27 Percent of Finance Departments Expect to Deploy Artificial Intelligence by 2020

27 Percent of Finance Departments Expect to Deploy Artificial Intelligence by 2020

27 Percent of Finance Departments Expect to Deploy Artificial Intelligence by 2020

The FINANCIAL -- A majority of finance departments expect to deploy one of several top emerging technologies by 2020, according to a worldwide survey of more than 400 organizations by Gartner, Inc.

“More than a quarter of organizations surveyed expect to deploy some form of artificial intelligence (AI) or machine learning in their finance department by 2020,” said Christopher Iervolino, senior director analyst at Gartner. “Moreover, half the respondents expect to deploy predictive analytics in the same period.”

The other technologies organizations expect to deploy in the same time frame are, in ranked order: mobile support for financial processes, robotic process automation (RPA), integration of external data, and AI or machine learning.

Mr. Iervolino explained that CFOs and other finance leaders are looking for new ways to reduce costs, improve controls and uncover fresh insights that could drive competitive advantage. The survey showed the ranking of nine common emerging technologies used to pursue these aims.

Despite rapidly growing interest in AI to improve financial planning and analysis (FP&A), only a few organizations are currently using it successfully, whereas the business case and best practices for other technologies such as predictive analytics and RPA are arguably better understood.

Gartner suggests using the following steps to get started with AI in FP&A:

Step 1: Examine Current FP&A Processes and Tools

Focus on existing shortcomings that could be improved with a more data-intensive approach, using more operational data and more direct participation from lines of business (LOBs). Then prototype proven vendor capabilities against these shortcomings.

Step 2: Expand Existing Financial Analytics Capabilities in FP&A Solutions

Look for underutilized capabilities the organization already has, such as data discovery, forecasting probability, correlation and exception detection functions. If needed, invest in analytics specialists or training to properly prototype these capabilities against known FP&A pain points.

Step 3: Pursue FP&A AI Opportunities

Once the finance organization has properly evaluated its existing tools, and built the expertise to use them, it will be in a strong position to build a business case to invest in an AI initiative, if the potential is identified. Moreover, it may demonstrate the need for the finance department’s involvement in existing AI initiatives.