The next wave of competitive differentiation lies in embedding artificial intelligence (AI) directly within ERP/MIS systems - not as an add-on, but as a native capability driving data, decision-making, and automation across operations.
Must-Have AI Features in your next ERP: Why AI-Enabled ERP Is a CEO's Best Investment
Article from | HiFlow Solutions
CEOs across the packaging and label converting industry are asking a pressing question:
“Do we need a strategy that leverages AI—or can we afford to wait?”
The answer is becoming clear. Growth and margin pressures in 2025 and beyond demand more than incremental process improvement. Packaging manufacturers face converging challenges—tight labor markets, supply chain disruptions, fluctuating material costs, and buyer expectations for faster, more customized production. Legacy ERP systems, built for linear workflows, struggle to keep up.
The next wave of competitive differentiation lies in embedding artificial intelligence (AI) directly within ERP/MIS systems—not as an add-on, but as a native capability driving data, decision-making, and automation across operations.
The New AI Divide: Leaders vs. Laggards
Recent research highlights a widening performance gap between digitally mature manufacturers and those relying on legacy processes. According to a 2025 NAPCO Research study, over 85% of packaging and print executives consider AI critical to maintaining competitiveness, and adoption is accelerating in areas like estimating, workflow automation, and prepress.
Digital leaders—those who have begun integrating AI into core systems—are seeing measurable results. Industry benchmarks show they achieve:
- 30–50% faster quote-to-cash cycles
- Up to 70% fewer order errors and production delays
- 5–15% higher gross margins due to improved accuracy, efficiency, and pricing precision
The message is clear: as AI becomes embedded within enterprise platforms, the companies that adopt early will define the industry standard for speed and responsiveness.
Where does implementing AI make sense?
AI is already reshaping how manufacturing organizations operate—especially in functions where structured data, repetitive workflows, and time-sensitive decisions intersect. Within ERP systems, several key areas stand out for their immediate value and measurable ROI. Aside from shop floor applications, here are five areas where packaging and print manufacturers can find value with AI.
AI in Estimating: Smarter Quotes, Consistent Margins
Estimating has traditionally relied on human judgment, tribal knowledge, and static spreadsheets. As product configurations and materials multiply, this approach can’t scale.
AI-driven estimating uses machine learning to evaluate the optimal manufacturing path based on a product’s dimensions, substrate, ink type, and finishing requirements. It automatically compares production options against available machinery, costs, and scheduling windows to generate the most efficient route.
When data is incomplete, AI can prompt for clarification or pull information from previous jobs, ensuring every estimate conforms to company standards and capabilities. The result:
- Quotes produced in minutes instead of hours
- Fewer pricing errors or margin erosion
- Consistent, data-backed cost models across estimators
For manufacturers juggling hundreds of daily quote requests, this acceleration directly translates to faster customer response, higher win rates, and stronger profitability.
AI in Purchase Order Processing: Orders That Process Themselves
Manual purchase order (PO) processing remains a costly administrative burden. Staff often rekey data from emails or PDFs, validate product details, and manually push orders into production. AI now automates this entire chain.
Through document intelligence, AI reads and interprets incoming POs, extracting line-item details, quantities, pricing, and delivery dates. It validates data against the ERP’s master records, flags inconsistencies, and corrects them before orders enter the production queue.
The benefits are tangible:
- Up to 90% reduction in manual data entry
- Faster order-to-production handoffs
- Significant reduction in downstream errors
This isn’t just about automation—it’s about process acceleration. When orders move from inbox to scheduling in seconds, companies gain real-time visibility and can adapt faster to customer demand.
AI in Supplier Delivery and Price List Management
Supply chain unpredictability has made real-time data synchronization essential. Historically, supplier price changes and material updates required manual review, often leading to discrepancies between purchasing, costing, and quoting systems.
AI simplifies this by interpreting supplier price lists and matching them automatically with internal material codes. It identifies deviations, flags outdated data, and updates cost records across the ERP.
