How to Use AI in Finance: Tips and Best Practices

The Strategic Advantage of Using AI in Finance

Your finance expertise, combined with knowing how to use AI in finance strategically, creates an unbeatable advantage in today’s hyper-competitive market. As artificial intelligence reshapes the finance profession, the key to success is implementing AI tools thoughtfully and systematically. 

Here are seven guidelines to guide you in how to get the most out of using AI in finance. Each method helps you apply your finance skills in new ways, turning AI’s possibilities into real-world results.

How to Use AI in Finance - Using Generative AI in the Real World
Source: CFI’s AI-Enhanced Financial Analysis course

Key Highlights

  • Learning how to use AI in finance starts with clean data and clear communication — everything else builds from this foundation.
  • Build confidence in AI by starting small, maintaining oversight, and ensuring every process remains explainable.
  • Use AI to amplify your financial expertise rather than replace it, focusing on enhanced decision-making rather than full automation.

1. Prepare Your Data for AI

Success with using AI in finance starts with your data. Think of data preparation like organizing your workspace. When your data is clean and well-organized, your AI tools can process it more accurately and efficiently.

Strip away unnecessary formatting from your datasets and save them in machine-readable formats like CSV files or basic Excel spreadsheets. Your column headers should be crystal clear, and your data structure needs to stay consistent throughout. 

💡 Quick Tip🔑 Why It Matters:
• Clear unnecessary formatting from datasets. • Clean, organized data enhances the accuracy and efficiency of AI analysis.
• Save data in machine-readable formats like CSV files or unformatted Excel files.
• Clearly label all columns and ensure consistent data structure.

2. Take Small First Steps, Then Scale Up

Jumping straight into complex AI implementations can feel overwhelming. Instead, begin your AI journey with focused, manageable projects. Take expense report automation, for example. It’s a straightforward process that can deliver immediate value while helping you build confidence with AI tools.

These small wins do more than just improve efficiency they help build trust in AI solutions across your organization. As you grow more comfortable with AI-driven processes, you can gradually tackle more complex applications.

💡 Quick Tip🔑 Why It Matters:
• Use AI narrowly focused tasks, such as automating expense reports, before scaling up to more complex applications.• Building confidence with smaller wins fosters buy-in and ensures smooth AI adoption.

3. Strengthen Your AI Prompting Skills

Working with AI requires a unique communication approach. Think of AI models as brilliant but inexperienced interns they’re incredibly capable but need clear, structured guidance to deliver their best work.

When crafting prompts for your AI tools, be specific and detailed in your instructions. Learn how to use techniques like Chain-of-Thought (CoT) prompting. The CoT approach breaks down large requests into manageable steps that guide AI tools like ChatGPT step-by-step. 

CoT prompting works particularly well for complex analytical tasks like comparative or trend analysis. And always review the outputs carefully.

The quality of your AI-generated insights directly depends on how well you communicate your needs to the system.

💡 Quick Tip🔑 Why It Matters:
• Treat AI models like a bright but inexperienced intern.• Well-crafted prompts improve the quality of AI-generated insights.
• Provide clear, structured instructions and review outputs carefully.

4. Balance AI with Human Oversight

The Role of Human Oversight in AI-Driven Decisions
Source: CFI’s Introduction to AI in Finance course

While AI brings powerful capabilities to financial operations, it works best as a complement to human expertise rather than a replacement. Keep humans in the loop for critical decisions and ensure you can explain every step of your AI-driven processes.

This balance is crucial. You should maintain final decision-making authority while leveraging AI to enhance analysis and streamline routine tasks. Understanding and being able to explain how your AI solutions work builds confidence and maintains accountability throughout your organization.

💡 Quick Tip🔑 Why It Matters:
• Always retain final authority over critical financial decisions.• A human-in-the-loop maintains accountability and builds trust in AI-driven processes.
• Use AI to enhance your expertise, not replace your professional judgment.
• Maintain the ability to explain every step of your AI-driven processes clearly.

5. Build Fair and Unbiased AI Systems

AI systems can inadvertently perpetuate biases present in their training data. Regular testing of your AI models for potential biases is essential, especially in finance where decisions can significantly impact people’s lives.

Use diverse datasets when training your models, and continuously monitor outputs for signs of bias. This vigilance is particularly important in areas like lending and hiring, where fairness and inclusivity are paramount.

💡 Quick Tip🔑 Why It Matters:
• Regularly test AI models for biases and use diverse datasets to train them.• Mitigating bias ensures fairness and inclusivity in lending, hiring, and other financial decisions.

6. Embracing Transparency with Explainable AI

In finance, the ability to explain how decisions are made is a best practice and often a regulatory requirement. Invest in AI tools that provide clear insights into their decision-making processes.

Explainable AI helps build trust with stakeholders and supports compliance efforts. This transparency becomes particularly valuable in high-stakes scenarios like credit scoring, where understanding the factors behind decisions is crucial.

💡 Quick Tip🔑 Why It Matters:
• Invest in tools that provide transparent insights into how models generate outputs.• Explainable AI builds trust and supports regulatory compliance, especially in high-stakes areas like credit scoring.

As AI technology rapidly advances, keep up to date on new developments in language models and automation. Make it a priority to stay informed about these advancements.

Following AI trends helps you identify new opportunities to improve your financial operations and maintain a competitive edge. Subscribe to reputable AI news sources, attend industry conferences, and engage with AI communities to keep your knowledge current.

💡 Quick Tip🔑 Why It Matters:
• Keep up with emerging advancements with language models and automation.• Staying informed helps you adapt quickly to new tools and maintain a competitive edge.

Take the Next Step: Master AI in Finance

When you understand how to use AI in finance, you gain a competitive advantage. Apply the seven guidelines outlined above to successfully integrate AI into your finance tasks. Take it step by step, learn from each experience, and continue to refine your approach as AI technology evolves. 

Looking to enhance your finance expertise with cutting-edge AI tools? CFI’s AI for Finance Specialization equips you with practical AI skills to drive smarter, data-driven decisions in finance.

Explore the AI for Finance Specialization!

Additional Resources

AI and Financial Statement Analysis

Revolutionizing Risk Assessment with Generative AI

AI for Excel Formulas

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