AI in ERP: The Next Wave of Intelligent ERP Systems

This merging of ERP and AI paves the way for a new generation of intelligent ERP solutions. These systems can analyze vast amounts of data, optimize processes, predict potential issues, and enhance decision-making.

By adopting AI-driven ERP software solutions, businesses can achieve greater efficiency, reduce costs, and enhance their agility, giving them a significant edge in the competitive market.

In this article, we will delve into the expanding role of AI within ERP systems, examining the added capabilities, spotlighting top AI-integrated systems, discussing implementation challenges, and forecasting future trends.

AI is set to be a pivotal strategy for driving digital transformation in the upcoming years. Read on to get up to speed on AI in ERP.

AI’s Rise in Enterprise

The use of AI has gained significant attention this year. It has gone from something that few people were talking about to the thing EVERYONE is talking about. This shift in focus can be attributed to the launch of OpenAI ChatGPT, which brought the power of AI to the masses. 

As of now, Microsoft has invested $13 billion in its partnership with OpenAI. Microsoft also announced Copilot, which leverages OpenAI’s technology to integrate advanced features into its products.

Two of the most prominent players in ERP and AI have recently expanded their partnership. SAP and NVIDIA are now working together to accelerate enterprise customers’ ability to harness the transformative power of data and generative AI across SAP’s cloud solutions and applications.

We’re also seeing other tech giants jockey for positioning. Google has followed up by announcing BARD and has been developing it rapidly. Amazon has announced a significant investment in Anthropic, another up-and-coming Open AI competitor with huge potential. Meta has announced it is working on an OpenAI competitor and plans to integrate AI features into its products. Apple is the only big player that hasn’t shown its hand so far.

The Takeaway from all this is that new technology trends often trickle down from the top, and you can expect it to arrive in all types of software, including ERP systems, one of the largest software market sectors globally.

Enterprise Software constitutes 41% of the global software market in terms of revenue. Enterprise resource planning (ERP) systems are pivotal in business operations across various organizational departments. With the infusion of artificial intelligence (AI) capabilities, the horizons of ERP are expanding.

As we explore this topic, we may introduce terms or concepts that may seem new and foreign.

Fear not; we aim to offer a high-level overview of how all these pieces come together, setting the stage for a deeper dive into specific applications and use cases.

Most people in the business world are still learning this new vocabulary related to AI.

For those who want to dive deep into the technical aspects of AI (not ERP specific), the State of AI Report 2023 is an excellent resource.

Understanding Enterprise Resource Planning

ERP encompasses comprehensive software suites designed to streamline and integrate business activities. These include manufacturing, inventory management, supply chain logistics, finance, human resources, and customer relations.

Industry stalwarts like SAP, Oracle, Microsoft Dynamics, and Infor are among the frontrunners in ERP solutions.

Artificial Intelligence Software

Artificial intelligence, often termed AI, denotes computer systems equipped to emulate tasks traditionally demanding human intellect. These tasks span from visual recognition and speech interpretation to intricate challenges like problem-solving, decision strategy formulation, and linguistic translation.

Sophisticated technologies such as machine learning, natural language processing, computer vision systems, deep learning, and predictive analytics underlie these AI functionalities.

AI Enhancements in ERP

When ERP systems embrace AI, they integrate advanced technologies such as machine learning algorithms, natural language processing capabilities, generative AI, and predictive analytics.

This confluence empowers ERP platforms to distill actionable insights from vast datasets, streamline and automate complex workflows, sharpen planning precision, bolster forecasting accuracy, introduce virtual assistants, and enhance performance analytics.

The Difference Between AI and Machine Learning

Artificial Intelligence (AI) and Machine Learning (ML) are sometimes used interchangeably, especially in marketing. However, they’re distinct.

AI is the broad realm of creating machines that can mimic human intelligence, while ML is a subset of AI, focusing on algorithms that let computers learn from data. So, while all ML is AI, not all AI is ML.

It’s important to discern these nuances despite the overlapping usage by some.

