Artificial Intelligence (AI) is expected to create a wave of productivity increases. With Enterprise Resource Planning (ERP) software at the core of business information systems, publishers are racing to incorporate new “generative” AI technologies into their systems. Incorporating AI into ERP will do more than automate manual processes by changing the way we record transactions, respond to customers, and make business decisions.
Next Generation AI
“Traditional” AI has been embedded in ERP for decades. Using historical data and statistical analysis, computers have made order recommendations, optimized inventory and classified data. These specific tasks have used defined algorithms to look at structured data to calculate a result. Generative AI is different because it uses patterns in unstructured data to learn and develop its own algorithms. Although based upon its own form of programming, this learning changes the nature of outputs to be more creative and expansive than traditional AI. In other words, the new programs allow the computer output to more closely resemble human output such as music, images or computer programs,
Current versions of generative AI struggle with what are called, hallucinations. Wikipedia calls hallucinations, “AI confident responses by an AI that do not seem to be justified by its training data.” A recent article on CMS Wire talks about how Alphabet lost over $100 billion in value due to AI misinformation, but more importantly, how the AI community is investing to overcome the problem. Improper conclusions and fabrications created by AI lead to mistrust in the technology. AI must overcome hallucinations before it can generate its anticipated wave of productivity.
Generative AI’s Impact in ERP
AI’s impact on ERP is anticipated to be broad and deep. The high-level goals of AI in ERP include:
- AI is already starting to automate data capture and enhancement. For example, updating customer and vendor master file data with contacts, correcting addresses, and other information updates.
- Elevate human work by automating data capture using machine readable documents. For example, accounts payable automation including intelligent data capture, matching and payment. Although these functions exist today, AI can increase accuracy and depth of the process.
- Automating interactions with customers and suppliers such as customer service information requests, investor relations. When AI can understand natural language and the intent of a request, the ERP system will be able to compose an e-mail with order status and attach related packing lists or other documents.
The role of computers in business has always been to automate repeatable tasks. As AI can perform more complex tasks, the level of work performed by staff will be more creative and complex.
Adoption of AI in Business
The major publishers all have teams working on AI in their business management software. Third party developers are also working on new ways to incorporate AI into their applications. Assuming AI follows similar patterns of other ERP breakthroughs, the third-party products will be first to market in the leading modern products. Cloud Native systems like Sage Intacct and NetSuite or modern platforms with open data architectures like Acumatica and SAP Business One will garner greater investment than legacy and niche products. Newer entrants like Oodo and NextWorld will also have leading edge AI capabilities.
The introduction of new technology comes with great expectations. Typically, those expectations take years to come. Futurist Jack Shaw’s provides insights into the delay in adoption and steps for executives in a recent ASUG News and Views article. Shaw believes AI will promote continuous “dynamic digital transformation” within organizations. Digital transformation will move from project based to continuous improvement using new computing techniques throughout the organization.
A recent Sage blog, Generative AI in 7 Easy Steps, begins with a focus on the customer. Practical advice includes:
- Augment the creativity of your people
- Understand the technical feasibility of Generative AI
- Use Incremental deployment.
Applications for Generative AI
We believe the big push for AI driven productivity gains will come from large enterprises. The largest opportunities will come from the biggest companies. This gives an advantage to SAP Business One and NetSuite to leverage the investments from their enterprise products in the mid-market.
- SAP has rolled out a digital currency tool that bypasses banks to transfer crypto currency into traditional financial institutions. This tool is already available for SAP Business One customers via the SAP Business Transformation Platform (BTP). BTP works with ChatGPT and IBM Watson and will likely also work with Google Bard.
- NetSuite’s Upsell Engine make recommendations based on a customer’s activity on the site. The recommendations improve as the customer continues to use the site.
- Sage Intacct already enriches information using the Sage Digital Network for address verification, tax locations and identification and validation of banking and credit information.
We expect every major software release will include new AI features. Over time, AI’s impact on ERP will be integrated into business processes to improve the way people perform work. For example, initial AI tools like Intelligent Materials Requirements Planning (MRP) use regression analysis to make better recommendations. Generative AI can use a broader range of data to find patterns to further improve calculations.
Capitalizing on AI’s Impact on ERP
Economists believe that AI will result in productivity gains similar to the industrial revolution. Similar to the industrial revolution, the internet changed business. The internet has changed the way we communicate. E-mail has replaced “Snail mail” and faxes. Customer self-service and e-commerce created whole new forms of competition.
Generative AI will make dramatic shifts in processes driven by the power of cloud computing. Although it appears early in the game, the rate of advancement and adoption is unparalleled. Shaw predicts that we will have “billions of times more computing power than we’d ever previously imagined” within 10 years. Computing power combined with tons of internet data will create currently unthinkable opportunities:
- Micro segment current customers to find new customers
- Automate “non value-added” setup of master data. For example, supplier inventory is always up to date and available within your system.
- Benchmark processes against competitors or processes from across industries.
To capitalize, companies need to have a continuous Digital Transformation mindset. It begins with a strategy with short and long term ROI objectives. A future vision of your organization including a digital technology platform which transforms your daily operations for efficiency. Begin your journey with a free Digital Transformation Readiness consult with one of our executives.