Even its harshest critics will attest to that. According to a report from Gartner, 30% of businesses will be leveraging AI by the end of 2024, and it’s likely that that number has only grown since the report’s publication. As this technology gains increasing popularity, the question is no longer whether it’s worth using but how it should be used.
More importantly, the question is how to use AI responsibly. The answer is the foundation of “Responsible AI.”
For finance teams, Responsible AI is an especially large concern. With its sensitive data, privacy compliance, and industry standards, there is perhaps no other sector more regulated and high-stakes than corporate finance. As a result, devising a strategy for AI deployment that neither violates essential compliance guidelines nor throws brand trust into question is essential. When finance teams want to harness AI solutions to expedite and automate vital business processes, honing in on what AI solutions are ethical, safe, and responsible is key.
To fully understand the subject of Responsible AI, we first need to establish a framework for what Responsible AI actually means. While the term itself might suggest a basic definition, it is frequently more nuanced than it seems.
To quote Microsoft:
“Responsible Artificial Intelligence (Responsible AI) is an approach to developing, assessing, and deploying AI systems in a safe, trustworthy, and ethical way."
"AI systems are the product of many decisions made by those who develop and deploy them. From system purpose to how people interact with AI systems, Responsible AI can help proactively guide these decisions toward more beneficial and equitable outcomes. That means keeping people and their goals at the center of system design decisions and respecting enduring values like fairness, reliability, and transparency.”
This might seem simple enough, but there is more to it, so let’s dive slightly deeper.
Both the development and usage of artificial intelligence must be based upon a fundamental understanding of how the tools in question will be used, what they will be used for, and in which areas their usage might be risky or inappropriate.
For finance teams and organizations, this means that Responsible AI should not begin or end with the question of convenience. Rather, the AI solutions that a business deploys must guarantee the proper security and assurance that the customer expects.
AI solutions that a business deploys must guarantee the proper security and assurance that the customer expects.
As we’ve seen, the best AI tools are designed to partner with the essential human components of finance organizations. They do not take over the driver’s seat, but they make the journey from start to finish on a workflow a little smoother.
Take Enterprise Resource Planning (ERP) systems as an example.
Many popular ERPs lack the dynamism and flexibility to keep up with the fast pace of financial needs for businesses. They provide a hearty wealth of features and functionalities, but they still put the onus on the teams who use them. As a result of this, there is increased risk due to manual resource burnout, a tendency to skimp on financial reporting for the sake of convenience, and a growing chance that small but essential compliance issues might slip through the cracks.
With augmentative AI (emphasis on augmentative), the teams working with Enterprise Resource Planning systems have some of that strain lifted off their shoulders. With automated processes dedicated to journal entries, estimating supplier accrual expenses, matching third-party data sources, and general ledger reconciliation, your personnel could spend fewer resources on repetitive manual tasks and more time ensuring the consistency and accuracy of your financial and compliance obligations.
With augmentative AI, the teams working with Enterprise Resource Planning systems have some of that strain lifted off their shoulders.
As a Workday Ventures company, Auditoria.AI is fundamentally committed to helping financial enterprises and teams harness the power of artificial intelligence and machine learning efficiently, effectively, and responsibly.
Auditoria’s AP Helpdesk and AP Accruals, part of the Auditoria.AI SmartBots for Workday SKU, help simplify a wide range of use cases related to the workload of accounts payable teams. Here’s a quick look at what Auditoria.AI has to offer:
All of Auditoria’s solutions are built upon a foundation of advanced AI technology to make work easier and more thorough for corporate finance teams. We strive to help our customers improve both their productivity and compliance by reducing processing time and errors, decreasing the cost of processing invoices, and more.
Auditoria.AI strives to help our customers improve both their productivity and compliance by reducing processing time and errors, decreasing the cost of processing invoices, and more.
With the help of our tools and technology, your business is in a better position to make the most of its resources, minimize close time, and eliminate the manual processes that are susceptible to human error, such as is often the case with supplier accrual outreach processing.
But, as we emphasized before, efficiency is not the foundation of effective AI usage—responsibility is.
This is why, in our commitment to Responsible AI, we have been certified for the Workday Responsible AI Badge and the EU-US Data Privacy Framework.
AI is here to stay—there’s no getting around it.
For many, the promises of AI's technological whirlwind are immensely exciting. The prospect of eliminating the pesky, headache-inducing manual tasks that bog down the day and frequently invite error seems like a cause for celebration. And it is—as long as you remain dedicated to the principles of Responsible AI.
In the realm of finance, there’s great potential to be mined from the capabilities of artificial intelligence and machine learning, and there is promise for even greater relief for the teams that enjoy its benefits and reap the rewards. AI has given us some immensely powerful tools. Of course, with Great Power…well, you know the rest.
When evaluating artificial intelligence-based software to be used by enterprise finance teams, it is paramount to consider AI governance practices to ensure transparency, accountability, and compliance. Check out this checklist of questions to ask of an AI vendor.
Proper governance mitigates risks associated with data privacy, algorithmic biases, and potential financial fraud. It also aids in aligning AI applications with corporate objectives and ethical standards, ensuring that AI-driven decisions are justifiable and accountable. Read the eBook to learn more about AI Governance.