Key Takeaways
- Machine learning for business helps automate processes that become smarter over time
- Implementing machine learning can reduce manual tasks and free up valuable employee time
- IntelliChief’s platform uses machine learning to improve workflows, reduce errors, and cut costs
- Real-time machine learning delivers continuous improvement without extensive programming
Is your organization struggling with the burden of repetitive manual tasks? Machine learning for business can revolutionize your business process automation initiatives by making them increasingly intelligent over time. By implementing machine learning to power your workflows, you can eliminate time-consuming routine tasks and enable your team members to focus on complex challenges that require human creativity and problem-solving skills.
IntelliChief leverages machine learning for business in innovative ways to help large, complex organizations streamline workflows, minimize errors, and reduce operational costs. Through the IntelliChief AI-enabled automation platform and its integrated modules, our machine learning applications continuously identify, execute, and improve processes suitable for automation.
Have a Project?
Understanding Machine Learning for Business
Machine learning applications are software solutions that utilize machine learning principles to enhance business processes while making them “smarter” through continued use. As a subfield of artificial intelligence, machine learning focuses on developing models that can make predictions and improve their performance over time.
Machine learning for business results from carefully designed algorithms, thoughtful programming, strategic planning, and ultimately, measurable performance improvements. Many organizations have adopted machine learning applications to streamline and standardize business processes, such as matching invoices against purchase orders or capturing data from documents for automatic processing and archiving.
These processes are typically repetitive, tedious, time-consuming, and potentially costly when errors occur. Business process automation that incorporates machine learning helps organizations maximize their technology investments by equipping solutions with intelligence that continually improves with experience.
In the textbook, Machine Learning by Tom M. Mitchell, Mitchell notes:
The field of machine learning is concerned with the question of how to construct computer programs that automatically improve with experience.
Machine learning applications apply this principle to your business processes and the technology that powers them. For example, IntelliChief uses a combination of intelligent capture and machine learning to support one of the most comprehensive accounts payable automation solutions available in the market.
How to Leverage Machine Learning Applications for Business
When it comes to implementing machine learning for business, the potential applications are virtually limitless. Machine learning has been deployed across industries worldwide, with valuable applications in various departments of your organization, including Accounts Payable, Accounts Receivable, Human Resources, Customer Service, and beyond.
Let’s explore several key tasks that can be enhanced or streamlined with machine learning applications for business.
Streamlining Invoice Processing
Machine learning algorithms can identify part numbers, prices, and vendor information from invoices with remarkable accuracy. Once this information is captured, it can be automatically matched against data from the original purchase order. Machine learning applications can even cross-reference part numbers to help filter out exceptions, reducing or completely eliminating the need for manual two- or three-way matching when processing invoices.
Increasing Automation Throughput
With machine learning for business, your team doesn’t need to manually calculate tolerances. Instead, invoices and sales orders are automatically read and compared against information stored in your company’s ERP systems, such as SAP ECC, SAP S/4HANA, Oracle E-Business Suite, Oracle JD Edwards, or Infor Global Solutions. This results in fewer human touches and higher straight-through processing (STP) rates.
Capturing More Vendor Discounts
Machine learning applications can read invoice due dates and determine which invoices need to be paid by specific dates to capture vendor rebates or discounts. This information can be extracted and presented during the voucher creation process with AI-enabled automation. If your company isn’t capitalizing on vendor rebates or discounts, it could be losing tens or even hundreds of thousands of dollars annually.
Collecting and Organizing Unstructured Content
Most business documents are “unstructured,” meaning they don’t arrive in a standardized format. With machine learning for business, the format of invoices or sales orders received from outside the organization becomes irrelevant. Once received, all data is captured and archived in a structured format, making processing much simpler for your team. Advanced machine learning applications can recognize data on unstructured documents, enabling seamless integration with your existing systems.
Automating Workflows Without Coding
As documents are captured, real-time machine learning applications can trigger automated workflows to keep them moving efficiently through your organization. For instance, a program that recognizes a vendor’s name could route that document to the appropriate user based on the vendor’s information. The application of machine learning in business processes eliminates the need for extensive custom coding while maintaining flexibility and adaptability.
Streamlining Audits
Have you noticed how stress levels rise when auditors arrive on-site? You’re not alone. Auditors play a vital role in verifying business compliance, but they often appear at the most inconvenient times, such as during operational crises. Machine learning software can alleviate this stress by continuously checking for issues. When discrepancies are detected, they can be promptly addressed by routing the issue directly to an employee for review, resulting in fewer audit-related interruptions and more consistent compliance.
