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RPA and AI: Living up to the Hype?

What you’ll learn


  • Examine areas of future growth in AI
  • Consider four key factors when adopting RPA and AI as part of your O2C process
  • Hear the survey findings of fellow accounts receivable professionals when asked about their digital transformation integration
  • Discover how peers are assessing business areas that can benefit from automation

Robotic Process Automation (RPA) and Artificial Intelligence (AI) have promised great things but are organizations truly seeing the scale of value that lives up to this business process automation revolution? HighRadius and sharedserviceslink set out to get the answers by surveying senior order-to-cash (O2C) and finance leaders on adoption rates, challenges, how these technologies have impacted finance, and where they are falling short.

The results of the survey and interactive discussion that followed tell us that now is the time for us all to move beyond the hype and focus on what it takes to stay competitive and truly transform business. AI engines can tackle vast amounts of manual processes that overwhelm employees, including processes around cash applications, credit management, collections management, and dispute management.

Some of the key conclusions from the survey are explored below.

Current landscape

Over half of respondents (55%) surveyed are either not using RPA yet or are in the early adoption stages. Of those using RPA, 66% confirmed it has made a positive impact but only 15% confirmed it had truly transformed processes.

While these statistics do not align with the hype around the adoption and advantages of RPA, they certainly match the reality that the RPA market is still very much in a growth stage.

“RPA is still the shiny new kid on the block. The path to successful, scalable automation remains littered with trial and error, and nobody has written the gold standard yet.”
The Forrester Wave™: Robotic Process Automation Services, Q4 2019

Examining some of the reasons for low adoption, 80% of respondents feel that not having in-house RPA skill sets and the ongoing maintenance of bots are key barriers to successful implementation.

Getting RPA solutions up and running demands a significant amount of coding work — both upfront and on an ongoing basis — this requires a certain skill set and often budgeting for professional services.  What’s more, the realization of what is involved in rolling out and maintaining an army of bots is a huge challenge that often doesn’t get the recognition it deserves.

This might explain why many companies deploy and maintain far fewer bots in practice than they initially purchase.

Evaluating AI adoption

Only 1/3 of those surveyed are using AI with 50% demonstrating a positive impact on their operations
From the survey “RPA and AI: Living up to the Hype?” by HighRadius and SSL

Within the last year, we have seen customers voice their desire for RPA solutions that extend beyond individual task automation, integrating AI components to enable broader use cases and more sophisticated task variation. This is just the beginning but begs the question as to why there is such low adoption in the industry?

58% of those surveyed state the inability to fully comprehend and communicate the business potential of AI in their business processes as a key barrier to success. As with similar challenges we see with RPA adoption, 48% also state the difficulty in building in-house expertise to build machine learning or AI applications from the ground up.

Areas of future growth in AI are generally consistent with where they are most used;

AI for analysis and RPA for processing.

Facing the reality

The survey results also tell us that:

  • Automation levels are particularly low and data is not being used for decision-making purposes
  • RPA is being used to some extent, with positive outcomes but organizations need to upskill their workforce to reduce the number of bot failures
  • A minority are using AI, with many organizations having plans to leverage this capability further to empower analytics. However, it seems there is still a lack of knowledge and use cases to demonstrate where and how finance teams can leverage AI to its full potential.

A 2020 survey by Deloitte states that 53% of their respondents started to implement some form of RPA, and this percentage will become 72% by 2022. We know that RPA isn’t just noise, but it’s clear organizations need to be realistic and engage with experts to help them identify and deliver the most value to their organization.

Moving beyond the hype

Based on working with over 200 companies globally, we believe there are four key factors to consider when adopting RPA and AI as part of your O2C process.

  1. Take a more holistic approach to process management. Businesses should connect with IT and client-facing teams to embrace new process initiatives to help drive change. Resisting new tools and processes in favor of old ways of working will slow down transformation efforts.
  2. Digital transformation is not just about technology. Equally important factors are people and process. Recognize the value of upskilling and leveraging the right data and technology to aid decision-making. Set up continuous improvement programs to ensure skill sets are at the right level to achieve an outstanding, sustainable customer experience.
  3. Leverage a fully integrated O2C integrated receivables platform.  Leveraging a single platform to automate financial processes and manage the entire O2C cycle increases productivity, enhances cash flow and makes it easier for clients to do business with you.
  4. Select a partner based on their RPA and AI references. To communicate the value of AI to stakeholders, organizations should work with a partner that is dedicated to customer success. When evaluating providers, ensure you speak to their customers about how they are leveraging RPA and AI – do these results provide deductive reasoning to come to an outcome, such as predicting invoice disputes or payment delays for example.
“There will be many situations when you need to adjust your finance tool to quickly adapt to changing customer demands and behaviors. We leverage AI through intelligent automation from HighRadius to make these real-time adjustments and deliver a better experience for our customers. This is invaluable and a stand-out capability when evaluating other tools in the market.”
ABInBev

The results of the survey and interactive discussion that followed tell us that now is the time for us all to move beyond the hype and focus on what it takes to stay competitive and truly transform business. AI engines can tackle vast amounts of manual processes that overwhelm employees, including processes around cash applications, credit management, collections management, and dispute management.
Innovations in RPA and AI allow finance teams to reduce the number of manual transactions posted, close their books faster and reduce the cost of regulatory compliance. Organizations that do not leverage these capabilities fully through an integrated receivables O2C platform, will inevitably lose market share and struggle to build long-lasting relationships with their customers.

There’s no time like the present

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HighRadius Integrated Receivables Software Platform is the world’s only end-to-end accounts receivable software platform to lower DSO and bad-debt, automate cash posting, speed-up collections, and dispute resolution, and improve team productivity. It leverages RivanaTM Artificial Intelligence for Accounts Receivable to convert receivables faster and more effectively by using machine learning for accurate decision making across both credit and receivable processes and also enables suppliers to digitally connect with buyers via the radiusOneTM network, closing the loop from the supplier accounts receivable process to the buyer accounts payable process. Integrated Receivables have been divided into 6 distinct applications: Credit Software, EIPP Software, Cash Application Software, Deductions Software, Collections Software, and ERP Payment Gateway – covering the entire gamut of credit-to-cash.