Top 20 ERP Systems with Artificial Intelligence Capabilities

The use of artificial intelligence (AI) has gained considerable attention in recent times. Big players in the tech industry, such as Microsoft, Google, Meta, and Amazon, are investing their resources in AI, indicating its importance in the world. As a result, AI has become increasingly prevalent in Enterprise Resource Planning (ERP) systems. As you consider which ERP system will take your company into the future, be certain you consider a system with cutting-edge capabilities around AI.

How Can Businesses Benefit From Artificial Intelligence In ERP?

ERP is the foundation of a company’s operations, and adding AI can revolutionize how businesses operate. This is especially true for manufacturing ERP, where this integration can yield remarkable results. A few highlights include:

• Efficiency in Operations: Manufacturing involves numerous repetitive tasks. Integrating AI can help automate these, thereby speeding up business processes. For instance, consider a manufacturing line that produces electronic devices. AI can predict when particular components might run out, prompting timely reorders and preventing production halts.
• Richer Insights: AI doesn’t just collect data; it makes sense of it. ERP systems can provide deeper and more actionable business intelligence insights with AI. For example, an automotive manufacturing unit could prompt AI to analyze historical sales data and accurately forecast which car models might be in high demand in the upcoming months.
• Human Judgment + AI = Enhanced Decision Making: This isn’t about replacing humans. It’s about complementing human intelligence. With AI-augmented ERP insights, decision-makers get a clearer picture, ensuring that choices are well-informed.

AI is Improving Enterprise Resource Planning Systems

The fusion of AI and ERP is more than just a fleeting trend — it represents a strategic evolution in how businesses operate and make data-driven decisions.

AI transforms ERP systems from passive record-keepers to active advisors that continuously optimize processes, uncover insights, and enable predictive planning. ERP provides the invaluable data backbone while AI supplies the intelligence.

Together, they create a virtuous cycle where AI models extract new value from ERP data, enhancing the data available for modeling. This synergy between AI and ERP leads to increased automation, improved efficiency, reduced costs, mitigated risks, and enhanced agility.

AI Features and Technologies in ERP

Before we dive into the benefits of AI in ERP, let’s take a closer look at the features that make it all possible. These cutting-edge technologies are the driving force behind the day-to-day advantages that companies can reap by integrating AI into their operations.

Machine Learning

Machine learning allows ERP platforms to continuously analyze data, identify patterns and insights, and improve decision-making without explicit programming. This takes ERP to the next level in areas like forecasting, predictive maintenance, and process optimization.

Natural Language Processing (NLP)

With NLP, ERP systems can understand text and speech. Instead of solely relying on forms, users can interact conversationally using natural language. NLP enables features like intelligent search, contract analysis, and voice commands.

Computer Vision

Computer vision equips ERP with the ability to extract insights from images, video feeds, and scanned documents through image recognition and analysis. This facilitates quality control, guided robots in manufacturing, and document processing.

Robotic Process Automation (RPA)

RPA uses AI to automate high-volume, repetitive administrative tasks normally performed manually. Bots can continuously process invoices, update records, generate reports, and complete repetitive ERP workflows.

Analytics

Sophisticated machine learning algorithms help ERP platforms uncover deep data insights that would be impossible to discover manually. This provides invaluable visibility for forecasting, decision support, and strategic planning.

Smart Assistants

Chatbots and virtual agents allow users to interact with ERP systems conversationally using natural language. These AI-powered assistants can answer queries, take action, and provide recommendations.

Generative AI

Generative AI models can automatically create new content like summaries, reports, and documentation based on ERP data. This augments human capabilities by automating routine writing and analysis tasks.

Reaping the Benefits of AI-Enabled ERP

Now that we’ve explored the key AI technologies powering modern ERP systems let’s examine the many benefits this integration unlocks for organizations:

• Increased Efficiency: By automating repetitive tasks and business processes, AI reduces manual work and allows employees to focus on high-value activities.
• Enhanced Insights: Sophisticated AI algorithms uncover deep insights from ERP system data that would be impossible to discover manually. This empowers data-driven decision-making.
• Improved Forecasting: Machine learning applied to historical data enables highly accurate demand forecasting, risk prediction, and trend analysis.
• Reduced Downtime: Predictive maintenance leveraging AI prevents equipment failures and avoids disruptive downtime.
• Higher Quality: Computer vision AI spots defects and anomalies to improve quality control and reduce waste.
• Better Resource Allocation: AI modeling optimizes inventory, production planning, staffing, and resource allocation based on demand.
• Lower Operational Costs: Automating manual work reduces labor costs. Predictive analytics further optimizes operations to cut costs.
• Increased Revenue: NLP chatbots improve customer experience. ML sales analytics informs you of upsell opportunities. Overall, AI boosts sales and retention.
• Enhanced Security: Continual AI monitoring detects potential fraud and cyber threats early.
• Democratized Insights: AI makes data insights more accessible to employees across the organization, not just analysts.

