The second part of the JofA s annual technology roundtable discusses the skills CPA firms must court to meet clients' increasing demand for insights on exponentially expanding amounts of business information.
You may have seen the headlines: "Rise of the Robo-Accountants," "How Artificial Intelligence Is Changing Accounting," "Blockchain: An Opportunity for Accountants? Or a Threat?"
The rise of transformative technologies such as robotic process automation, blockchain, and artificial intelligence (AI) has certainly raised concerns among many accountants about what their profession will look like in the future. What do CPAs need to be doing now to enhance their prospects for success?
The answer, it seems, is in the data. Not a specific number or some particularly juicy morsels of information, but all the data. The need to collect, organize, and mine data for business insights --all in real time--will present the accounting profession with unprecedented challenges and opportunities in a rapidly approaching, radically different future.
The skills that accounting firms and CPAs will need to succeed in a data-dominated, technology-driven economy took center stage during the second half of the JofA's annual accounting technology roundtable discussion. After exploring the impacts of technologies such as AI and blockchain in Part 1 of their conversation (see "Paving the Way to a New Digital World," JofA June 2018, tinyurl.com/y73oc4gy), the panel of accounting technology experts turned their attention to the people part of the future equation.
Short profiles of the panelists--Alan Anderson, Rick Richardson, and Amanda Wilkie--are on page 51.
The edited version of the conversation follows. To hear the roundtable in full, go to tinyurl.com/ydf4h8p5 for Part 1 and tinyurl.com/y9wulz9w for Part 2.
With new technologies changing the ways accountants do business, what effects do you foresee on the staffing model for accounting firms and accounting departments?
Richardson: Let's talk about some new brethren who are going to join the staff. The first is what the business is calling a data scientist. The second is what I'll call a big data engineer--not a data engineer, but a big data engineer.
In the data scientist classification, you are really looking at a combination of super technical skills and analytics. So they need to be able to program, to be able to handle statistics, to be able to handle large data sets. They are the ones the firm is going to...