AI is no longer a futuristic concept — it’s here, reshaping financial operations, forecasting, and compliance. Is your team AI-ready?
Manual workflows, from data entry to financial reporting, have long dominated finance making it heavily dependent on extensive human oversight and predefined rules. AI’s potential to augment the field is opening up new and exciting possibilities that enhance accuracy, speed, and decision-making.
Why should you attend?
Finance teams are under immense pressure to move faster, reduce inefficiencies, and make smarter decisions — yet traditional methods have held them back. AI is the game-changer that transforms financial operations from reactive to proactive. Here’s your chance to catch up to the recent advancements and leverage them to your advantage.
- The state of AI in finance – Drivers of adoption and why top-tier finance teams are investing millions in it right now
- AI use cases in finance and accounting – From automation to forecasting to compliance.
- Avoiding the pitfalls of AI – How to navigate compliance, accuracy, security, and many other nightmares.
- Adopting AI – Preparing your team, implementation plan, tools, and best practices.
Who should attend?
Whether you're a CFO, controller, FP&A leader, or finance professional, this session will give you the knowledge and strategies to leverage AI effectively.
Speakers
Bill Dillmeier is a seasoned CFO, founder, and investor with 20+ years of experience in finance. With deep expertise in finance automation, forecasting, and AI-driven analytics, Bill has helped high-growth companies navigate revenue recognition, cash flow forecasting, and pricing transitions.
Webinar summary
Q. What is the topic of today's webinar?
The webinar discusses AI in finance, focusing on how to leverage AI for automation, decision-making, and forecasting. Bill Dill Meer, our guest, will share insights on using AI in finance and how to make your finance office AI-native.
Q. Why is AI in finance such a hot topic right now?
AI is transforming finance by automating manual workflows and enhancing decision-making processes. As the world evolves, AI is becoming a critical tool in finance to improve efficiency, accuracy, and forecasting capabilities.
Q. What are some real-world examples of AI being used in finance?
One example Bill shared is using AI to integrate Salesforce data and predict which opportunities in the sales pipeline are most likely to close. This has improved the accuracy of financial forecasting and cash flow management.
Q. How does AI improve financial forecasting accuracy?
AI allows finance professionals to rely on data-driven insights rather than subjective judgment, which often leads to errors. By using AI tools, Bill was able to increase the accuracy of pipeline forecasts by using AI to analyze Salesforce data in real time.
Q. Is AI a "make or break" moment for finance leaders?
Bill believes AI adoption is crucial for finance leaders. In today’s world, being able to use AI effectively is essential for scalability, lean operations, and maintaining a competitive edge. Those who don’t adopt AI risk falling behind.
Q. How can AI be used to automate revenue recognition and billing?
Bill described a use case where AI helped automate the process of revenue recognition for usage-based pricing. By integrating with platforms like Metabase, AI enables granular tracking of consumption and automates billing, ensuring timely and accurate invoicing.
Q. How does AI help with usage-based pricing in SaaS companies?
AI assists by tracking unit consumption for usage-based pricing, predicting when contracts will expire based on consumption patterns, and automating revenue recognition. This allows for more accurate forecasting and proactive customer engagement, reducing manual effort.
Q. What role does AI play in predicting customer churn?
Bill discussed using AI to predict churn by analyzing usage patterns and customer sentiment. AI can identify early warning signs like inconsistent usage, allowing companies to take proactive measures to retain customers.
Q. Can smaller companies adopt AI for finance?
Yes, smaller companies can adopt AI, but the challenge lies in security and the need for resources. Bill suggests that while smaller companies may not have extensive data science teams, they can start by using off-the-shelf AI tools to begin integrating AI into their finance functions.
Q. What steps should finance leaders take to adopt AI in their functions?
Bill recommends starting small with specific use cases, such as automating accounts payable or billing processes. Finance leaders should focus on one metric or process, understand their current workflows, and explore where AI can be integrated for automation and increased efficiency.
Q. How can AI improve decision-making in finance?
AI can enhance decision-making by analyzing large data sets to identify trends and make predictions. For example, AI can assist in forecasting by providing high, medium, and low scenarios and helping finance leaders understand the financial impact of different business outcomes.
Q. How does AI help with expense management in finance?
AI can automate the analysis of marketing spend, identify profitable channels, and optimize cost allocation. By tracking and analyzing data, AI helps finance leaders decide where to cut costs without affecting profitable areas of the business.
Q. Can AI handle volatile data when predicting outcomes?
Yes, AI can process volatile data by using regression analysis and historical data to predict future trends. However, in new startups, it may be challenging to get enough data to make accurate predictions, and more data points are needed for reliable forecasting.
Q. What tools can finance leaders use to implement AI?
Bill suggested that companies can use established tools like Zenskar for automating billing and revenue recognition, or opt for off-the-shelf tools like Bill.com, which integrates AI to automate financial processes while maintaining security.
Q. How do security concerns impact AI adoption in finance?
Security is a significant concern, especially regarding sensitive data like PII. Bill noted that some companies are building in-house AI models to protect data, while others are using AI in private cloud systems to avoid exposing sensitive customer information.
Q. How can companies balance AI adoption with data security?
To ensure security, companies should focus on anonymizing data, building secure internal models, and complying with regulations like HIPAA. Additionally, using tools that operate within private cloud environments helps mitigate the risks of exposing sensitive financial data.
Q. What is the future of AI in finance?
AI will continue to drive efficiency, automation, and better decision-making in finance. Bill predicts that AI will empower entrepreneurs to build businesses with leaner operations and more precise financial management, especially through the integration of various AI tools.
Q. How can AI be used for strategic financial planning?
AI can support strategic financial planning by providing accurate forecasts, scenario analysis, and insights into which areas of the business need attention. AI tools can also assist in adjusting forecasts based on changing market conditions, helping finance leaders make informed decisions.
Q. What are the key takeaways for finance leaders considering AI adoption?
Finance leaders should start with a clear use case, such as automating billing or revenue recognition, and explore AI tools that align with their needs. It’s important to embrace AI with a curious mindset, begin small, and scale as the organization becomes more comfortable with the technology.
Q. How do you see AI impacting finance teams in the future?
In the future, AI will continue to evolve and automate more finance tasks, reducing manual work and providing real-time data insights. While human oversight will remain essential, AI will significantly enhance the speed and precision of financial decision-making, allowing finance teams to focus more on strategic activities.
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