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The sheer number of backlogs and delays across the public sector are unsettling for an industry designed to serve constituents. Making the news last summer was the four-month wait period to receive passports, up substantially from the pre-pandemic norm of 6-8 weeks turnaround time. Most recently, the Internal Revenue Service (IRS) announced it entered the 2022 tax season with 15 times the usual amount of filing backlogs, alongside its plan for moving forward.
These frequently publicized backlogs don’t exist due to a lack of effort. The sector has made strides with technological advancements over the last decade. Yet, legacy technology and outdated processes still plague some of our nation’s most prominent departments. Today’s agencies must adopt digital transformation efforts designed to reduce data backlogs, improve citizen response times and drive better agency outcomes.
By embracing machine learning (ML) solutions and incorporating advancements in natural language processing (NLP), backlogs can be a thing of the past.
How ML and AI can bridge the physical and digital worlds
Whether tax documents or passport applications, processing items manually takes time and is prone to errors on the sending and receiving sides. For example, a sender may mistakenly check an incorrect box or the receiver may interpret the number “5” as the letter “S.” This creates unforeseen processing delays or, worse, inaccurate outcomes.
But managing the growing government document and data backlog problem is not as simple and clean-cut as uploading information to processing systems. The sheer number of documents and citizens’ information entering agencies in varied unstructured data formats and states, often with poor readability, make it nearly impossible to reliably and efficiently extract data for downstream decision-making.
Embracing artificial intelligence (AI) and machine learning in daily government operations, just as other industries have done in recent years, can provide the intelligence, agility and edge needed to streamline processes and enable end-to-end automation of d …