AI Is Only as Good as Your Data
For anyone who has ventured into the world of AI, you have quickly learned that AI relies on data sources to generate its output. In my household, my wife was the first to embrace a practical use for AI. She is using it to track her “macros” as they apply to her diet. With AI, she can upload a recipe, take a picture of the nutrition panel of an ingredient, take a picture of everything her plate, or simply type in the name and quantity of what she is eating. She quickly learned that AI relies on data sources that may not be accurate. It is not uncommon for her to argue with the AI until she gets the correct results (so it’s not just me that she argues with).
If you are using AI to make financial related decisions, QuickBooks (online or desktop) is often the source for financial truth. If QuickBooks data is messy, AI-driven forecasts and insights will be equally messy and unreliable. Some of the common QuickBooks data issues we see frequently include incorrect workflows, improper usage of the chart of accounts and simple misclassification of expense or revenue items. A big problem is backdated or manually entered transactions, and equally concerning can be a lack of job or class tracking and missing links between invoices, payments, and jobs.
AI models that use QBO data for cash flow forecasting, profitability analysis, or problem detection depend on clean, consistent financial data. Without it, predictions become little more than guesswork.
Operational Data Must Match Financial Reality
Often a QuickBooks addon is used to run operations (addon applications like Acctivate, Results Software, etc.), and in these cases it is necessary to capture rich operational data—inventory control, job duration, labor, scheduling, outstanding purchase and sales orders, and detailed customer history, that is not reflected in QuickBooks. This data is incredibly valuable for AI, but only when it aligns with financial outcomes and what goes into the accounting.
Alignment comes in a variety of areas and means that things in the operational system are integrated and mapped properly to the accounting system. What we often find is situations where the mappings between the addon and QuickBooks are set up incorrectly. Resulting in incorrect application to the General Ledger.
When operational data doesn’t reconcile with financial data, AI cannot possibly assess job profitability, technician efficiency, or customer lifetime value with any level of accuracy.
The AI Layer Requires Clean Inputs
Microsoft Fabric can act as a central platform that brings financial and operational data together for analytics and AI. Fabric can unify data, but it cannot correct poor definitions or broken processes on its own.
For AI to be effective, businesses need to ensure that standardized definitions for customers, jobs, revenue, and costs are used consistently, and that there are clean dimensional models for AI training as well as reporting.
The data pipelines from source systems must be reliable so that the data will flow consistently, and the business logic applied should clearly document the data transformations. Implementations should be monitored and tested to catch any data issues early, because AI will only amplify what you feed into it – good or bad.
Why Data Quality Matters More for SMB AI
Small Business Owners are becoming increasingly reliant on AI in their applications. Where larger enterprises may employ data analysis and reporting teams, smaller businesses must rely more on the technology to help them with reporting and decision support for daily operations. AI can help identify things like when to hire or schedule technicians, how much inventory to stock, which customers are most profitable or where cash flow risks exist
However, if AI recommendations are based on unreliable data, the consequences are immediate and expensive. High-quality data reduces risk and increases confidence in automated insights.
How Mendelson Consulting Helps SMBs Build AI-Ready Systems
If you’re exploring AI and unsure whether your data is ready, that’s where to start, let Mendelson Consulting help your business improve process effectiveness, accounting integration, and overall data quality so you’re ready to turn valuable information into real, useful business insight.
