Moderated by Emily, Digital Transformation Consultant at Hyperbots
Emily: Today’s discussion is special as I have John with me. John is the CEO at LiveData LLC, and today we will talk about the journey of automation in the past versus now, especially in the finance and accounting segment. So, before we begin, John, do you mind telling us a little more about yourself?
John: Yeah, no problem. Thank you for having me. It’s a pleasure, and it’s a topic that I love to talk about how to automate. I’ve been involved in this field my entire career. It started with Excel sheets and figuring out how to make them work as simply as possible. As technology evolved, I was able to utilize it more. Now, running LiveData LLC, we help companies with finance automation and process improvements throughout their business.
Emily: Thank you for the introduction, John. You’ve said that you’re a firm believer in the power of automation, and over the last decade, you have spearheaded many automation projects in various organizations. Can you summarize some of the automation projects you’ve implemented?
John: Sure. The biggest projects have focused on enabling finance personnel to work on tasks that add real value instead of just pulling together reports. Initially, I built Excel models using Hyperion, analytics, and financial reporting to simplify data processing. Then, we moved to more automated processes using bots and tools like UiPath for repetitive tasks, such as invoice processing, to eliminate manual data entry. With the advent of OCR technologies, we further reduced manual intervention. Now, I’m excited to be working with HyperBots on AI automation, which is the next generation of finance automation.
Emily: That’s amazing. John, we see a lot of AI buzz today with claims of AI transforming business operations. What is your take on that?
John: The buzz around AI is justified because we can now utilize it in ways we never could before. It’s not just about making machines more intelligent but about processing all the available data both web-based and internal to provide higher-quality answers and insights. Tasks that used to take weeks can now be completed in minutes.
Emily: I agree. What have you been hearing in your peer group about the possibility of AI transforming finance and accounting processes?
John: It’s a critical time for finance and accounting to adopt technology. Historically, finance professionals have relied heavily on manual processes, but now, with the shortage of accountants and the complexity of tax laws and transaction volumes, it’s essential to adopt the latest technologies. Those who don’t adopt will likely fall behind their competitors.
Emily: From a business perspective, what impact does modern automation have compared to traditional methods?
John: Modern automation tools can go beyond just pulling numbers they can provide natural language feedback, synopsis, hypotheses, and suggest areas for further investigation. In the past, tasks like data processing could freeze your computer or take a day to complete. Now, we can get real-time, insightful feedback.
Emily: Can you give some examples of intelligent tasks that weren’t automatable before but are now possible with AI?
John: One example is the variance analysis. In the past, tools like Hyperion automated reporting but couldn’t provide insights about the data. Now, AI can analyze variances and suggest reasons, such as changes in volume or price. It can even correct data inaccuracies and highlight potential issues.
Emily: Let’s talk about invoice processing. Can you elaborate on how AI improves this task?
John: Previously, invoice automation struggled with inconsistencies and required manual data correction. Now, AI can understand invoice details even if they aren’t perfectly formatted, extracting information like amounts, tax details, and vendor names, and suggesting appropriate accounting actions. This reduces the need for human data entry and improves accuracy, allowing accounting staff to focus on review rather than data correction.
Emily: We’ve certainly come a long way. Why wasn’t this possible before, and what has changed in the technology landscape?
John: The biggest change has been the increase in computing power, enabling us to process vast amounts of data in seconds. Previously, tasks like reserve calculations could take 18 hours and weren’t feasible to run frequently. Now, we can run these calculations daily and get real-time insights.
Emily: Are there tasks in accounting that will always require human intelligence?
John: Absolutely. While AI can make us more accurate and efficient, it can also produce errors or hallucinations that need human oversight. Strategic tasks, especially those involving future planning with no existing data, will always require human intelligence and creativity.
Emily: What are the differences between traditional automation and AI-led automation?
John: Traditional automation required exact processes and rigid programming. AI-led automation is more flexible, can learn from other data, and suggest new ways to improve processes without needing explicit programming. However, we must be cautious of information overload and potential errors from AI.
