First of all, AI optimizes the time that the CFO’s team invests in error-prone and labor-intensive tasks and therefore, augments the role of each member of the CFO office. And in the long run, this will help members of the CFO office to focus their time on strategic and higher-value initiatives, rather than executing mundane repetitive tasks.
At HighRadius, we speak to 1000s of CFOs every year and understand their constant tussle with repetitive and complex workflows that take up a significant portion of the bandwidth of the members in their offices as they attempt to navigate the O2C process in an old-fashioned manner.
We have seen how businesses leverage AI capabilities to improve their cash flow and strengthen working capital. However, the CFO’s office continues to have some reservations about implementing AI. In this blog, we’ll focus on the apprehensions that keep CFOs from investing in AI and the right way to overcome these apprehensions.
The adage “The sooner you begin, the better it is,” holds true here. According to a survey by Rackspace technology, 26% of companies considered that the higher implementation cost of AI was one of the biggest barriers to adopting AI. And yes, that holds true to some degree, because implementing AI is a considerable investment in terms of selection, implementation, and maintenance of corresponding software.
In 2022, CFOs will 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 understand that the investment in choosing the right tech will bear returns in the future.
Additionally, CFOs need to focus on the future that AI technology offers, and how it impacts revenue and employee productivity for the CFO 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.
The next aspect that CFOs need to cater to is the ambiguity associated with the impact of AI adoption on team productivity. The primary concern is around the team’s ability to learn the skills required to use AI quickly.
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.
You can resolve the inhibitions of teams with proper training which software vendors provide as a part of solution offering. Here are some steps to ensure that a dynamic team leverages AI-powered software and easily accepts the new solution:
It is imperative to remember that the success of any software depends on how your team leverages it. Following these steps will ensure that your team moves forward in the right direction.
Finance is one of the most critical departments in an organization and therefore, it can be difficult to entrust it to relatively nascent technology. AI is here to help your team do their jobs better and help your business manage scale with limited team size to improve employee productivity and decision-making ability.
CFOs need to educate their teams that AI is going to mimic human intelligence and will aid the decision-making and problem-solving abilities of employees. AI will help improve bottom-line Key Performance Indicators(KPIs) like Days of Sales Outstanding, Average Days Delinquent, Reduction in bad debt, etc with a touch of innovation and creativity.
As the CFO, you need to tell your team to be patient. AI will prove invaluable once they learn how to harness its power. And while it is still in its infancy, your team shouldn’t doubt the capabilities of AI offerings. Rather encourage them to consider the AI-powered solution like an intern, which needs to be fed intelligence to eventually lower your workload without compromising on quality.
Bonus tip: It’s equally important that your employees understand that an AI-based software solution is not going to eat their jobs but add to their ability to do their jobs better and manage larger volumes.
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.
For Artificial Intelligence to function properly, the AI/ML/NLP models need lots and lots of data. The more data is provided, the more rigorous the model training is. This is a cause for concern for many CFOs as the amount of data that their organization generates might not be enough to warrant the use of Artificial Intelligence. And as mentioned above, AI/ML learning from inadequate or inaccurate data sets runs a risk of bias and liability.
Let’s understand how this problem can be solved with an example. If you are a mid-market organization using a fully-loaded top-of-the-line software with an average number of clients, then you’ll need to wait until the insufficiency of data is overcome and the confidence level with which recommendations are made are more reliable.
For these early days of deployment, don’t refrain from using the solutions. Rather use your available manpower to train the system on what’s right and what’s not. Discuss this with your software vendor and jointly decide how you can overcome this challenge.
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 an accounts receivables function standpoint, mid-market CFO offices can leverage AI to:
So, with AI at your disposal, you can collect money on time, post cash efficiently, and resolve disputes from the timely onboarded happy customers. The combined outcome will ensure strengthened working capital for CFO offices. At HighRadius, we aim to enable CFOs offices to overcome their hesitation with the adoption of AI & automation technologies to modernize their processes.
Get in touch with us to learn how organizations like yours have benefited from our AI-based solutions. Request a demo here!
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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