The State of ERP with AI in 2024

As we look around moving into 2024, we see certain patterns emerging with AI in ERP. Several of the systems featured in our review of this year’s top ERP systems now feature some level of AI enhancement.

Here’s what’s catching our eye and how companies are adapting.

More Businesses are Using AI Assistants and Bots

From our vantage point, we’ve noticed that vendors are increasingly integrating AI assistants and bots into their ERP software. This isn’t just a fleeting trend – it seems to be a shift towards more automated and efficient workflows.

Cloud Systems Make AI More Accessible

We’ve seen that Cloud ERP systems are not just about data management anymore. They’re paving the way for broader access to AI capabilities. By harnessing the power of the cloud, businesses of all sizes can tap into advanced AI tools without needing hefty investments.

A Need for More AI Experts

One challenge we’ve noticed is that there aren’t enough people trained in AI. As more businesses want AI, the hunt for experts is heating up. The skills businesses need keep changing, so there’s always something new to learn.

Not All ERP Vendors Are Up to Speed

While many ERP vendors are racing ahead with new AI features, some are lagging. They’re trying to add the latest tools to stay competitive and meet their customers’ demands.

Some ERP vendors will probably resort to strategic acquisitions to accelerate the process of integrating AI features into their ERP solution. This is exemplified by IFS’s acquisition of Falkonry, a company that develops an AI-based time-series data analytics tool.

AI Adoption in Manufacturing ERP

Manufacturers are now reaping the benefits of integrating AI technology into their ERP and manufacturing software. AI-powered features such as real-time monitoring and predictive maintenance have been increasing. With AI-enabled ERP systems, computer vision can be utilized for automated quality control and inspection. Intelligent order promising based on constraints and production schedules can also be implemented.

A new AI-driven system from the University of Virginia shows the benefits of AI in practice. Using multiple AI agents working together, the system can make real-time adjustments to keep production running smoothly, even during disruptions like machine breakdowns. This approach aims to improve speed and quality and reduce waste on the factory floor. Read more about it here.

These intelligent manufacturing capabilities and feature sets will only increase, becoming indispensable for manufacturing ERP systems in the next five years.

Top ERP Systems with AI Capabilities

Oracle

Oracle, a prominent ERP solutions provider, harnesses artificial intelligence and machine learning technologies to significantly augment operational efficiency and user engagement across various sectors, including finance and supply chain. Here’s a breakdown of the AI-driven features and functionalities within Oracle’s ERP ecosystem:

• Oracle AI Apps for ERP: Oracle AI Apps for ERP are cloud-based applications that help businesses optimize their operations by automating transactional processes, providing smart insights, and recommending actions. Some apps include Supplier Recommendations, Intelligent Payment Discounts, Automated Expense Audits, Procure-to-Pay, and Order-to-Cash. Oracle AI Apps for ERP aim to help businesses work smarter, faster, and more efficiently.
• Oracle Cloud Infrastructure (OCI) AI Services: Oracle’s AI services can be applied to various industries like finance, HR, marketing, and manufacturing. These services include natural language processing, computer vision, speech recognition, conversational AI, anomaly detection, and predictive analytics.
• Oracle Generative AI: Oracle offers various generative AI services, such as large language models, natural language processing, computer vision, speech recognition, and conversational AI. These services are designed to be easy to use, scalable, secure, and integrated with Oracle’s cloud applications and platforms.
• Machine Learning Services: Oracle’s machine learning services enable data scientists to build, train, deploy, and manage custom learning models using open-source frameworks or in-database machine learning technologies. These services are easy to use, scalable, secure, and integrated with Oracle’s cloud applications and platforms.

With a suite of AI-integrated features, Oracle offers businesses the tools to navigate modern industry challenges, boost innovation, and maintain a competitive edge in a dynamic market environment.