While the specific use cases may differ, AI offers immense potential regardless of industry or business function. With AI technologies’ continued maturity and ERP platform evolution, virtually every enterprise can realize benefits. The examples here showcase only a fraction of what is possible. As AI capabilities grow more advanced in the years ahead, so will the breadth of potential applications.

Use Cases and Impact Across Industries and Departments

The benefits we’ve discussed can be seen across industries and departments within businesses of all sizes. Here are some specific examples:

Industries:

• Manufacturing: AI provides intelligent manufacturing, optimizes production planning, enables predictive maintenance, and leverages computer vision for quality control. This leads to increased output, lower costs, and higher-quality products.
• Distribution: AI analyzes data to optimize logistics and inventory management, improving delivery times and proactively managing disruptions.
• Automotive: AI informs design changes, optimizes manufacturing, customizes marketing, guides autonomous driving, and facilitates predictive vehicle maintenance.
• Aerospace & Defense: AI optimizes intricate supply chains, production scheduling, inventory management, and quality control for complex defense projects.
• Oil & Gas: AI guides robotic inspections, predicts equipment failures, increases drilling accuracy, and informs exploration strategies through data analysis.
• Industrial Machinery: AI boosts uptime through predictive maintenance and optimizes production quality and efficiency for machinery builders.

Departments:

• Finance: AI can automate business processes like auditing and reporting while detecting fraud, forecasting earnings, and informing investment strategies through advanced analytics.
• HR: AI chatbots handle frequent employee inquiries while also analyzing HR data to refine hiring practices, identify retention risks, streamline payroll, and inform talent development programs.
• Customer Service: AI chatbots and virtual agents enable ²⁴⁄₇ automated customer service. NLP allows quick responses to queries, while machine learning recommends solutions based on past resolutions.
• Sales: AI analyzes customer data to predict needs, identify upsell opportunities, optimize pricing, and tailor promotions to boost revenue.
• Procurement: AI forecasts demand to optimize purchases, identifies cost-saving suppliers, and automates purchasing workflows.
• IT: AI handles level‑1 support queries, automates help desk tickets, monitors systems, and predicts security threats.
• Logistics: AI plans optimal delivery routes, tracks shipments, and proactively manages potential supply chain disruptions.
• Accounting: AI automates invoice processing, AR/AP, expense reporting, and reconciliation while flagging anomalies.

The Top AI-Enabled Modern ERP Systems

Through extensive research on enterprise software providers, we’ve identified the ERP systems with the most robust integration of artificial intelligence capabilities. These vendors are leading the way in leveraging AI to transform ERP functionality.

As AI technology progresses rapidly, we will periodically update this list to reflect new AI feature releases from these established vendors and emerging players. Our evaluation criteria focus on the breadth and depth of AI capabilities and how seamlessly they are incorporated into the ERP experience.

Oracle

As a prominent enterprise software provider, Oracle has focused extensively on integrating artificial intelligence and machine learning into its ERP software solutions. Oracle leverages AI to optimize operations and boost user engagement across sectors, including finance, manufacturing, and supply chain management.

• Oracle AI Apps for ERP: Cloud applications designed for business optimization, encompassing Supplier Recommendations, Intelligent Payment Discounts, Automated Expense Audits, Procure-to-Pay, and Order-to-Cash.
• Oracle Cloud Infrastructure (OCI) AI Services: Broad industry applications like finance, HR, marketing, and manufacturing, offering features from natural language processing to predictive analytics.
• Oracle Generative AI: Services range from large language models to conversational AI, all made user-friendly and scalable.
• Machine Learning Services: Tools for data scientists to develop, execute, and manage tailored learning models.

Acumatica

Acumatica has incorporated various AI and machine learning capabilities into its ERP software to automate workflows, provide interactive assistance, and improve overall efficiency. Key features focus on accounts payable, reporting, warehouse management, and customer support.

