4 Behavioral Strategies for effective Finance-AI delivery

You may not get the desired business success just by investing in new-age technologies and automation and integrating them into finance functions. No doubt, the implementation of digital capabilities does fuel finance functions that bring agility, efficiency, and output in business, however, it needs a strategic direction and an approach. As the adaptation of new-age technologies and AI is at a very nascent stage in finance departments, many finance leaders and executives fail to see its long-term result of it. But according to a Gartner study, organizations that have followed 4 behavioral strategies in implementing AI Finance have rigged out more use cases than companies who have not taken it.

Hiring AI-specific Talent 

A big force in leading the finance transformation in organizations is hiring the best and right AI talent. The biggest challenge for finance companies today is keeping pace with regulations and innovation, but what bridges this gap is AI and new-age technologies. Most companies have experienced that hiring the best AI talent has actually helped finance leaders and CFOs to lead operations and produce favorable business output effectively. A key factor plaguing finance organizations today is data deluge and deploying AI-skilled staff can help CFOs and leaders up the business game. According to Forbes, the banking industry can save up to $1 trillion by 2030 if it banks on AI and new-age technology integration into finance functions. Employing AI-powered staff can work with the AI nuances and helps them overcome inertia in working with new AI applications and expand the learning curve.

AI for Quick Wins

Finance leaders while making technology investments to achieve enhanced customer experience, customer loyalty, customer behavior, real-time data collection, and analysis and drive decisions making must ensure that they are embedded with automation capabilities. This not only supports finance leaders to transform finance functions but also enables finance leaders to experiment with AI tools and technologies and apply them in different use cases. By doing this, finance executives build business models for different challenges arising on the horizon. Building in-house AI talent source reduces the organization’s dependency on external use-cases.

Fail-Fast Approach

Finance leaders in companies are taking an early fail-fast approach to avoid any guesswork while deploying AI into finance operations and functions. CFOs must conduct ample pilots to ease deploying AI process into appropriate finance functions and zero on the most successful pilots in the future. Numerous AI pilots promise huge productivity gains. Accounting, back-office processing, and cash flow forecasting are three popular use cases explored by successful organizations, unlike others who explore one like customer payment forecasting. 

AI-Finance Leadership

To fully optimize the benefits of AI and new technologies in finance functions, CFOs must ensure that the process and execution are entrusted to experts in AI. For instance, rather than a Finance Controller, the head of Finance Analytics can be vested with the leadership to lead AI deployment in finance functions. Head of Finance Analytics would be more successful in integrating AI into finance operations as their expertise and domain are closely related to finance and new-age technologies. Moreover, a financial analytics head would sideline any traditional finance function and focus more on AI complexities and challenges every new digital capability integrated with finance functions in relation to the business context.

Experienced finance professionals and leaders can achieve these strategies by opting for the Executive Programme in Digital finance Transformation offered by IIM Lucknow, in association with Miles Education.