This ensures every quote and purchase reflects current supplier pricing, minimizing cost leakage and margin variance.
In logistics, AI automates the registration of incoming shipments and delivery notifications, parsing ASNs and shipping manifests directly from supplier emails. This delivers:
- Near real-time inventory visibility
- Reduced lead time for materials availability
- Elimination of manual receiving errors
For packaging manufacturers, where materials often represent 50–70% of job cost, this automation protects margins while increasing supply chain agility.
AI in Logistics and Invoicing: Automating the Back End
The administrative side of manufacturing—proof-of-delivery, invoicing, and reconciliation—has long been a pain point. AI brings precision and speed to these processes.
Using optical character recognition (OCR) and natural language processing (NLP), AI systems can parse scanned Bills of Lading (BOLs), invoices, and credit memos—no matter the format. The technology identifies key fields (PO numbers, quantities, dates), matches them to shipping or purchase records, and reconciles automatically within the ERP.
This reduces cycle times and minimizes the need for manual review. Finance teams gain confidence in data accuracy, and customers benefit from faster, more reliable billing.
AI in Accounting: Automating the Back Office
Accounting has traditionally been one of the most manual, time-consuming areas of manufacturing operations. Processing supplier invoices, validating purchase orders, and reconciling cost data require significant administrative effort — and even a small delay can ripple across purchasing, production, and financial reporting.
AI-powered Accounts Payables processing is transforming this critical function by replacing human data entry with intelligent automation. Instead of manually keying in invoice details or building complex EDI integrations, AI reads, validates, and records invoices directly from email attachments — whether they
The result is an end-to-end automated accounts payable workflow that dramatically reduces time, effort, and errors.
- Cuts invoice processing time from hours to minutes
- Frees finance teams from repetitive entry, allowing focus on analysis and cash management
- Automatically captures and records invoices in near real time
In a manufacturing context, where margins are tight and volumes high, the ability to process hundreds of invoices daily without error translates directly into stronger cost control and faster month-end closing.
The ROI of AI: Measuring What Matters
AI’s ROI in ERP systems is both operational and strategic.
1. Speed and Throughput
AI accelerates every step of the quote-to-cash cycle—estimating, ordering, production, and billing. A process that once took days can now be executed in minutes, compressing delivery timelines and improving cash flow.
2. Error Reduction
By automating data capture and validation, AI cuts rework, material waste, and customer credits—areas that can silently erode margins.
3. Labor Efficiency
With administrative tasks automated, teams can refocus on value-added activities like pricing strategy, customer service, and process improvement.
4. Data Capital
Each AI transaction enriches an organization’s data foundation. Over time, this enables predictive analytics—forecasting demand, optimizing machine utilization, and identifying cost anomalies.
Studies across manufacturing show that AI-enabled firms realize 15–25% productivity gains and achieve payback on AI investments within 6–12 months, particularly in document-intensive workflows like estimating and PO processing.
Conclusion
AI in ERP is no longer optional—it’s essential infrastructure for manufacturers navigating complexity, labor shortages, and rising customer expectations.
Those who embrace AI as a strategic investment—not a novelty—will capture new efficiencies, protect margins, and scale intelligently. The future of packaging manufacturing won’t be defined by machines or materials, but by how intelligently the enterprise operates.
The question for every manufacturing leader is no longer “Should we use AI?” — but “How fast can we integrate it into the heart of our business?”
HiFlow ERP/MIS can deliver on the promise of AI. From AI-powered estimating that accelerates quoting, to purchase order automation that eliminates bottlenecks, to supplier processing that reduces costs and errors—HiFlow’s AI modules show how intelligence built into workflows produces measurable savings, sharper decision-making, and greater agility. For packaging manufacturers facing tariffs, labor shortages, and relentless competition, HiFlow’s AI-powered ERP is not just a system upgrade—it’s a pathway to sustainable growth and future-proof operations.
The content & opinions in this article are the author’s and do not necessarily represent the views of ManufacturingTomorrow
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