The power of AI integration and process automation in ERP.
The fourth industrial revolution has arrived. Known as Industry 4.0, this iteration of industry moves beyond digital solutions to include process automation and artificial intelligence (AI) tools capable of increasing speed, reducing errors and improving data accuracy.
While AI and automation are applicable across all industries and operations, one business area experiencing significant growth is enterprise resource planning (ERP). Tasked with collecting, assessing and applying data across organizational departments, many ERP solutions are reaching the upper edge of their capabilities as data volumes and velocity rapidly increase.
Effective integration of AI and process automation into ERP tools can help companies unlock new opportunities for business growth. Here's how.
The evolution of ERP
What began as digital is now dynamic.
First-generation ERP systems helped companies automate key policies but also came with inherent limitations. Initial deployments were entirely on premises, meaning performance was naturally bound by the upper limit of on-site storage and computer power.
Additionally, these systems were naturally siloed. Disparate databases made it difficult for managers and C-suites to get a complete picture across finance, payroll, HR, human capital and CRM operations.
Finally, these first-stage systems were both proprietary and prepackaged, meaning companies could spend significant amounts of money on tools that did too much — or too little.
Cloud computing created the opportunity for ERP advancement. By leveraging the cloud, companies were able to combine multiple data sources and drive better outcomes. For example, by using locally stored financial data and combining it with cloud-based supplier information, it became possible to assess and adjust supplier relationships on demand.
Additionally, cloud-native tools naturally lend themselves to specialization, in turn making it possible for companies to find best-fit solutions rather than spending on one-size-fits-all frameworks. And no discussion of the cloud is complete without mentioning scalability. While on-site solutions are limited by physical storage and digital computing capacity, cloud tools are infinitely scalable and adjustable to meet business demands.
The result? Dynamic solutions that provide the foundation for real-time strategy.
Accurate, accessible and automated: the role of AI in ERP
While the cloud sets the stage for ERP advancement, it also creates an operational paradox: complexity.
Put simply, more data from more sources makes it more difficult for companies to see what they have, why it matters and how they can effectively use it. AI helps companies improve visibility without sacrificing security.
AI tools are designed to perform a specific task. To accomplish this goal, they use what are known as machine learning (ML) algorithms. Using a combination of coded rule sets and large data sources, these algorithms "learn" how to identify correlations between pieces of data.
For example, ML solutions could be taught to recognize common behaviors in fraudulent transactions, such as users without complete banking profile information and the movement of large sums over short periods of time. Multiple algorithms are then combined to create an AI solution. Building off the ML framework listed above, AI could be used to identify possible fraud, terminate suspicious user sessions and report this data to security teams.
In practice, AI enables companies to achieve three key goals: capture accurate data on demand; access this data anywhere, anytime; and automate the process of capturing and correlating this data.
How AI-powered ERP can streamline financial operations
AI integration isn't limited to a specific industry. From manufacturing and retail to healthcare and law, any business can benefit from the adoption of AI-driven ERP.
However, finance occupies a unique position at the intersection of regulation and responsiveness. For example, while healthcare administrators must contend with rapidly evolving compliance regulations, their interaction with patients is mostly peripheral.
Retail companies, meanwhile, continually interact with customers but aren't subject to the same level of government oversight as healthcare operations.
In finance, both expectations apply. Firms must deliver top-tier customer service and experience while simultaneously safeguarding critical personal financial data, scanning for potential fraud, and reporting both actions and assets to government agencies.
As a result, combining AI with ERP systems offers substantive benefits for financial organizations, including:
Improved data handling
AI tools can pull data from multiple ERP data sources simultaneously. This makes it possible to ensure accuracy, eliminate redundant information and pinpoint emerging trends.
Increased financial process automation
With AI, effort-intensive and error-prone processes such as data collection and evaluation can be automated. This frees up staff to focus on line-of-business efforts.
Enhanced user experience
With ERP tools now used across all levels of financial organizations, user experience is critical for success. If staff avoid using ERP systems, full value isn't recognized. AI in finance can improve the end-user experience by providing on-demand access to the tools and data they need.
The future of ERP in financial services
According to recent data, 35% of companies are now using AI and 42% are exploring their options. And while more than half are seeing benefits including cost savings and improved automation, 65% are using more than 20 data sources to inform AI operations, creating the potential for increased complexity and reduced visibility.
So, what does this mean for financial services trends? Firms need to work smarter, not harder. By applying AI broadly across ERP operations using purpose-built, cloud-based tools, companies can zero in on the data they need when they need it, while keeping staff focused on driving business growth.
The democratization of AI, such as the evolution of generative tools like ChatGPT, also informs the future of ERP in finance. Much like cloud computing before it, more accessible AI makes it possible for enterprises to build and deploy bespoke AI solutions that deliver targeted answers to relevant questions, allowing companies to take action.
Navigating intelligent opportunities
AI for ERP is moving into the mainstream. This means more opportunities for organizations and more challenges in making sure that AI tools are effectively implemented and applied.
Mazars can help companies strike a balance between ERP operations and AI-driven insight. From proof of concept and platform selection to full-scale implementation and maintenance, Mazars makes it possible to unlock the door to AI-driven business growth.
The information provided here is for general guidance only, and does not constitute the provision of tax advice, accounting services, investment advice, legal advice, or professional consulting of any kind. The information provided herein should not be used as a substitute for consultation with professional tax, accounting, legal or other competent advisers.