Artificial Intelligence: Moving from Theoretical to Practical for Business
By
Mike Bruening
Somewhere between the over-hyped buzz that positions Artificial Intelligence as a magical panacea and the daily predictions that AI will be the demise of humanity, lies the reality that AI is a transformational technology with the capabilites to address current business procesess. The Science, Technology, and Medical fields are all rapidly embracing Artifical Intelligence. However, for AI to move beyond Chatbots and Virtual Assistants and gain broad business usage, AI must cost-effectively assist in growing sales revenue or reducing expenditures. The initial high impact areas of opportunity for AI in business may not be the exciting magazine cover headlines that drive both the positive and negative conversations around AI. Early adoption of Artificial Intelligence in business may likely take place in the blocking and tackling of Accounting, deep within the lines of the balance sheet.
AI can transform processes that many might think are mundane business activities, but such tasks remain mission critical to turning received orders to hard cash. For years, Chief Financial Officers have authorized signifcant technology expenditures in enterprise software with lukewarm corporate results. Now, these enterprise solutions and the data they generate can feed Artificial Intelligence engines to create systemic changes to business ledgers. Of the emerging fields within AI, Computational Linguistics may lead the adoption of Artificial Intelligence in business.
Computational Linguistics allows machines to interpret text much like Siri translates spoken words into a format that can be used by computers. With 90 percent of available data being unstructured, Computational Linguistics combined with AI-driven engines allow business leaders to reassess the data and business practices that could not previously be understood or automated by machines. AI can fundamentally change how a company operates with the ability to harness large stockpiles of articles and records while removing burdensome manual tasks tied to critical business processes.
AI engines can roam across invoices, emails from customers, contracts, news articles and other unstructured data to speed up key accounting practices in Accounts Receivable, Collections, Deductions, and Reconciliations. The days are numbered for customers who chronically short-pay or tread along the gray areas of their suppliers write-off policies hoping their practices fall under the radar. AI’s ability to identify the validity of short payments or chargebacks in an efficient and fast method will force these customers to reduce and eliminate such practices.
In the front office operations, AI can assist in the administration of Contract Management. Across most industries, Salespeople and Account Executives must enter lengthy promotional contracts into customer portals and templates. Accurate contract entry is critical to proper pricing, billing, and invoicing. The combination of multiple accounts, products, and promotional deals all occurring across different time frames can create a mountain of administrative tasks for people who are charged with generating incremental sales. Computational Linguistics enables the automation of contract entry, workflow approval and store contracts in a centralized repository. AI can complete these tasks faster and more accurately than manual inputs. Artificial Intelligence can also extract, interpret, and access these contracts in cases of disputes and discrepancies.
AI can also be used to interpret vast amounts of unstructured data in the domain of competitive intelligence. Moving beyond simple website scraping services, Computational Linguistics can examine competitive notices of land purchases, plant acquisitions, advertised hiring positions and employment announcements. By incorporating these new data sources with existing buzz metrics and reports from analysts, AI can provide new insights on where a competitor may be strategically focused.
The engine-driven architecture of AI requires less programming code, so the ability to test and implement Computational Linguistics projects can occur at astonishing speeds. These low code installs allow businesses to test out concepts, modify, and retest all within weeks. Successful proof of concepts can be fully implemented in months. Proving the power of AI on issues in rapid succession provides learnings on how to incorporate AI into other business areas. Once business leaders gain experience implementing applications of Computational Linguistics, the hesitancy of deploying new AI solutions will disappear, and AI will continue to evolve.
When accessing where to implement Computational Linguistics in business operations, here are some questions to ask:
1. Where can AI be deployed to free up sales generating employees from burdensome administrative tasks?
2. In the Order to Cash business flow, what areas could potentially benefit from AI automation?
3. What areas of the company have been identified as running sub-optimally?
4. If accelerated, what document-driven processes could reduce working capital?
5. What sources of unstructured data, both inside and outside the company, could be harnessed to provide a distinct competitive advantage?
