aren’t exotic:

• Remove render-blocking scripts so that product pages and checkout load instantly.

• Serve optimized images so that product pages pop, not crawl.

• Cache intelligently so that repeat visitors get lightning-fast experiences.

This is ROI you can measure. Launch a feature and you might get a lift in one segment. Fix speed and you lift all segments, every page, every customer.

Speed isn’t a tech metric. It’s a revenue number hiding in plain sight.

 

About APHarmony: 

apHarmony is a Chicago-based custom software studio specializing in performance-driven eCommerce development. We help businesses boost revenue by optimizing site speed, streamlining code, and delivering seamless customer experiences. Ready to turn milliseconds into millions? Contact us today to discuss your performance roadmap: Contact us!