How AI Can Help Forecast Your Budget — Tips and Tricks You Need to Know

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If you're anything like me, business forecasting spreadsheets play too much of a role in your finances. I've got spreadsheets for almost everything, but there's a better way. You can use AI in budgeting and forecasting, and it's not as overwhelming as you think. However, there are some precautions you should take.

I wanted to learn everything I could about budgeting and forecasting financials and, importantly, bring AI into that mix to see if it could save time and enhance my view of my business. To put this article together, I spoke to people using AI in budgeting and forecasting and asked them for tips and examples, too.

Table of Contents

• AI Budgeting and Forecasting Benefits
• How AI is Used in Budgeting and Forecasting
• How to Implement AI in Forecasting

AI Budgeting and Forecasting Benefits

Efficiency

I've written several articles on AI now, and efficiency is one area where AI seems most beneficial. I wasn't surprised when my research found that efficiency is a major benefit of using AI in budgeting and forecasting.

When researching the benefits of AI, eight different people mentioned the role AI plays in efficiently managing budgets and forecasting.

Connor Gillivan, Owner and CMO at AccountsBalance, has extensive experience in this space. In his bookkeeping company, Gillivan uses AI to analyze data related to budgeting and forecasting in real-time.

He says, "We've integrated AI tools to analyze cash flow, sales data, and expenses in real time. For instance, AI flags potential cash flow issues early by comparing historical spending patterns with current income, helping us adjust budgets more efficiently. These tools also project future revenue based on customer trends and market conditions, which takes the guesswork out of planning."

Data analysis was a manual task assigned to humans, who needed time to gather, analyze, and spot patterns and trends. With AI, this work can be done in minutes. Plus, AI can continuously analyze data and alert humans when changes occur.

We know that AI is efficient from HubSpot surveys. As many as 81% of salespeople spend less time on manual tasks thanks to AI, and 78% say that AI helps them work efficiently.

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Accuracy and Reliability

I spoke to many experts who credited AI with improving the accuracy of data analysis and forecasting. In fact, 17 experts mentioned accuracy 27 times.

Dávid Breitenbach, chief commercial officer at PatentRenewal, measured AI's impact on forecasting accuracy.

He said, "AI assists in identifying patterns of seasonality in our business, allowing us to better prepare for fluctuations in demand. This ensures, in the long run, that our budget aligns with periods of high and low sales activity, preventing financial surprises. Overall, AI has increased our forecasting accuracy by 25%, which has been key in optimizing our financial strategy, reducing waste, and improving our bottom line."

It's important to know that you must look after your AI and data to get the most accurate results. Michael Abramov, CEO at Keylabs, discusses the importance of model accuracy and offers tips on improving it. In his article, Abramov notes that model accuracy is fundamental for financial services and invaluable for risk assessment in the financial industry.

Abramov's tips for maintaining model accuracy include:

• Data preprocessing. This is important for accurate AI and includes cleaning, transforming, and preparing data to improve quality. With AI, you get out what you put in.
• Feature engineering. The practice of creating new or enhanced features to improve a model's ability to identify patterns and relationships. For example, upon receiving your data analysis, you might add new mathematical functions to better represent the relationships between variables.
• Hyperparameter optimization. The method of adjusting parameters to better accuracy.

Data-Driven Decision Making

Dávid Breitenbach, mentioned above, also credits AI with helping make data-driven decisions. Like efficiency and accuracy benefits, data-driven decisions are a benefit that I'm finding commonly associated with AI.

Breitenbach said, "We started experimenting with AI tools to enhance our sales forecasting and budgeting. We developed our processes, and now, these tools help us to make smarter, data-driven decisions. For example, analyzing historical sales data, customer behavior, and market trends improves the accuracy of our sales forecasts."

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Eric Colson first shared the above screenshot in this Harvard Business Review article. In it, Colson provides a process for making business decisions using AI. Importantly, Colson includes a human later in the analysis.

Big data is inputted into the AI, which analyzes the data and provides possible actions. These findings are then judged by humans in conjunction with other non-digital data (something AI simply cannot do). Finally, with all of the above, a business decision is made.

I like how Colson is looping in the all-important human in the process. While AI is amazing, it will never replace human insight.

Colson says it best when he says, "The key is that humans are not interfacing directly with data but rather with the possibilities produced by AI's processing of the data. Values, strategy, and culture are [our way of reconciling] decisions with objective rationality. This is best done explicitly and fully informed. By leveraging AI and humans, we can make better decisions than using either alone."

How AI is Used in Budgeting and Forecasting

Now that we know AI's benefits in budgeting and forecasting, let's look at specific use cases.

Time Savings

Russell Rosario is a CPA, CFO, and software engineer who focuses on AI. At his financial strategy consultancy, Rosario uses AI to save time, speed up processes, and reduce errors. Rosario shared some excellent use cases, including saving time and reporting.

Rosario says, "AI speeds up the process and reduces errors for budgeting. I worked with a startup that spent weeks on manual data entry and couldn't keep up with rapid growth. We implemented an automated system that updated budgets in real time as orders came in. The founders now check budgets daily and make adjustments, boosting cash flow visibility."

Reporting

Rosario also saves eight hours per week by automating his reports. He says, "AI handles routine reporting, freeing us to advise clients. AI provides insights impossible alone while we guide complex decisions beyond AI.

