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Artificial intelligence (AI) is making a big splash in enterprise applications across the board, but most of the attention has gone to public-facing functions like chatbots and personal or professional assistants. But this masks the fact that much of the real action is taking place behind the scenes, in the myriad back office processes that contribute to the costs and complexities of running a modern organization.

AI is not like previous generations of technology, however, which were targeted at specific operations and crafted to operate in a predefined manner. Instead, the challenge for the enterprise is to create the kind of training and development processes that allow AI to place traditionally manual processes under fully automated control – essentially assuming the day-to-day work of running the office while the labor force focuses on continued optimization and strategic development.

Right AI for the Job

Not all back office processes are the same, however, and some will take to this new paradigm more quickly than others. The task at hand, then, is to determine which functions aren’t just the easiest to automate but will contribute most directly to the bottom line.

According to Automation Anywhere, a developer of robotic process automation and other technologies, organizations that are seeing the best results from back office transformation have focused on these key areas:


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  • Accounts payable: AI is far more capable of scaling operations in response to incoming workloads than a team of clerks. This takes the bite out of time-consuming tasks like data extraction and validation, proof-of-delivery and posting to ERP and financial platforms.
  • Accounts receivable: Likewise, AR is peppered with cumbersome jobs, mostly centered on order processing and fulfilment, as well as invoicing and cash allocation.
  • Employee onboarding: AI handles rote tasks like filling out forms and populating databases, which frees up staff to handle more challenging aspects of the job like recruitment and retention.
  • Employee data management: This is a high-volume, transaction-heavy process where one task often triggers multiple others. Automation is expected to reduce costs in this area by as much as 40%.

The healthcare industry, in particular, is looking at substantial gains in cost reduction and operating efficiency by turning back office procedures over to AI. As a highly regulated industry, healthcare faces mountains of paperwork related to everything from patient outreach and scheduling to insurance claims and fulfillment of prescription medications.

A recent analysis by MIT/Sloan Management showed that admin costs make up more than a third of the healthcare burden in the U.S., averaging about $2,500 per person. AI can take over many of these tasks, such as medical coding, billing and reimbursements, while at the same time cutting down on errors, waste and fraud. And unlike the more noticeable advances taking place on the clinical side, back office AI does not need FDA approval or other regulatory burdens to be implemented.

Lightening the load

No matter the industry, one of the biggest office burdens any organization faces is document management. Whether it is scanning, storage, collation or any number of other jobs, managing documents is a burdensome, time-consuming task. According to Managed Outsource Solutions, however, AI is quickly making its way into a wide variety of document-related apps, which is not only making these processes faster and more efficient, but more secure as well. Forward-leaning organizations are finding that automated scanning, data extraction, clustering and categorization also bring more unstructured data into analytics platforms at a faster pace, which improves overall business intelligence and hastens decision-making.

Be forewarned, though – deploying AI into back office processes isn’t like flicking on a switch, says ITPro’s John Loeppky. For one thing, different jobs will benefit from types of AI, whether it’s general intelligence, machine learning or more advanced forms of deep learning and neural networking. Likewise, over-deployment of AI can prove troublesome if the human workforce is not being trained to draw maximum benefit from the technology. Ultimately, business leaders need to understand that old-fashioned ROI still governs any technology deployment.

No doubt the headlines going forward will be chock full of walking, talking, driving forms of AI. But it’s fair to say that the real action is behind the scenes, where it not only reduces the cost of doing business but provides a more responsive and productive environment both at home and in the office.

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