When it comes to SAP applications, AI benefits are plentiful. From extracting information to building self-driven customer service, AI has a lot to offer. Learn more in our Trends blog!
It goes beyond computer science – no matter the industry, automating business processes has become critical to business strategy and success. Forrester reports that the total benefits gained from business automation total around $32 million through increased employee efficiency, employee productivity, process efficiency, and overall reduction of processing times. Further, Forrester’s 2019 Business Technographics survey shows that 62 percent of global business and technology leaders are already implementing or expanding their implementation of machine learning today, with 24 percent planning to implement it within the next 12 months. Indeed, the application of artificial intelligence (AI) is predicted to profoundly impact all aspects of business, promising companies more time for value-adding tasks and less human error due to the elimination of tedious, mundane tasks.
When it comes to SAP, applying AI applications can rectify some of the issues people have with the system, such as SAP ERP. How so? Read on for the answer!
It’s All About Data
According to Silicon Angle, working with SAP software can lead to confusion. Like many large companies, SAP has made a number of acquisitions over the years, which has resulted in a complex and disorienting product line. For example, when it comes to its HANA products, SAP sells SAP HANA, C4/HANA, S4/HANA and HANA Cloud Platform. Further, working with SAP systems requires a lot of information.
To mitigate this confusion, companies need to intelligently connect people, things, and businesses. How can they accomplish this goal? The answer lies in data.
SAP has always been a data-centric company and its specific business is known for transactional data mined from customers, products, points of sale, and structured data. However, business intelligence goes beyond reporting said data. To become intelligent enterprises, businesses need to make sense of a growing volume of data, create a step change in productivity, and innovate quickly. In other words, they need to accelerate value creation – and AI can help them get there.
Ways Companies Can Benefit from AI
SAP points out that artificial intelligence simplifies workflows, leads to more exact forecasts, and creates new business models based on data science. Thanks to better data, it accelerates decisions and increase the company’s ability to adjust to market changes thanks to real-time information and predictions that can be without human intervention. As a result, AI technology makes companies profoundly more efficient, increasing their competitiveness in the process, with 94 percent of companies believing that machine learning opens up significant competitive advantages.
New business assets like intelligent chatbots that are used for customer service rely on algorithms, which learn through direct contact with customers and react more precisely to their needs. Applications for AI in SAP can include:
- A digital chat assistant enabled by deep learning that asks questions and gives answers to help users accomplish their goals
- An application that automatically categorizes service tickets, prioritizes tasks, and suggests answers to standard questions.
- Predicting customer behavior.
- Identifying the most suitable applicants from a variety of job applications.
- Helping companies measure the influence of their brand and the effects of sponsorship and advertising investments.
Six Ways AI Empowers Customers across Industries
It is undeniable that AI systems have a multitude of benefits to offer users. Prior to utilizing AI, many companies were weighed down by time-consuming and tedious short-term tasks, which distracted them from focusing on value-adding, strategic tasks and innovation. By utilizing AI, companies are able to improve efficiency, empower employees, and improve both data quality and analytics.
According to SAP, the following applications can enrich customer relationships and provide immediate business value:
1) Document Classification
Due to extensive paper and document-based communication, many modern companies still struggle with low process efficiency across their organization. Tools that have AI support can help companies that manage large numbers of business documents to automatically and easily classify documents based on customer-specific classification schemas.
2) Document Information Extraction
While many communication-heavy businesses struggle with Document Classification, they also find processing the information contained in said documents to also be difficult. AI services can process various documents that have content in headers and tables and extract information. AI also makes the method more efficient with less errors and difficulties.
3) Service Ticket Intelligence
This form of AI service can help businesses build self-driven customer service by supporting the dedicated customer service team in handling large volumes of service interactions. By accessing historical service interaction data that already exists in the CRM application, incoming customer service tickets are automatically, correctly categorized and routed to the right agent. The agent is then given recommended solutions that improve operational efficiency.
4) Data Attribute Recommendation
Business units and organizations struggling with the consistency and accuracy of their master data can benefit from AI services that offer data attribute recommendation. Thanks to the usage of machine learning capabilities, data records can be easily matched and classified, which leads to more efficient and higher-quality master data management, speeding up the data creation or cleaning process.
5) Invoice Object Recommendation
Through the prediction of correct account assignments, this AI service supports the accounts payable department in their decision making. Through the usage of historical data, the solution enhances financial reporting by minimizing roadblocks that arise due to discrepancies in accounts/budgets. It also reduces repetitive and redundant tasks, including searching for G/L accounts and correcting wrongly assigned accounts.
6) Business Entity Recognition
This approach utilizes a powerful machine learning technology to detect and highlight any given type of named entity in unstructured text into pre-defined categories. This method helps to increase overall document processing productivity, increase efficiency, and reduce errors through the ability to detect named entities in text entities.
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