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Visibility Corporation’s Chief Solutions Architect. I assist manufacturers in upgrading to Visibility’s ERP system.
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Your enterprise resource planning (ERP) system is critical software that gives you visibility into your business operations as a manufacturer, and artificial intelligence (AI) is on the way. Artificial intelligence (AI) is evolving at a rapid rate around the world, and it will have an impact on many aspects of daily life, including your present or future ERP system. Here are several ways ERPs are implementing AI for financial statement auditing and forecasting, as well as some things to consider if you want to adopt an AI-powered ERP system.
AI is already being used to audit financial statements and contracts. You can put your financials via an AI-based auditing software application to see whether the AI can discover any abnormalities or unexpected transactions that auditors should look into. To assess risk, AI may be able to quickly examine all of the data collected by users and providers. Machine learning may be used to educate an AI auditing tool with the knowledge of top CPA firms. Machine learning can also be used to train these types of computers to distinguish between routine and odd commercial transactions.
In several areas, the use of AI to increase forecast accuracy has already begun. AI can forecast a financial profit and loss statement (P&L) statement using both internal and external data sources. Your current backlog, forecasted bookings, past financial performance, new product releases, new market opportunities, cyclical business trends, and other forecast drivers that are already known by your financial planning and analysis (FP&A) team for your specific business are examples of internal data drivers. Macroeconomic market movements, commodity pricing, supply chain implications from trade wars, and other factors offered by a service like Google are examples of external drivers. To assist your company’s forecasting activities, AI will look for trends and correlations in the data.
You can prepare for an AI audit as a user by ensuring that your system produces clean, consistent data with good organization and audit trails. For analysis, your data should be generated in a systematic, logical manner. Internal controls should be designed and followed, and your ERP system should support them. You can develop processes to ensure that your ERP system’s digital workflows capture the right approvals on quoted pricing to clients, engineering revisions, purchase orders, expense reports, work orders, journal entries, and other items.
ADDITIONAL INFORMATION FOR YOU
Many people state that they desire to run a data-driven company. It may take some time and effort to prepare your data for AI. Fortunately, exercises like business process optimization and business value chain mapping may help you enhance how your system distributes data right now. Determine your primary companies and product categories, as well as how data is acquired via system transactions. This allows you to see where your business flow has efficiency and where it has slowness or bottlenecks. You may decide to move extra staffing resources and/or implement a software solution to aid once you’ve identified the areas that need to be improved.
For your data to be useful/accepted, AI may need to index it. Make sure you have ERP data fields that can receive metadata information associated to a part or product, for example. When modern digital images are potentially tagged with the photo date, the time the photo was taken, the place where the photo was taken, the camera used to shoot the shot, and so on, this is an example of metadata. Your ERP system’s capability might be set up to receive information about who, what, where, and when so that your data can tell a story. The more data AI can analyze and correlate, the more useful it becomes.
AI is being embraced by an increasing number of businesses, and this trend is projected to continue. AI auditing and forecasting are newer topics that I anticipate will gain traction as more businesses adopt this technology.
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