• AP document recognition: Reducing manual input via AI-powered document creation.
• Natural language search: Simplifying data retrieval and analysis.
• Helpdesk self-support: AI-driven tools for problem-solving and user support.
• Warehouse shipping and receiving: AI-enhanced efficiency in warehouse tasks.
• Guided reporting and analytics: Data insights driven by AI algorithms.

Epicor

Epicor utilizes artificial intelligence and machine learning within its ERP platforms to meet the evolving needs of the manufacturing industry, distribution, retail, and automotive companies. Epicor concentrates its AI efforts on data analytics, digital assistants, and enhancing the user experience.

• Epicor Data Analytics: Machine learning insights for better data understanding.
• Epicor Virtual Agent (EVA): An AI chatbot with task execution, NLP, and alerts.
• Epicor Kinetic Design: AI-driven design for user-centric applications.
• Machine Learning Component: Continuous learning for better user assistance.

IFS

IFS provides an extensive suite of AI functionalities deeply embedded across its solutions. IFS AI aims to deliver an interactive user experience, proactive productivity features, and data-driven insights focused on optimization and simulation.

• Co-pilot: A conversational AI assistant for intuitive user interactions.
• AI-powered Automation: Workflow enhancements and reduced manual work.
• AI-powered Optimization: Advanced algorithm-driven efficiency improvements.
• AI-powered Analytics: Predictive tools for data-driven decisions.
• AI-powered Simulation: Modeling and forecasting for better strategy planning.

Infor

Infor offers a robust enterprise-grade AI platform to help businesses quickly realize value across operations, forecasting, pricing, asset management, and human resources. Infor provides both broad horizontal AI capabilities as well as industry-specific solutions.

• Operational Intelligence: Automated process initiation for efficiency.
• Asset Intelligence: Predictive analytics for better asset management.
• Forecast Intelligence: Data-driven forecasting tools.
• Customer Sales Intelligence: Insights into customer preferences for strategic sales.
• Pricing Decision Intelligence: Data analytics for investment pricing.
• Human Capital Intelligence: AI tools for improved HR management.
• Coleman AI: Comprehensive AI algorithm library and rapid deployment tools.
• Augmented Intelligence Service: Business-focused AI solutions.
• Coleman Digital Assistant: NLP-powered conversational tool.

Microsoft

Microsoft Dynamics 365 integrates AI through Microsoft’s Dynamics 365 Copilot initiative, which focuses on augmenting human capabilities across sales, marketing, e‑commerce, supply chain management, and customer service functions.

• Sales Optimization: AI-driven tools for better sales communications and CRM navigation.
• Enhanced Customer Service: AI tools for responsive customer interactions.
• Marketing and Customer Insights: Personalized marketing and workflow tools.
• Online Commerce Efficiency: AI tools for seamless product listing and description creation.
• Supply Chain Management: Predictive tools for supply chain efficiency.
• Real-time Assistance: Immediate insights across business operations.
• AI-driven Forecasting: Predictive analytics for demand forecasting.
• Pricing Decision Support: Data-driven tools for pricing strategies.

SAP

SAP, a leader in ERP solutions, has embraced AI primarily through SAP Business AI, which is tailored for business process optimization, and SAP Joule, a generative AI assistant designed for intuitive user interactions.

• Industry-Specific AI: Tailored AI solutions for industry relevance.
• Ethical AI Deployment: Ensuring AI is utilized responsibly.
• Integrated AI: AI-driven cohesion among various departments.
• Agile Decision-Making: Quick decision tools based on AI insights.
• Task Automation: AI tools for repetitive task efficiency.
• Joule — The AI Copilot: Personalized assistance, on-demand insights, and secure AI functionalities.

With their AI integrations, these ERP systems are reshaping how businesses operate and make decisions, highlighting a new era of automation and intelligence. We’ll keep updating this list as more vendors add new AI features.

The Cost of ERP with AI

One question that we see is whether integrating AI into ERP platforms substantially increases costs compared to more traditional ERP software.

The answer depends on multiple factors:

• AI-enabled ERP is not necessarily more expensive upfront. Many vendors now include basic AI capabilities like virtual assistants and basic predictive analytics as part of their core ERP system license cost or monthly subscription fees.
• However, more advanced AI capabilities like computer vision quality control or complex predictive modeling will likely incur additional fees and require customized integration services — the more extensive the AI tools, the higher the cost.
• Cloud-based ERP systems tend to make AI integration more affordable, leveraging economies of scale. On-premise systems require more in-house infrastructure and expertise for advanced AI.
• The vendor’s AI prowess matters. ERP providers newer to AI may charge premiums, while those with mature AI abilities may include it more seamlessly.
• Customizing AI to specific business needs adds cost. Out-of-the-box AI provides more general capabilities.

