Can AI and Automation Replace Accountants?

Technology is changing Finance and Accounting in a big way.

A few years ago, The Coca-Cola Company began reviewing its existing balance sheet reconciliation process across 50,000 general ledger accounts. Multiple systems and manual processes had created serious challenges which saw more than 800 associates spending 14,000 hours a month on reconciliations alone. By moving from manual processes to automation, Coca-Cola was able to reallocate 40% of the team involved in manual and routine reconciliations. The team was then able to focus more on activities like metrics, reporting, IT controls, and change governance. Since the shift in 2015, the company has realized millions of dollars in efficiencies that have been reinvested into the accounting function.

A recent survey by Deloitte found that out of 400 respondents, 72% say their C-suite is supportive of Robotic Process Automation (RPA) and 53% say they already have an RPA initiative underway. These numbers will continue to grow as the demographics of the workforce change. India is also an important market for RPA if one is to go by the proliferation of RPA start-ups in the ecosystem.

The other issue to consider is that of talent. Millennials now constitute roughly one-third of finance teams today. Yet, according to 74% of CFOs surveyed for EY’s The Changing Role of the CFO, finance organizations are facing a talent crisis. Even with the encouraging number of young people working in the finance and accounting industry today, only 25% say they will stay according to a CEB (a Gartner subsidiary) Global Labor Market Survey. The CEB survey also states that “in every case…people welcomed…technology because they hated the tasks that the machines now do, and it relieved them of the rising pressure of work.”This sentiment reflects the future of the accounting and finance profession—rote, transactional tasks aren’t worth your teams’ valuable and over-stretched time anymore.

Accountants who want to ensure career viability and succeed in the long term must develop technical competence in the areas of data analytics, data science, business intelligence, and information systems and expertise in more traditional (yet high-demand) skills like financial planning, decision support, internal controls, and risk management.

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