How AI writing code will change Finance (and what you need to know)
There is a lot of buzz about what AI can and cannot do. But if there’s one thing that’s undeniable, it is that AI is exceptional at writing code. Until recently, working with code meant either learning a programming language or relying heavily on IT and data teams. But now, thanks to generative AI, you only need to understand your business logic. AI handles the coding. This is about to change how finance and accounting teams operate—dramatically.
This matters because programming languages like Python and SQL are powerful tools, especially compared to Excel or Google Sheets. They’re built for speed, efficiency, and accuracy at scale. A few quick examples:
Processing Huge CSV Files: Python can easily process millions of rows of data in seconds, whereas Excel often freezes or slows dramatically.
Automating Manual Tasks: Instead of manually cleaning data row by row, Python scripts can automate standardizing formats, handling missing data, and removing duplicates instantly.
Generating Reports and Reconciliations: SQL queries directly pull data from different sources and automate reports or reconciliations, eliminating repetitive monthly tasks.
Joining Data from Multiple Systems: SQL quickly combines data from your CRM, ERP, banking, and billing systems, simplifying reconciliations and reporting.
Forecasting and Modeling: Python provides access to advanced analytics and machine learning, enabling finance teams to create sophisticated forecasts and scenario analyses quickly.
How to Get Started
1. Test Everything Thoroughly
Just like you'd never trust an Excel workbook without checking formulas first, you shouldn't use new code without testing. Create a dedicated test environment where you run AI-generated code on historical data. Verify results carefully—reconcile any differences before running it live in your production environment.
2. Invest in Your Finance Data Infrastructure
The full benefit of coding comes when you have easy access to your finance data. Invest in tools like Fivetran, Airbyte, or other data connectors to move data from sources (QuickBooks, Netsuite, Salesforce, Stripe, banks) into a central data warehouse (Snowflake, BigQuery, Redshift). Once centralized, you can automate complex processes using SQL or Python.
3. Start Small and Local
Getting started doesn’t require a big investment. You can run Python scripts directly on your computer—just like working on a local Excel file. Cursor, VS Code and ChatGPT itself are all helpful tools for writing and executing code. AI tools can help you write, debug, and explain the code clearly, in simple language.
What This Means for You
AI writing code doesn’t replace your role—it elevates it. Your job shifts from repetitive spreadsheet management to defining logic clearly, interpreting results, and optimizing workflows. AI does the heavy lifting; you ensure the business logic is sound.
If you’ve ever struggled with the limits of spreadsheets or wished you could automate routine tasks without becoming a developer, now’s your chance. AI puts powerful, scalable tools in your hands—no coding skills required.
If you want to partner with someone to help identify processes that can be replaced or accelerated by code, schedule an appointment with Lumera for a deep dive into your specific needs and use cases.
