Need a guide through the forest of new tech and innovation terminology? Here’s an overview of some of these technologies and what they could mean for your organization.
KPMG experts Steven K. Rainey, Brad Brown and David B. Kirk lay out a basic taxonomy in a recent TEI article. The tech innovations are “camouflaged by overly complicated terminology,” they assert, while also noting that “intelligent automation may not be a choice. It is no longer about ‘if’ but about ‘where, how, and how fast.’”
The co-authors divide the spectrum of intelligent automation into three categories:
- Basic process automation. Also known as “bots,” systems in this class (such as robotic process automation tools) digitize routine tasks that are performed the same way over and over, vastly accelerating the output. For example, if performed manually, a task like setting up a state tax folder for multiple unique entities might take a tax professional several minutes each time and involve dozens of clicks and/or menu selections. But, because the process is standard and repeatable, a bot can do the same work via a single user action or click.
- Enhanced process automation. Systems in this category leverage natural language processing and machine learning to handle complex transactions that involve both structured and unstructured data. Again, the authors offer a useful example: processing K1s, which may include unstructured data in variable formats and terms in attachments and footnotes. The software can extract and systematize this information. As a result, the authors explain that “the tax filing process using information from the Schedule K-1 and related white-paper details may be expedited, and quality and consistency can be enhanced by reducing the likelihood of manual errors.”
- Cognitive automation. The most hyped, but also the most promising category, cognitive automation systems mimic human capabilities such as perceiving, gathering evidence and making judgments. These systems are trained, rather than traditionally programmed, to operate in specific knowledge domains – for example, a particular federal or state tax law. “The real power of cognitive computing is its ability to ingest massive amounts of data about which to formulate hypotheses,” the KPMG experts note. “The human brain cannot handle this volume of data and does not have the time to absorb it, let alone process it.”
The article offers a lot more content that will interest tax leaders, including a glance at the history of intelligent automation, thoughts on how it will impact tax professionals’ careers and an assessment of the potential benefits for tax departments.
Please remember that the Tax Matters provides information for educational purposes, not specific tax or legal advice. Always consult a qualified tax or legal advisor before taking any action based on this information.