"AI handles routine reporting, freeing teams to focus on strategy. A consulting firm I advised was bogged down producing monthly reports, costing 10 hours per week. We set up dynamic dashboards that pulled data from their systems, saving 8 hours weekly. They reinvested that time in business development, growing revenue by 22% year over year."

Improving Forecast Accuracy

Mark McDermott, CEO and Co-Founder at ScreenCloud uses AI to improve forecast accuracy.

He says, "We use AI to identify hidden seasonality patterns that go beyond typical calendar cycles, helping us forecast spikes in unexpected months."

For example, AI alerted McDermott's team to a surge in manufacturing sign-ups during February - something they wouldn't have caught without it. This helped the team allocate sales efforts and budgets precisely where they'll have the most impact.

"We rely on Salesforce Einstein AI for real time forecasting, giving us up-to-the-minute projections on revenue, which we can adjust mid-quarter if needed. Since adopting it, we've improved forecast accuracy by nearly 18%, which has helped us hit revenue targets more consistently," McDermott says.

In HubSpot's CRM, forecasting is made easy. As part of Sales Hub, your forecast data is delivered directly to you through CRM. You can view your sales forecasts, what's forecast to come in, look at categorization, and even see reports showing where all your prospects are. This will help you know where to invest your efforts to help meet objectives.

If you need support with Hubspot's forecasting analytics, there are lessons on this and sales forecasting.

Demand Forecasting

One specific example of how AI significantly impacted sales forecasts for Peter Hunt, director and physiotherapist at The Alignment Studio, was when he expanded his pilates and wellness services.

Hunt says, "By analyzing the data from our physiotherapy clients, AI helped us identify a growing demand for these additional services, leading to a 20% increase in Pilates bookings within six months."

With over 30 years of experience in private practice and sports-physio clinics, Hunt says his background allowed him to implement these tools strategically. This ensures that AI solutions complement existing processes rather than overwhelming the team.

"AI has not only improved our financial forecasting but also empowered us to make data-driven decisions, supporting sustainable business growth," Hunt says.

Hunt's use case perfectly represents how AI and human insights have been used together to make data-driven business decisions. In this case, Hunt is using AI in demand forecasting, and the insights give him the data he needs to decide whether to open a new service.

How to Implement AI in Forecasting

Hopefully, this article has made you curious about implementing AI into your budgeting and forecasting. I asked experts to share their best tips for implementation, and here's what they said.

Start small.

Sophie Marasco, Founder of Thanks A Bunch Florist, recommends starting small when implementing AI.

Marasco uses AI in budgeting and forecasting in her flower shop to manage financials and forecast future sales. She says, "AI-powered platforms analyze our sales history and predict future cash flow based on various factors, such as seasonal trends and customer behaviors. This gives us a clearer picture of how much to budget for things like supplies, marketing, and labor."

When starting with AI, Marasco says, "Start small, maybe with an AI-driven accounting tool, and slowly incorporate more advanced analytics as you become comfortable. This gradual integration has worked well for us, and the data-backed decisions have made our financial operations more resilient."

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What I like about this: From researching AI previously and in other verticals, I know the benefit of integrated AI simply and on a smaller scale. For example, 74% of marketing professionals use AI more if integrated with existing tools. Likely, the mental leap and process adaptation are much smaller if you're already using and enhancing a tool with AI. As Marasco said, start with your accounting tool and see what you can enhance with AI.

Don't skip human insights.

I've mentioned this above, but this tip is highly important. When implementing AI, you must remember that it isn't a complete replacement for human insights. AI is a tool that will enhance the budgeting and forecasting process and help humans, not replace them.

Russell Rosario shared his insights on how AI saves time above, but he also warns that human judgment is still vital. The key, Rosario says, is "Using AI for routine tasks so experts can focus on high-value work. AI improves decision-making by providing data-driven insights. With the right tools and guidance, any business can leverage AI to gain a competitive advantage."

Dávid Breitenbach was another key contributor to this article. He provided insights on accuracy and data-driven decision-making and stressed the importance of human oversight.

He said, "While AI can provide predictive analytics and trends, our team reviews these insights regularly to adjust for any unforeseen factors like changes in the market or internal priorities. This hybrid approach we developed ensures we stay flexible and responsive while leveraging the power of AI."

What I like about this: We know from the above that human insights are key, but I think having this message at the forefront of your internal processes and dialogue around AI and human collaboration is important. I'd like to think it brings comfort to employees who may be concerned about their jobs with the integration of AI.

Regularly expand data.

Hayley Kirkby, Wholesale Sales Manager at Connect Vending, has found success in adding regular data.

Kirkby says, "[adding] seasonal trends or shifts in customer behavior really helped us set more accurate goals, manage resources better, and ultimately be more efficient at hitting our targets. This is the most important thing to remember: AI is only as good as the data fed to it."

What I like about this: This tip is mentioned above and is frequently mentioned when asked about best practices for implementing AI. I think it's important to mention this as data quality could be the difference between a good experience with AI, which brings trust, or a poor one. It would be a shame to discount AI when the issue is the data.

Bring AI Into Your Budgeting and Forecasting

I had some apprehensions about how AI would be a success in budgeting and forecasting. I was pleasantly surprised at the confidence experts expressed when discussing AI's benefits and use cases in budgeting and forecasting.

Hopefully, you've read this article and are intrigued to try AI. Give it a go! Make sure you implement these tips to make your AI journey a success.

Topics: Artificial Intelligence

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