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AI vs Human: CFOs Should Use Both
Financial Services Review | Monday, December 26, 2022
Work is elevated by business technology, yet the employee retains control. Without significant training or challenging interfaces, good technology is a superpower that enables users to do, see, and understand more.
FREMONT, CA: Business technology improves work while giving employee control. Good technology can do, see, and understand more for people without requiring in-depth training or challenging user interfaces. The need for such enabling technology has never been stronger for the CFO, which is coping with continually fluctuating economic conditions, a faster speed of business, and an overwhelming deluge of data.
Finance and accounting teams, on the other hand, cannot be expected to become data scientists to acquire, evaluate, and quickly extract value from an ever-increasing amount of data. For them to be able to move quickly, they need better tools.
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Artificial intelligence and machine learning (AI/ML) are current technologies that have been helpful. Application of these skills must take into account those working in accounting and finance.
People-first Technology: Technology is highly innovative and powerful, performing great feats at speeds never previously possible that humans may be unable to complete. However, some technologies offer options that individuals might not desire or that are not compatible with current procedures e.g. Google Glass, 3D television, Windows Phone, etc. No matter how innovative, technology must address a problem and inspire user interest to succeed.
Finance executives desire technology that will enable them to complete their tasks more quickly and accurately to translate them into the Office of the CFO terms. It should complement their years of experience and training, support current finance and accounting procedures, demonstrate demonstrable value, and be something they want to use.
They are intuitively aware of how it functions, have the option of ignoring it, and have control over how and where it adds value. AI/ML flags the words and phrases it believes are incorrect and make the final decision. No language proficiency, spelling bee champion, or Modern Language Association (MLA) Handbook is required. The technology does the work to assist in avoiding mistakes, and it does it effortlessly, contextually, and without taking up additional time while leaving in charge.
The speech-to-text technology from the late 1990s failed if they're old enough to remember it. It promised a bright future in which microphones will replace keyboards for voice-activated computers and quick, simple content creation. However, one crucial factor was overlooked by the developers: users don't want to communicate with their computers.
Software designers must comprehend their target market and how they operate to understand their difficulties and create solutions for those who are carrying out the work. The constant expansion of data has been a problem for all of them. They are producing more of it with more tools, and it is arriving more quickly. Employees can't sort through all of this data, become data scientists, and identify anomalies, opportunities, and statistically significant trends within numerous datasets. But without having to become data scientists, AI/ML may assist those working in finance and accounting in utilising their data in novel, cutting-edge ways.
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Businesses operating across multiple jurisdictions face tax questions that extend well beyond their home market. A company with operations in Singapore, India, Malaysia or Australia may be navigating local corporate tax rules while also dealing with transfer pricing, withholding obligations and global reporting requirements. That complexity has expanded the role of advisory firms well beyond tax compliance into broader business planning.
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