Acumatica

The AI features in Acumatica software streamline business processes through automation, like zero-touch automation for invoicing and interactive assistance, aiding in problem-solving and improving efficiency. Some specific features include:

• AP document recognition: Automatically creates AP documents from vendor bills using AI/ML, reducing manual data entry and errors.
• Natural language search: Allows users to search for data and information using natural language queries, simplifying data access and analysis.
• Helpdesk self-support: Provides interactive assistance and self-service options for users to resolve issues and find answers using AI/ML.
• Warehouse shipping and receiving: Automates and optimizes warehouse processes such as picking, packing, and shipping using AI/ML, improving efficiency and accuracy.
• Guided reporting and analytics: Generates reports and dashboards with AI/ML-driven insights and recommendations, enabling data-driven decision-making.

These features enhance operational efficiency and free employees from mundane tasks, fostering a more enjoyable work environment and aiding in talent attraction and retention.

Microsoft

Microsoft is at the forefront of integrating AI into its ERP offerings with Dynamics 365. This platform leverages AI to enhance business processes across various functions. Here’s an overview of AI features in Microsoft Dynamics 365:

• Dynamics 365 AI for Sales: This tool uses AI to provide actionable insights for sales teams, helping to prioritize leads and opportunities with the highest likelihood of conversion.
• AI Summarization: AI summarization in Microsoft Dynamics 365 synthesizes complex data from multiple sources across Supply Chain Management, Finance, Commerce, and Human Resources into clear, actionable insights, streamlining operations and enabling faster decision-making.
• Customer Insights: An AI-powered feature that aggregates data from various sources to create a 360-degree view of customers, enabling personalized engagement and proactive service.
• Supply Chain Management: AI functionalities in Dynamics 365 optimize supply chains by predicting disruptions, automating inventory management, and offering intelligent order fulfillment suggestions.
• Fraud Protection: Dynamics 365 uses AI to detect and prevent fraudulent activities in real-time, safeguarding financial transactions and customer data.
• Virtual Agents: AI-driven virtual agents can engage with customers and employees, providing instant responses and support to improve satisfaction and productivity.

By incorporating AI into Dynamics 365, Microsoft empowers businesses to automate complex processes, gain deep insights, and remain agile.

Epicor

Epicor, an established ERP software provider, leverages artificial intelligence and machine learning to enhance operations across several industries, including manufacturing, distribution, retail, and the automotive aftermarket. The following list outlines the AI-driven features and functionalities that Epicor incorporates to meet the unique demands of these sectors and promote business growth:

• Epicor Data Analytics: Uses machine learning to provide users with actionable insights. The system analyzes data and identifies patterns and trends that users may not be able to see on their own. Based on these insights, the system can then provide users with recommendations and suggestions.
• Epicor Virtual Agent (EVA): A chatbot that uses task execution and recommendations, natural language processing (NLP), and proactive alerts to help users with tasks.
  • Task Execution and Recommendations: EVA can automate tasks and recommend actions to users based on their past behavior and the current situation.
  • Natural Language Processing (NLP): EVA can understand and respond to text or voice interactions. This makes it easy for users to interact with EVA and get the help they need.
  • Proactive Alerts: EVA can send timely alerts and execute targeted actions based on the data it can access. This can help users to avoid problems and improve their efficiency.
• Epicor Kinetic Design: An AI-driven framework for intuitive, responsive applications. This means that Epicor Kinetic applications are easy to use and can adapt to the needs of individual users.
• Machine Learning Component: Epicor’s machine learning component evolves to provide better user assistance. This means the system constantly learns and improves, providing users with the best possible experience.

Overall, Epicor Data Analytics and Epicor Virtual Agent are powerful tools that can help businesses improve their efficiency, productivity, and customer service.

