How to Think About AI Adoption: A Practical Framework for Finance Teams

AI is transforming the way we work—but for many teams, figuring out how to adopt it can feel overwhelming. “Just try AI” is easy advice to give, but hard to act on. With countless tools, new features, and emerging platforms, where do you even begin?

At Blue Onion, we’ve been thinking a lot about how to make AI adoption feel more approachable, especially for finance teams. We’ve developed a framework to help you navigate the AI landscape in a structured, practical way. Whether you’re just starting out or exploring advanced use cases, this model breaks AI adoption into four clear “buckets.”

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Bucket 1: Use AI in the Tools You Already Have

The easiest and most approachable place to start is with the tools you already use daily. Most modern software is quietly integrating AI behind the scenes—helping you work faster, reduce errors, and get smarter results with little to no learning curve.

There are two ways to tap into this:

• AI-powered products: Tools like Gmail, Excel, or your accounting platform are already using AI to enhance performance. You don’t need to do anything special—just benefit from it.
  
  
• AI add-ons and enhancements: Many of these platforms now offer lightweight AI features like autocomplete, smart suggestions, or email drafting (think: Gmail’s “Help Me Write”). These are designed to reduce friction in your daily workflows and are a great way to experiment with AI in a low-risk way.
  
  

Bottom line: You don’t have to be an AI expert. Just try using the new features within tools you already know and love.

Bucket 2: Experiment with New Tools That Solve Real Problems

The second bucket is all about trying new things. There’s a wave of AI-native apps focused on productivity, content generation, research, and more. These tools can unlock real efficiencies if you’re willing to explore a bit.

At Blue Onion, we encourage our team to:

• Try new tools that seem relevant
• Take advantage of free trials or low-cost subscriptions
• Share what worked and what didn’t
  
  

Many AI apps are priced affordably (often under $30/month), so there’s minimal risk. More importantly, by encouraging team-wide experimentation, you create a culture of curiosity and continuous improvement.

We recommend setting aside a small budget specifically for AI exploration. Ask team members to report back with feedback:

• What problem did it solve?
• Was it worth it?
• Would you recommend it to others?
  
  

Bucket 3: Customize AI for Your Workflows

Once you’ve dipped your toes in, you might find yourself wanting more tailored solutions. That’s where custom GPTs and prompt-based tools come in.

You can now create your own GPT-powered assistants to support specific use cases—like summarizing financial reports, generating insights from dummy data, or prepping client notes. Tools like ChatGPT make this easier than ever.

A great hack? Ask GPT to help you build itself. You can input a goal like:

“Help me create a custom GPT that summarizes Excel data into a weekly report.”
GPT will walk you through the process, ask for inputs, and generate the instructions you need.

This stage is more freeform and exploratory, but it doesn’t require coding skills—just clear thinking about your workflow and what you want the AI to do.

Bucket 4: Build Custom AI Applications (for the Technical Folks)

Finally, for teams with technical resources, you may reach a point where building your own AI-powered applications makes sense. This could include:

• Automating internal workflows
• Creating integrations across multiple systems
• Solving high-volume, repeatable pain points
  
  

This is where the classic “build vs. buy” question comes into play. If a problem is unique enough—and the solution critical enough—building a custom tool may deliver outsized ROI.

You don’t have to go it alone. Even just documenting your ideal workflow and partnering with an engineer can be enough to get started.

Putting It All Together: The Path to AI Adoption

To recap, here’s how we think about the journey:

1. Use AI in tools you already have – Leverage what’s already there.
2. Experiment with new AI apps – Low lift, high potential.
3. Customize your AI experience – Build GPTs and prompts that fit your workflow.
4. Build your own apps – For advanced, high-impact use cases.
   

No matter where you start, the key is to stay curious and open. AI isn’t about being perfect or knowing everything—it’s about experimenting, learning, and finding what works for you and your team.

At Blue Onion, We Build AI Into the Tools You Already Use

You don’t have to be a machine learning expert to benefit from AI. Our platform automates finance workflows, handles data cleanup behind the scenes, and makes your team more efficient—without needing to learn a new system.

We’re doing the AI heavy lifting, so you can focus on what matters.

Ready to see how we’re doing it? Schedule a demo or reach out to learn more.

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