AI’s influence is burgeoning in the finance and accounting space, transforming intelligent tools into indispensable partners. But for accountants, controllers, analysts, and CFOs eager to capitalize on AI’s potential, these complex systems can feel cryptic. How can you engage in a dialogue with a system that’s based on intricate algorithms?  

For companies implementing AI for the first time, a consultant can arm your team with the knowledge to interact effectively with AI models. But there are also essential best practices that you can empower your team with now as you consider these tools.  

Familiarize Yourself with the AI’s Underpinnings

Literacy and foundational knowledge are key to setting realistic goals and expectations around AI models. Give you and your team the context for how these models work, how they can be used and what capabilities they offer—or don’t offer. 

  • Know the basics: Before diving deep, acquaint yourself with the core principles of the model. Is it a supervised or unsupervised model? What data did it train on? These basic details will provide context for the results.
  • Study the documentation: Many AI tools come with extensive documentation. Spend some time navigating these resources; it will illuminate the model’s design, objectives, and primary functions.

Ask Probing Questions

To maximize the value derived from AI, finance teams must engage in active questioning and exploration. Rather than passively accepting outputs, create a dialogue. Ask precise, tailored questions that compel you and the technology to justify its insights.

  • Be specific: Instead of asking, “How did you calculate this forecast?”, ask “Which indicators most influenced this Q4 forecast?” Precision breeds clarity.
  • Explore scenarios: For FP&A professionals, use AI tools to run different financial scenarios. Pose hypotheticals like, “How would a five percent decrease in annual marketing spend impact sales forecasts?”
  • Challenge the model: If an insight feels counterintuitive, ask the model to justify or elaborate. For instance, if AI suggests an unexpected budgetary allocation, probe its rationale.

Delve Into Model Insights

While AI offers powerful insights, finance leaders should go beyond surface-level results to truly comprehend the intelligence. When presented with model outputs, predictions, and visualizations, take time to dive deeper.

  • Visualize the data: Many AI tools offer visualization capabilities. These can help controllers and accountants better comprehend complex insights, showcasing data patterns and predictions graphically.
  • Break down outputs: CFOs should dissect model outputs to understand the key drivers. If AI suggests a surge in revenue, investigate the contributing factors to better understand the AI model’s recommendations.
  • Seek trends, not just outcomes: Instead of merely focusing on end-results, study the trends and patterns the model identifies. For accountants, this could mean observing transactional patterns to detect anomalies.

Understanding Limitations and Assumptions

Finance and accounting professionals should maintain a critical eye to ensure a model’s outputs are sound. When using AI, remember to scrutinize the underlying data, assumptions and recommendations.

  • Recognize data dependence: AI’s conclusions heavily rely on the training data. If that data has gaps, the AI’s insights might too. Always question the source and quality of the data behind the model.
  • Accept imperfection: No AI model, no matter how advanced, is infallible. CPAs, for example, should cross-check AI’s tax recommendations with current tax laws and their professional judgment.
  • Unearth implicit assumptions: Every AI model operates under certain assumptions. Finance professionals must recognize these assumptions. For instance, a financial projection might assume steady economic conditions, overlooking potential upheavals.

Continuous Learning and Collaboration

The AI landscape is evolving. As new tools emerge, it’s important to continue assessing knowledge gaps and identifying effective ways to work alongside the technology. 

  • Stay updated: Regularly revisit the tools you’re using, understand their updates and adjust your interactions accordingly. Models also need periodic retraining. Ensure that these occur to maximize accuracy.
  • Collaborate, don’t replace: Remember, AI is a tool to augment your capabilities, not replace them. For FP&A professionals, use AI for data-heavy tasks, but rely on your strategic acumen for decision making.

Establishing Mutually Beneficial Human-AI Collaboration

As AI models become staples in the financial toolkit, the ability to interact, question and interpret them will distinguish top-tier professionals. By following these practices, finance practitioners can establish a synergistic relationship with AI, harnessing its capabilities to foster data-driven insights and strategies. 

Does your business need help asking the right questions? Paro’s fractional finance experts can help your business better understand its data and improve data analytics capabilities. With decades of experience, our vetted network of experts can help you get the most value from your tools. 

About the Author

Eli Gill, VP Engineering, Product & AI at Paro

Eli Gill is the Vice President of Engineering, Product, and AI at Paro, an AI-powered marketplace that delivers finance and accounting solutions to businesses through a combination of expert fractional talent, data-driven tools, and guiding insights. Eli has worked in the AI and machine learning field for over 10 years and served for five years as a limited term lecturer in the subjects of machine learning, data science, and AI at Purdue University.