IFS

IFS AI is a comprehensive suite of artificial intelligence capabilities integrated throughout all IFS solutions. By utilizing all available data and IFS capabilities, IFS AI provides an interactive user experience, proactive productivity, and supercharged insights. Some of the key features of IFS AI include:

• Co-pilot: Serves as a conversational AI assistant, enabling users to seamlessly perform tasks, access essential information, and receive valuable recommendations through natural language interactions.
• AI-powered Automation: Automates various workflows, business processes, and actions based on data-driven triggers and predefined rules, streamlining operations and minimizing manual intervention.
• AI-powered Optimization: Utilizes advanced algorithms and machine learning to optimize planning, scheduling, and resource allocation, enhancing operational efficiency and reducing costs.
• AI-powered Analytics: Offers predictive and prescriptive analytics, anomaly detection, and root cause analysis through data science and machine learning, delivering crucial insights for informed decision-making.
• AI-powered Simulation: Employs data modeling and machine learning to simulate different scenarios and outcomes, aiding businesses in anticipating challenges and evaluating strategies before real-world implementation.

IFS AI is built on a powerful, flexible and cloud platform that supports multiple deployment options, integration capabilities, and open APIs. IFS AI aims to help businesses work smarter, faster, and more efficiently.

Infor

Infor provides a comprehensive enterprise-grade AI platform to propel businesses toward achieving swift and tangible results from their data. Here’s a breakdown of AI features within Infor’s platform:

• Operational Intelligence: Generates automated process triggers based on specified events or conditions, leading to improved process efficiency and reduced manual interventions.
• Asset Intelligence: Utilizes predictive analytics to maximize the lifespan of assets by timely addressing health, maintenance, and parts needs, thus improving asset health and labor efficiency.
• Forecast Intelligence: Employs historical data and market conditions to predict future demand, enhancing forecast accuracy, reducing inventory costs, and potentially increasing revenue.
• Customer Sales Intelligence: Provides insights on customer preferences and behaviors to enhance sales strategies and customer satisfaction, thus potentially leading to revenue growth.
• Pricing Decision Intelligence: Analyzes market drivers and historical pricing data to support investment pricing decisions, aiding in market-centric pricing strategies.
• Human Capital Intelligence: Streamlines the management of human resources, aiming to improve labor efficiency, reduce costs, and enhance employee satisfaction and retention.
• Coleman AI: Features a library of AI algorithms, facilitates the building of machine learning models by business users, and ensures rapid deployment of AI capabilities from end to end.
• Augmented Intelligence Service: Offers business-focused solution design with industry expertise, aiming for a swift realization of value from AI adoption within 90 days.
• Coleman Digital Assistant: Boasts a conversational interface powered by Natural Language Processing (NLP), offering out-of-the-box skills, DIY skill-building tools, and seamless integration with Infor or third-party applications for workflow orchestration across systems.

These features show Infor’s commitment to leveraging AI to drive efficiency across various organizational facets.

SAP

SAP, known for its robust ERP solutions, has embraced artificial intelligence (AI) through SAP Business AI and Joule, the AI copilot. These advancements enhance operational efficiency, decision-making, and user interactions within the SAP ecosystem.

• Industry-Specific AI: Trains AI on industry and company-specific data, ensuring relevance and reliability in AI-driven solutions.
• Ethical AI Deployment: Adheres to leading ethics and data privacy standards, ensuring responsible AI utilization across the organization.
• Integrated AI: Incorporates AI into core business processes, connecting departments like finance, supply chain, procurement, sales, marketing, human resources, and IT to foster a cohesive AI-driven business environment.
• Agile Decision-Making: Facilitates rapid decision-making by providing valuable insights derived from data analysis.
• Task Automation: Automates repetitive tasks, making processes more efficient and allowing employees to focus on strategic initiatives.

Joule — The AI Copilot

Joule, introduced by SAP as a generative AI assistant, is designed to improve user interaction with SAP business systems:

• Personalized Assistance: Provides a personalized user experience by understanding unique roles and facilitating streamlined task management across SAP applications.
• On-Demand Insights: Offers quick answers and smart insights on-demand, aiding in prompt decision-making.
• Enhanced Productivity: Delivers tailored content to expedite work processes, like generating job descriptions and offering coding assistance.
• Data Privacy and Control: Ensures user control over decision-making and data privacy while utilizing generative AI in a secure environment.

SAP is working directly with NVIDIA to power its solutions with best-in-class AI features. The integration of AI in SAP’s enterprise solutions, particularly through SAP Business AI and Joule, illustrates an all-in approach from one of the top players in the industry. It presents a practical blueprint for leveraging AI in the enterprise sector, setting a solid groundwork for future innovations.

