Generative AI ERP Systems: 10 Use Cases & Benefits ['25]

Enterprise resource planning (ERP) software helps businesses see the process across different departments so they can make smarter decisions faster. Generative AI, alongside technologies like RPA, has the potential to enhance ERP processes. Microsoft is already offering generative AI ERP solutions through its Dynamics 365 Copilot tool, with other companies expected to follow suit in the near future.¹

Explore what generative AI Enterprise Resource Planning (ERP) systems offer to businesses:

What are the challenges faced in ERP technologies?

Customization vs. standardization

ERP software often needs customization to cater to specific organizational needs. However, excessive customization can lead to issues with updates, upgrades, and support.

Data accuracy and quality

The efficiency of an ERP system is contingent upon the accuracy of data input. Inaccuracies can lead to flawed insights and decisions.

Scalability issues

As organizations grow, their ERP systems need to scale accordingly. Some ERP solutions might not handle rapid growth efficiently.

Training and user adoption

Employees need training to use the ERP system efficiently. The complexity of some ERP systems can result in a steep learning curve.

Data security and compliance

Ensuring the ERP system adheres to data protection regulations (like GDPR) and is protected from cyber threats is crucial.

What are the use cases of generative AI ERP systems?

Generative AI, particularly models and techniques that can generate new content or data based on patterns they’ve learned, has a lot of potential for enhancing ERP systems. Here are some potential use cases of generative AI within ERP systems:

1- Financial planning & automation

The financial use of Generative AI in ERP systems can cover the automation of entire procure to pay cycle and such as the accounts payable process. Check out for more on ERP and AP:

• Accounts Payable Automation in Dynamics 365
• NetSuite Accounts Payable (AP) Automation
• Blackbaud Accounts Payable (AP) Automation
• Sage Accounts Payable (AP) Automation

Another important element for ERP systems is financial planning. Advanced generative AI models are capable of generating potential financial models or projections based on varying business conditions or strategies, which can be a good contribution to enterprise financial planning. Also, it can be used for improving fraud detection capabilities.

For more on these, check our article on the use of generative AI in finance.

2- Data augmentation and enhancement

Generative AI tools are increasingly evolving in data analysis skills. For example, ChatGPT has a new Code Interpreter plugin for data analysis and visualization. In general, generative AI tools are advanced in analyzing vast amounts of data. Specifically, they can contribute to ERP data analysis and protection by:

• Synthetic data generation: Filling in gaps or creating synthetic datasets from actual business data and customer data for improved analytics, especially when actual data might be scarce or sensitive.
• Data cleaning: Predicting and correcting data entry errors based on patterns in the data.

3- Demand forecasting

Generative AI models can predict product or service demands by generating potential future scenarios based on historical data and market trends.

4- Predictive maintenance

Using generative models to anticipate when parts or equipment may fail by simulating various operational conditions can enable the prediction of potential problems that can occur in business processes beforehand.

5- Scenario planning & simulation

Generative AI models are competent for creating different scenarios given the correct prompt and context. By using its potential for scenario planning and simulation, businesses can create “what if” scenarios for business strategy planning so that they can anticipate potential challenges or opportunities.

6- Customization and personalization

• It can be used to generate customized user interfaces or experiences based on individual user behavior, roles, or preferences within the ERP system.
• Generative AI can also be used in marketing and sales operations for improving customer experience, such as personalizing content for specific target audiences.

7- Automated report generation

ERP also includes the preparation and planning of massive amounts of reports from different business operations. Creating detailed, coherent, and customized reports for different departments, stakeholders, or purposes without human intervention is an important contribution generative AI can bring into the ERP.

You should check our ChatGPT in audit and intelligent automation in audit articles for more on report generation automation.

8- Enhanced user assistance

Using natural language processing (NLP) abilities of the generative AI technology to produce contextually relevant help content, troubleshooting guides, or workflow suggestions for users is another important use case. By understanding natural language queries of users, AI chatbots and voice assistants are especially promising generative AI technologies for simplifying user interactions within ERP systems.

Also, generative AI technology has vast potentials for education and educational processes across different areas. It can also be used for educational purposes in teaching employees certain ERP systems.

9- Supply chain optimization

Generative AI helps supply chain management teams test ‘what if’ situations, so they can be ready for changes like delays, shortages, or demand spikes.

Check out generative AI in supply chain management to learn more about this and other supply chain-related use cases.

10- Product design and development

In manufacturing modules, generative AI could aid in generating new product designs based on specified criteria or customer feedback. 

Check our article on generative AI in manufacturing to learn more about this.

What are the benefits of integrating generative AI into ERP systems?

Organizations leveraging generative AI solutions with their SAP applications data are already seeing stronger business performance.(https://www.ibm.com/think/topics/ai-in-erp)

1. Enhanced data analytics: Generative AI, by producing synthetic datasets that augment existing data, enable better testing, modeling, and insights, especially when real data might be sparse or confidential.
2. Improved decision-making: By simulating various business scenarios, generative AI offers insights into potential outcomes, assisting leaders in making more informed and proactive decisions.
3. Improved operational efficiency through intelligent automation: Tasks like content generation, report creation, or predictive analysis can be automated with generative AI, reducing manual effort and the potential for human error.
4. Personalization: Generative AI can customize interfaces, recommendations, or content to individual users or departments, leading to a more tailored and efficient user experience in the business applications.
5. Better demand forecasting: Generative models, by accurately predicting product or service demands by generating potential future scenarios based on historical data and market trends, ensure optimized inventory management and resource allocation.

Future of generative AI in enterprise applications

SAP, working with NVIDIA to integrate generative AI into ERP systems,² predicts that ERP will become a smart assistant, offering timely insights, learning from users, and helping teams make faster, better decisions.³

More human interaction

ERP systems have traditionally required users to adapt to them. Employees will be able to talk to ERP systems in plain language, like asking a question or giving a command to a colleague. Whether it’s filtering a report or generating a summary, tasks will become simpler and more intuitive.

Personalized user experiences

Generative AI will allow ERP systems to tailor experiences based on the user’s role, behavior, and preferences.

Better forecasting for real-world problems

With the help of generative AI, ERP systems will be able to analyze vast datasets and detect patterns more effectively. Business analysts will have access to powerful tools that were once locked behind technical expertise.

Automation that learns from you

While automation is already helping reduce repetitive tasks, future ERP systems will go further. They’ll learn from how users work, adapting to corrections and making smarter suggestions over time.

A system you can trust

AI will also help ERP systems become more secure. Continuous monitoring will detect strange behavior, flag potential threats, and alert users. Vendors will need to build AI with ethics, privacy, and safety in mind, so users can rely on it without worry.

External Links

• 1. Introducing next-generation AI and Copilot capabilities for ERP - Microsoft Dynamics 365 Blog. Dynamics 365 Blog
• 2. AI ecosystems, cloud transformation, and sustainable AI lead our key learnings from SAP Sapphire 2024 - SAP Southeast Asia News Center.
• 3. 6 Unexpected Ways AI Is Changing the Future of ERP UX | SAP Design.