AI technologies are proving their ability to transform industries as diverse as hospitality, insurance, finance, retail and many others. For many enterprises, these changes are manifesting themselves as improvements to internal operations, especially in the so-called back office.
Companies have a wide range of business processes that can be improved and made more efficient with the use of AI for business operations.
AI simplifies and accelerates procure-to-pay and order-to-cash processes
Despite the evolution of e-commerce, corporate procurement of supplies and customer billing are still mostly paper-based. Companies ask for paper or PDF invoices to pay expenses and issue customer invoices in similar forms despite over two decades of the much-promised paperless office.
Supporting documents, as well, such as receipts, contracts, statements of work and other documentation, are paper-based. Despite the use of CRM and ERP systems, these paper-based processes incur wasted time, are error-prone, and introduce significant labor and time inefficiency.
Because it seems that the truly paperless office is not coming anytime soon, companies are looking to AI-based systems to speed up payment and procurement processes. AI is simplifying and accelerating invoice processing.
AI systems are using natural language processing to recognize important parts of submitted documents, such as the invoice or PO number; the amount of the invoice; who is paying the invoice; and the date of the invoice to see if it's on time or overdue. The AI invoice system can then code the invoice and send it along to the appropriate parties.
As machine learning and AI technologies become integrated into the procurement and purchasing processes, companies can see time efficiencies and cost savings. As these systems get smarter, they can begin to learn what normal purchases look like, flag purchases that seem out of the ordinary and either directly send purchases to the right parties for approval or wave that approval step altogether if the purchase matches normal behavior as learned by the AI system from prior transaction and approval processes.
Reducing the labor associated with compliance, audit and collections
Companies still struggle with paying invoices on time and handling large, complicated, multistep, multi-payment, multi-invoice processes efficiently. Cognitive technologies are making it easier for these companies to get paid what they are owed by tracking where projects are in the payment cycle and keeping track of timely and delinquent payments.
AI for business operations is helping companies identify the best paying customers and reward them with more favorable pricing or terms. On the flip side, AI systems can also keep track of trouble with problematic customers and identify the optimal time to reach out to those customers, resulting in a more constructive conversation with that party and increasing the chances of prompt payment.
Furthermore, AI is helping to reduce payment-related issues by auditing the receipts and expense reports of employees. By using AI-enabled systems that utilize computer vision and natural language processing capabilities, organizations now have the ability to audit every expense report. The system can check travel dates and expense amounts and make sure receipts are from approved vendors. Having the ability to review every expense can add up to significant savings for the organization by catching intentional or unintentional expense violations of company rules.
In fact, AI is already helping companies deal with the multitude of compliance and regulatory challenges. AI systems can provide automatic documentation of certain activities and record paper and voice-based transactions when necessary. AI systems can listen in on phone conversations to ensure compliance in the pharmaceutical and financial industries and can record paper transactions, storing them for compliance in heavily regulated industries, such as healthcare or banking.
Automating human-intensive and mundane tasks
For other industries, back-office operations require many workers to handle important but mundane activities. In the construction, manufacturing, retail and real estate industries, companies are using AI to manage employee and goods delivery scheduling, especially for businesses that have hourly and shift workers.
AI systems are already being used to manage personnel schedules. By teaching the system what a typical work week looks like, it will know to schedule certain people for particular days or shifts, not to schedule people for unapproved overtime, and to take into account scheduled vacation and sick days.
Other AI systems are being used to optimize delivery schedules for goods, warehouse operations, and IT support and administration. Wherever a human is required to approve a document, handle a workflow or otherwise manage a process, AI systems can add efficiency.
All of these use cases for AI help to solve pain points for companies. Back-office operations present a conundrum for businesses: they don't offer any real competitive advantage, but if they're not completed correctly, they can impose significant risk, cost and liability for organizations. As such, AI for business operations offers value to these businesses by addressing back-office inefficiency that previously required large amounts of high-importance but low-value human activity.