ERP AI Features Roundup

Upon reviewing the various ERP systems and AI features highlighted above, you might recognize some prevailing trends regarding the types of features that ERP vendors are incorporating into their offerings.

These additions respond to the growing demand for intelligent business process automation and insight generation.

Let’s recap some of the most in-demand and common features:

• Predictive Analytics: Analyzes data to discern patterns and forecasts future outcomes, leveraging business intelligence to make data-driven decisions proactively.
• Natural Language Processing: Facilitates interaction with ERP software using natural language via chatbots and virtual assistants, enhancing user accessibility and experience.
• Computer Vision: Streamlines data entry and document processing by extracting text, images, and data from documents, reducing manual intervention.
• Machine Learning: Harnesses algorithms that learn from data to tailor workflows, refine processes, and enhance decision-making, enabling a more intelligent, adaptive operational environment.
• Planning and Scheduling Optimization: Using sophisticated algorithms to optimize planning and scheduling processes, improving efficiency and resource allocation.
• Intelligent Process Automation: Integrates and mimics human actions in digital processes to automate workflows, driving efficiency and consistency across operations.
• Anomaly Detection: Identifies abnormal patterns in data that may indicate potential problems or issues needing intervention, ensuring timely resolution and minimizing risks.
• Sentiment Analysis: Evaluates text to comprehend the attitudes, opinions, and emotions encapsulated within, offering valuable customer insights for better engagement strategies.
• Recommendation Engines: Proposes actions or next steps in workflows based on historical data and patterns, supporting informed decision-making and process continuity.
• Chatbots/Digital Assistants: Provides conversational interfaces for interacting with ERP systems to retrieve information or perform tasks, enhancing user engagement and productivity.
• Predictive Maintenance: Forecasts when maintenance will be required on machinery based on IoT sensor data, enabling proactive maintenance scheduling to prevent costly downtime.
• Demand Forecasting: Estimates future demand utilizing historical data, regression models, and deep learning algorithms, aiding inventory and production planning.
• Cash Flow Forecasting: Predicts future cash flow needs by analyzing historical data and sales forecasts, ensuring financial readiness and sustainability.
• Reporting and Financial Statements: Automates the generation of financial reports and statements using historical data, streamlining financial management and compliance.

The AI capabilities we have explored are much more than just technological enhancements; they are changing how we use our ERP software solutions. And this is just the start. Presently, it is all about keeping up with the latest advancements and features as they are being released at a fast pace.

Benefits of AI-Enabled ERP

Integrating Artificial Intelligence (AI) with ERP systems isn’t about adding flashy features. It’s about delivering real, tangible benefits that impact the bottom line.

Here’s how the AI features translate into significant advantages in ERP systems:

• Automated Processes and Workflows: AI can automate repetitive tasks, making ERP systems more efficient.
• Better Insights from Data Analytics: AI-powered analytics provide valuable insights from ERP data, aiding better decision-making.
• Increased Productivity and Efficiency: AI enhances employee productivity and efficiency by automating tasks.
• Improved Reporting and Forecasting: Predictive analytics in AI-enabled ERP improves reporting and forecasting, making them more accurate.
• Enhanced Customer and Employee Experience: Tools like AI-powered chatbots and virtual agents improve interactions for customers and employees.
• Improved Decision-Making: AI facilitates data-driven decision-making by unveiling insights from ERP data.
• Automation and Reduced Human Error: AI-driven business process automation reduces the chance of human errors in ERP processes.
• Optimized Manufacturing Operations: AI improves inventory management, predictive maintenance, anomaly detection, and quality control. This increases efficiency, uptime, and throughput.

Embracing AI within our Enterprise Resource Planning systems goes beyond technological enhancement; it’s about creating a more intuitive, efficient, and human-centric operational environment. The benefits outlined encapsulate a shift towards smarter business operations where technology serves us and improves our daily work experience.