Emily: What challenges do you foresee for CFOs in adopting AI-led automation?
John: There will be challenges, just like with any new technology. One major issue is ensuring data security and accuracy. AI can sometimes produce incorrect results, and if trusted too much, this could lead to significant errors in financial statements. It’s crucial to balance adoption with oversight.
Emily: How do you see AI-led automation impacting finance and accounting over the next two years?
John: Adoption will be rapid due to the shortage of accountants and the need for efficiency. We’ll see tools becoming smarter and more integrated into daily operations. Companies that adopt AI will likely experience fewer errors and greater efficiency, while those that don’t may struggle to keep up.
Emily: Any advice for CFOs who are unsure about exploring AI for their operations?
John: Start by talking to your current vendors and exploring how they are integrating AI into their platforms. Stay current by reading about the latest developments in AI. Consider bringing in consultants or experts to demonstrate how AI can benefit your specific needs. It’s essential to understand and embrace AI to remain competitive.
Emily: Thank you so much for sharing your insights, John. This discussion on the evolution of automation has been enlightening.
John: Thanks for having me.
The shift from traditional workflow automation to AI-enhanced processes in finance represents a leap toward more intelligent, adaptive, and strategic financial management. AI’s ability to learn and improve over time, predict future trends, and provide deep insights into financial data offers CFOs powerful tools to drive efficiency, compliance, and strategic decision-making. While traditional automation streamlines tasks based on rules and workflow, AI introduces a level of sophistication and analytical depth that transforms finance functions into proactive, strategic pillars of the organization.
The table below highlights the evolution from traditional automation, to AI-led automation.
FINANCE FUNCTION | TRADITIONAL WORKFLOW AUTOMATION | AI-LED AUTOMATION |
Procure to Pay (P2P) | Automates workflow, payment processing, and basic vendor management tasks based on predefined rules. Each invoice needs to be reviewed by a human. | Uses machine learning to improve invoice processing accuracy over time, predicts optimal payment timings for cash flow management, and detects fraudulent invoices through pattern analysis. Enables straight-through processing for 80% of invoices. |
Order to Cash (O2C) | Focuses on automating order entry, credit checks based on static criteria, and straightforward dunning processes for overdue accounts. | Enhances credit scoring with dynamic models, automates personalized dunning campaigns using customer data to improve collections, and predicts future payment behaviors for credit risk management. |
Financial Planning & Analysis (FP&A) | Streamlines data aggregation for budgeting and forecasting, relying on historical data and linear projections. | Utilizes predictive analytics for forward-looking insights, identifies trends and anomalies, and simulates various business conditions for strategic planning, offering adaptable FP&A. |
Expense Management | Simplifies expense report submission and approval processes, enforcing policy compliance through rule-based checks. Each expense needs to be reviewed by a human. | Employs NLP and machine learning for detailed expense report audits, identifies policy violations and fraudulent patterns, and personalizes reporting guidance to reduce errors. Enables straight-through processing for 80% of expenses, and receipts. |
Treasury | Automates cash management and forecasting based on historical cash flow patterns and executes predefined investment strategies. | Leverages advanced analytics for accurate cash flow forecasting, recommends investment strategies by analyzing market trends and the company’s financial health, and adapts to real-time market conditions. |
Mergers & Acquisitions (M&A) | Supports data room management and basic due diligence automation, relying on manual analysis for valuation and integration planning. | Automates in-depth financial, operational, and market data analysis to uncover insights, predicts integration success, identifies synergies and red flags, and optimizes deal structuring based on strategic objectives. |
Tax and Compliance | Facilitates tax calculation, filing, and basic compliance monitoring through rule-based systems. | Automates complex tax planning strategies, monitors compliance with changing regulations using predictive analytics, identifies potential compliance risks, and adapts to new tax laws and regulations for tax filing and reporting |
This detailed look at AI’s impact across various finance processes underscores the need for CFOs to embrace AI technologies, not just for the operational efficiencies they bring but for their potential to fundamentally redefine how finance supports and drives business strategy.