A new study released by Tata Consultancy finds that a majority of companies see artificial intelligence (AI) as “essential” to competitiveness with widespread adoption expected across job functions by 2020 in areas such as finance.
With finance leaders serving as the data stewards at many companies, we see a transformation of the Office of Finance. The promise of AI, cloud adoption, new technologies and the trend towards self-service has also influenced the evolution of the CFO role. They are becoming more of a strategic leader. CFOs now spend more time optimizing the business and less time on finance administration. A recent McKinsey study cites that four in 10 CFOs say they spent the majority of their time in the past year on activities other than traditional and specialty finance.
According to KPMG, AI will push finance into more complex and judgment-led analysis roles, which demands more creative and strategic skills such as developing commercial insight from financial analysis and using financial expertise to influence the business.
In this scenario, the CFO also assumes the role of the “chief data officer.” Aside from managing financial health, the CFO collects and interprets data coming from an ever-expanding array of sources. Beyond internal financial metrics, this involves having a steady pulse on financial markets, investor sentiment, plus micro-economic and industry data points. With the increasing fragmentation of both internal and external data, decision-making can be a complex and daunting undertaking.
Traditionally, finance leaders focused on lagging indicators. By bringing AI to corporate performance management (CPM), CFOs can raise the bar, gaining forward-looking indicators needed to uncover new opportunities faster and address issues proactively. For example, machines can quickly detect unusual spike in orders from a particular location, unusual expense items recorded by an individual, or unusually favorable terms contained in equipment leases recorded for a supplier.
Before investing in new AI capabilities, what must the Office of Finance consider to effectively evaluate its potential?
To design a successful roadmap, identify a mix of basic automation techniques, machine learning and of course human intervention and management.
In addition, consider the following to realize the full potential of AI for automating routine tasks and to differentiate and drive new innovations for the Finance function:
- First build a solid foundation: AI will only work once you have a solid foundation to deriving trusted insights. This means having a handle on your data and managing its growing scope. Furthermore, the data you feed these algorithms will make a difference, so data quality is more important than ever.
- Use AI to deliver more reliable data faster: Once you assemble your data into your ‘information supply chain,’ you can leverage AI tools to automate the processes to assure the governance, quality and reliability of your data, such as automating the clean-up of your growing data sources.
- Surface smarter insights faster: Once you have the foundation, you can make your data smarter and more helpful with AI and business intelligence tools for smarter interpretation. By injecting learned patterns from your data, you can surface alerts and gain forward-looking insights. This will allow the Office of Finance to be more proactive and improve efficiencies across the entire Finance function.
While the future of AI promises to be transformational for businesses, it’s still early days. How are you leveraging AI in your organization? I’m interested in your thoughts.