Future of AI in ERP

The technology industry is rapidly evolving with the help of Artificial Intelligence (AI) advancements from major players such as OpenAI, Anthropic, Google, and Microsoft, as well as a growing number of startups. This dynamic ecosystem significantly overlaps AI and Enterprise Resource Planning (ERP).

What’s Next?

Integrating AI and ERP is a substantial development set to redefine the ERP market. Here are some informed predictions we have:

1. Acquisition Wave: There could be a series of mergers and acquisitions as larger vendors aim to acquire innovative startups to incorporate their novel AI solutions into broader ERP offerings.
2. Democratization of AI: The emergence of user-friendly AI tools will enable a broader range of businesses to utilize AI within their ERP systems without requiring a deep understanding of the technology.
3. Ethics and Regulations: As AI becomes integral in ERP, new ethics and regulations will surface to ensure data integrity and promote a culture of transparency and accountability.
4. Industry-Specific AI Solutions: The demand for tailored AI solutions will increase, leading to industry-centric AI-ERP solutions that address unique operational challenges.

Upcoming AI Trends:

Several trends in AI innovation are on the horizon to reshape the ERP landscape:

1. Explainable AI (XAI): As AI models become more complex, the need for understanding the logic behind AI decisions within ERP systems will grow, driving the adoption of Explainable AI.
2. Hyperautomation: The push for higher efficiency will lead to hyperautomation, integrating AI deeply into ERP software to automate many business processes.
3. Augmented Intelligence: Augmenting human intelligence with AI will create a more collaborative AI-human interaction within ERP environments.
4. Cross-Platform AI Capabilities: AI capabilities that can function across various ERP platforms and integrations will help promote more unified, cross-functional business operations.

The interaction between AI and ERP opens up new avenues for innovation and opportunity.

Given the rapid pace of innovation over the last year, it’s difficult to predict the next five years. We can only be sure that things will be moving rapidly, and it may be hard to keep up for some.

For ERP vendors in the evolving landscape of AI-driven ERP, staying relevant isn’t just about keeping pace, but about setting the pace.

For businesses, As AI integrates deeper into ERP, proactive adaptation becomes a business’s competitive edge. Adaptable businesses will navigate the challenges and leverage the numerous opportunities in the AI-enhanced ERP domain.

We will continue to update this article as systems and features evolve. For now, please check out our detailed system comparison and guide for ERP systems that feature artificial intelligence and machine learning.

Frequently Asked Questions about ERP with AI

What is the benefit of an AI-enabled ERP system?

AI-powered ERP systems automate tasks, provide insights, and adapt to optimize processes like supply chain and production. This improves forecast accuracy and decision-making, freeing employees to focus on higher-value work. AI makes ERP systems effective digital assistants that drive the intelligent enterprise.

What benefits does AI provide for manufacturing industry operations?

AI can use techniques such as computer vision, IoT sensors, Machine Learning algorithms, and simulation to enhance quality control, predictive maintenance, production scheduling, inventory management, and logistics planning, ultimately improving overall efficiency.

Is AI used in HR management features of ERP solutions?

Indeed, AI can be helpful in various HR processes such as talent acquisition, onboarding, training, payroll, retention analytics, and more. One example of how AI can assist is through chatbots that aid recruitment and natural language processing (NLP) that analyzes employee sentiment.

What is the future outlook for the adoption of AI in enterprise software?

Most analysts predict rapid growth in AI adoption as the technology improves and becomes more ubiquitous. AI may become a ​“must-have” capability for ERP and other enterprise software in the next five years.

Can AI fully automate finance processes like accounting and auditing?

While AI can automate many finance processes, most experts believe human oversight is still required in accounting and auditing to ensure accuracy and compliance. However, AI assists with invoice processing, anomaly detection, and financial reporting.

How does AI improve supply chain management?

With the help of AI, businesses can improve demand forecasting accuracy, optimize inventory levels, automate purchase orders, efficiently route shipments using Machine Learning, and use real-time data to make dynamic adjustments to their supply chains.