The bottom line is integrating AI does not automatically make an ERP system drastically more expensive. However, the more customized and pervasive the AI capabilities required, the more impact on overall cost. Assessing needs and vendors carefully is key to budgeting appropriately. The productivity gains from AI often deliver ROI.

Implementation Considerations

Once an AI-driven ERP system is selected, integrating it successfully requires an ERP implementation plan that accounts for the following:

• Change Management: Prepare staff for the AI-enabled ERP through training and communication. Have change champions who can answer questions and assist with adoption.
• Data Preparation: Scrub and structure data to train AI models. Create pipelines for ongoing data feeds to drive continuous learning.
• Customization: Work with vendor consultants to tailor AI models and system workflows to your business. Validate accuracy.
• Integration: Develop interfaces connecting the AI ERP with legacy systems, IoT infrastructure, and data repositories.
• Testing: Thoroughly test the system using actual company data sets before launch. Assess usability and user experience.
• Monitoring: Track AI model performance post-launch using accuracy metrics and model governance tools. Retrain periodically.
• Security: Conduct cybersecurity audits, access controls, and vulnerability testing to secure the AI components.
• Compliance: Ensure data usage, algorithms, and system behaviors meet legal and compliance standards.
• ROI Tracking: Quantify benefits over time, like process efficiency gains, cost reductions from automation, and revenue increases.

With proactive planning across these areas, companies can maximize the transformational potential of AI-enabled ERP. Patience pays off – a thoughtful implementation sets the stage for long-term competitive advantage.

Need help selecting ERP?

Businesses face the challenge of selecting ERP systems that fit their needs among a sea of options. We are optimistic about the future of AI in ERP, but sometimes, human intelligence is preferred.

Our experts can assist you by providing a proven shortlist of ERP systems that align with your requirements. We analyze your needs, handpick the ideal solutions, and connect you with the top ERP vendors for customized price quotes, demos, and further steps.

What are some common use cases for AI in ERP systems?

Some of the most common applications of AI in ERP systems include predictive analytics, intelligent process automation, computer vision for quality control, natural language processing for documentation, and chatbots for user interaction. For example, predictive analytics uses machine learning algorithms to forecast demand, detect anomalies, predict failures, and enable preventative maintenance. Intelligent process automation can automate repetitive administrative tasks within the ERP system using technologies like robotic process automation.

How does machine learning benefit ERP software?

Machine learning allows ERP systems to continuously analyze data, identify patterns and insights, and improve decision-making without explicit programming. Machine learning algorithms can find complex relationships and interactions within ERP data that are invisible to humans or traditional programming. This enables the ERP system to get smarter and optimize processes without human intervention.

What ERP business processes can AI automate?

Some key ERP processes that AI can automate include demand forecasting, production scheduling, inventory optimization, quality control, maintenance scheduling, and repetitive administrative tasks. AI excels at automating routine, rules-based processes that rely on analyzing large volumes of data, such as using historical sales data to forecast future demand. AI can also take over administrative tasks within ERP, like employee record updating, invoice processing, and report generation.

Does my company need to hire data scientists to implement AI?

Some AI capabilities may require internal data science expertise to develop and validate machine learning models properly. However, many ERP software vendors now provide pre-built AI tools and platforms that allow you to leverage AI without needing to build it from scratch. With vendor-supplied AI tools, you will still need to configure the models and algorithms for your business needs and data. But you likely will not need to hire specialized data scientists in most cases.

What risks are associated with AI-enabled ERP systems?

Some potential risks with AI-enabled ERP include inaccurate predictions if models lack quality data, biased decisions if historical data is imbalanced, lack of transparency into model logic, over-reliance on AI without human oversight, and potential security vulnerabilities. Extensive validation, diverse data, and cybersecurity measures are essential to mitigate these risks.

How can AI transform supply chain management?

AI can transform supply chains by improving demand forecasting with more data sources, optimizing logistics variables like routes and shipments, increasing real-time visibility for proactive management, predicting potential disruptions before they occur, continuously identifying optimization opportunities, and enabling dynamic adjustments based on live data.

What is the benefit of computer vision in manufacturing ERP?

Computer vision AI applied to manufacturing ERP can automate visual inspection for defects, read serial numbers and barcodes, guide robots, track work progress, monitor production line efficiency, and improve quality control, resulting in less waste.