Even as the recession cloud still looms over and inflation is at an all-time high, the CFOs office continues to invest in digitizing their operations and is leaning more than ever towards AI adoption. In fact, by 2025 the market for artificial intelligence (AI) software will reach almost $134.8 billion.
It is clear that with the unprecedented growth opportunities that AI capabilities can offer the CFOs, they can develop a robust and recession-proof strategy and implement them across specific use cases.
This disruption has also made executives working across departments like sales and operations rely more on the finance function for insights and analytics. Moreover, finance leaders are expected to recession-proof their finance functions as well as make frequent adjustments to recent cash flow data. However, this explosion of information can be overwhelming, especially for the finance teams, as they continue to operate spreadsheets and other manual methods to manage data. This not only results in increased manhours, but also impacts data integrity, and leaves little to no time for finance teams to run detailed analysis and provide strategic recommendations. Hence, finance leaders have realized that automation is the best strategy to eliminate siloed manual processes and enable global visibility, transparency, compliance, and standardization. It also protects their business and bottom line from any economic uncertainty.
AI adoption is no longer just about reducing costs, but it has become a catalyst for revenue growth. CFOs need to change their outlook on the cost aspect of AI and understand that its value proposition justifies a business case for investment. Through this new lens, CFOs need to know that the investment in choosing the right tech can protect their business from any recession-induced situations.
Additionally, CFOs need to focus on the future that AI technology offers, and how it impacts revenue and employee productivity for the CFOs office. A good case in point is an investment to enhance your collections strategy and predict a delay in invoice payments resulting in 50% faster collections. In such a case, the cumulative return on investment (ROI) justifies the investment in AI to improve collections efficiency.
And the way AI works, the more data is fed for customer payment behavior; the better the algorithm is equipped to help you make informed decisions to enhance collections efficiency.
After learning how to overcome the roadblocks to AI adoption at mid-market CFO offices, let’s pick a scenario to understand how AI helps CFO offices be successful in strengthening working capital.
The companies which have overcome inhibitions around AI adoption have seen a major impact on their bottom line KPI performance, the productivity of employees, and streamlined processes. From accounts receivable function standpoint, mid-market CFO offices have leveraged AI to:
The next aspect that CFOs need to cater to is the ambiguity associated with the impact of AI adoption on team productivity. Moreover, The primary concern is around the team’s ability to learn the skills required to use AI quickly. These fears are predominantly stoked not only due to AI adoption across organizations, but also the economic uncertainties and the resultant job loss in a few sectors.
Needless to say, this concern is genuine; every CFO needs to ensure that their team welcomes the shift in technology. The right mindset and effective change management to leverage the capabilities that AI offers will speed up the process.
But, you can resolve the inhibitions of teams with proper training which software vendors provide as a part of their solution offering. Here are some steps to ensure that a dynamic team can leverage AI-powered software and easily implement the new solution:
It is imperative to remember that the success of any software depends on how your team leverages it. Following these steps to will ensure that your team moves forward in the right direction.
AI/ML models are trained by using existing datasets that an organization accumulates over time. There is a chance that the AI model develops biases, including cognitive biases, deployment biases, and aggregation biases that will negatively impact work.
If the data points being used by the AI algorithm have a built-in bias, it will affect the decision that the CFO makes.
But, there is a solution to this! To achieve trustworthy AI-enabled applications with accurate outputs consistently across myriad use cases and users, you need effective frameworks, toolkits, processes, and policies to recognize and actively mitigate AI bias. Available Open-source tools can assist in testing AI applications for specific biases, issues, and blind spots in data.
HighRadius collaborates with the world’s top CFOs to integrate artificial intelligence into their finance processes across Order-to-Cash, Treasury, and R2R. It helps the CFOs office to onboard customers seamlessly, streamline their collections, run cash posting efficiently, and manage disputes effectively. Adopting AI-enabled finance solutions ensure that CFO offices possess stronger working capital, preparing them to deal with any recession-related situations.
Automate invoicing, collections, deduction, and credit risk management with our AI-powered AR suite and experience enhanced cash flow and lower DSO & bad debtTalk to our experts
The HighRadius RadiusOne AR Suite is a complete accounts receivable solution designed for mid-sized businesses and SMBs to automate eInvoicing, Collections, Cash Reconciliation, and Credit Risk Management to enable faster cash conversion and maximize working capital.
It is quick to deploy and ready to integrate with ERPs like Oracle NetSuite, Sage Intacct, MS Dynamics, and scales to meet the needs of your order-to-cash process.
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