Optimizing Customer Order Processing
Customer service representatives often spend considerable time on routine tasks like manually entering orders into ERP systems or coordinating with other departments, such as engineering or quality assurance, resulting in extended lead times. Lead time can be difficult to track, but machine learning technologies can create and route sales orders automatically, resulting in faster sales order processing that allows customer service representatives to focus on delivering exceptional customer experiences.
| Application | Business Benefit |
| Invoice Processing | Reduced manual matching, faster approvals, fewer errors |
| Automation Throughput | Higher straight-through processing rates, less manual intervention |
| Vendor Discount Capture | Increased early payment discounts, improved cash flow management |
| Unstructured Content Management | Standardized data, regardless of input format, improved searchability |
| BPA with advanced workflow | Reduced bottlenecks, consistent routing, improved process visibility |
| Audit Management | Continuous compliance monitoring, reduced audit stress |
| Customer Order Processing | Faster order fulfillment, improved customer satisfaction |
Experience Real-Time Machine Learning for Business
Does your organization struggle with inconsistent task completion? Over time, business processes tend to become less standardized as on-the-spot decisions become normalized and integrated into your workflows. Non-standardized processes become problematic when employees are absent or retire. They can also harm your business by slowing down processing queues or increasing your cost-per-transaction.
Organizations can avoid these common challenges by implementing automation technology with real-time machine learning capabilities. Process automation minimizes time and cost concerns, but with real-time machine learning for business, you can ensure that your automated processes continuously improve over time.
The learning curve is remarkably short. For example, the first time an invoice is received from a new vendor, it may require minimal manual processing; however, the next time one is received, the system will already know how to handle it. Machine learning for business helps mitigate the adaptation period necessary when new vendors are introduced or transaction volumes increase.
IntelliChief’s advanced process automation software is designed to scale with your business, allowing you to continue growing without worrying about your team’s capacity to manage increasing workloads.
Comparing Traditional Automation vs. Machine Learning
| Traditional Automation | Machine Learning Automation |
| Fixed rules and predefined logic | Adaptive rules that improve with experience |
| Requires explicit programming for each scenario | Learns from data patterns automatically |
| Limited ability to handle exceptions | Progressively improves exception handling |
| Struggles with unstructured data | Excels at processing unstructured content |
| Constant maintenance required | Self-improving with minimal intervention |
Machine Learning Applications Across Industries
The application of machine learning in business is transforming mission-critical processes across industries by enabling AI-enabled automation and intelligent decision-making. Leveraging machine learning for business empowers organizations to streamline operations, reduce costs, and enhance ROI through advanced data insights and business process automation with advanced workflow.
Manufacturing
In manufacturing, machine learning applications optimize mission-critical business processes such as predictive maintenance, quality control, and supply chain optimization. By integrating these solutions with enterprise-class ERP systems like SAP ECC and Oracle E-Business Suite, manufacturers can reduce downtime, improve product quality, and ensure seamless operations.
Retail
Retailers use machine learning for inventory forecasting, price optimization, and customer behavior analysis. These capabilities enable touchless automation (STP) of sales order management and demand planning, providing real-time analytics and process optimization that enhance customer satisfaction and profitability.
Financial Services
In financial services, machine learning applications focus on fraud detection, risk assessment, and regulatory compliance. By embedding intelligent capture and validation within ERP-integrated workflows, organizations can reduce errors, accelerate processing, and maintain stringent compliance standards.
Transportation and Logistics
Machine learning optimizes route planning, fleet management, and delivery forecasting in transportation and logistics. These applications enable organizations to streamline order-to-cash (O2C) and purchase-to-pay (P2P) processes through automated data capture and intelligent workflow management integrated with ERP platforms like Infor Global Solutions.
Implementing ML applications that seamlessly integrate with enterprise ERP systems is essential for maximizing operational efficiency and driving digital transformation. IntelliChief’s AI-enabled automation solutions combine machine learning, intelligent capture, and business process automation with advanced workflow to help organizations unlock the full potential of their data, streamline mission-critical processes, and achieve measurable ROI.
Getting Started with Machine Learning for Business
Implementing machine learning for business doesn’t require a complete overhaul of your existing systems. IntelliChief’s approach focuses on integration with your current ERP environment, whether you’re using SAP ECC, SAP S/4HANA, Oracle E-Business Suite (EBS), Oracle JD Edwards, or Infor Global Solutions.
The process typically involves:
- Identifying high-volume, routine processes that would benefit from automation
- Implementing intelligent capture capabilities to digitize and standardize information
- Configuring machine learning algorithms to recognize patterns and improve over time
- Integrating with existing ERP systems for seamless data exchange
- Monitoring performance and optimizing the system based on results
As your machine learning applications gain experience with your specific business processes, they become increasingly effective at handling exceptions and identifying opportunities for further optimization.
Transform Your Business with Machine Learning
Machine learning for business represents a significant opportunity to transform how your organization handles routine processes. By implementing intelligent automation that continuously improves through experience, you can free your team to focus on strategic initiatives while reducing costs and minimizing errors.
IntelliChief’s AI-enabled automation platform with machine learning capabilities helps large, complex organizations consolidate workflows, mitigate errors, and cut costs. Our solutions integrate seamlessly with enterprise-class ERP systems and adapt to your specific business requirements.
The future of business process automation lies in technologies that not only execute tasks but learn and improve over time. Machine learning for business delivers this capability, providing a sustainable competitive advantage in an increasingly digital business landscape.
To learn more about how IntelliChief’s AI-enabled automation platform uses machine learning to help customers work smarter, not harder, contact IntelliChief today.