It is high time your business started using AI-powered tools for business forecasting.

Data forecasting has become an integral part of the planning process for business growth and commercial stability. Finance, supply chain, procurement, and operations are the common sectors that use data prediction, and more industries are joining the league.

You can add more power to the historical data used for forecasting by using Artificial Intelligence (AI) technology. Nowadays, many applications use AI and Machine Learning technologies for data prediction.

Before diving deep to learn about top AI-based business forecasting tools, we will look at the definition, types, and use cases for data prediction.

What Is Business Forecasting?

Business forecasting means predicting developments in different aspects of business, such as sales, cost, and profits, using various tools and techniques. These predictions are helpful when it comes to building informed strategies.

What Is Business Forecasting

By forecasting, companies can identify the problems during any organizational investigation. This process uses different quantitative or qualitative models to analyze the collected historical data.

After the analysis, the companies get predictions that they can use for demand planning, marketing, financial operations, and even user experience. There is a difference between the forecast data and actual performance. Using the deviation, you can improve the accuracy of future predictions.

Major Types of Business Forecasting

While there are different types of data forecasting or predictions, let us discuss two common types below:

Demand Forecasting

Demand is an essential part of every business. Making forecasts on resource demand, including raw material, inventory, and workforce, helps organizations plan accurately to meet the requirements well ahead of time. Thus, companies can fulfill internal and external demands.

Growth Forecasting

Growth Forecasting

Predicting a company's growth model (sales/revenue) is also crucial for planning and strategizing. With data on future growth, organizations can make accurate decisions on budget, resource allocation, marketing strategy, and business patterns, depending on metrics like inventory location and customer subscription cancellation.

AI in Data Predictions and Business Forecasting: Use Cases

Here are some industry-based use cases of AI forecasting:

1. Finance

Finance companies can predict fraudulent actions using AI-based forecasting and take action against them. They can also predict property prices from AI tools by considering location and historical pricing.

2. Government

Government agencies can use AI forecasting to modernize and digitize their processes, mitigate risks of cyberattacks on national databases, cost control, increase employee efficiency, database maintenance, and improve responses from lawmakers.

3. Manufacturing

Manufacturers use AI forecast to reduce production downtime, boost efficiency, and improve customer satisfaction. The predictions can also be used for process design, maintenance, supply chain optimization, etc.

4. Healthcare

Healthcare Data Forecasting

Organizations providing healthcare services often face challenges while implementing new technologies. Healthcare organizations can smoothly implement new technologies and streamline their existing processes with AI business predictions.

5. Insurance

For insurance companies, tasks like risk management and customer satisfaction can be predicted with AI. Fraud detection, optimized marketing, customer expansion, underwriting, personal rate management are other sectors where insurance organizations can use forecasting.

6. Sales

AI data forecasting informs sales companies about the leads with the maximum chance of a conversion. It also helps by providing data such as willingness to pay and the chance of canceling membership.

7. Telecommunication

Telecom companies use business forecasting with AI tools for building customer relationships and increasing user satisfaction. Data prediction is also useful to retain loyal customers and eliminate fraud.

8. Product

Product Data Forecasting

AI is also useful for determining product prices, comparing competitor data. It also predicts the chance of accidents during product procurement and supply so you can stay prepared with insurance.

9. Operations

Companies dealing with operations can get a credit risk score and insurance costs for individuals using AI. Also, they can point out employees who might leave the organization soon.

Now that you know the possibilities of AI-powered business forecasting, it is time to learn which tools are available to assist you. Check out the following list of AI forecasting tools you should use for business prediction:

H2O AI Cloud

H2O AI Cloud is a top choice for businesses that want to build AI models and applications. This end-to-end platform makes rapid AI model development possible in the cloud and on-premise.

It comes with a comprehensive autoML feature that ensures accurate and transparent data prediction rapidly. This platform allows you to come up with new business ideas to resolve critical business issues by using its predictive results.

Business organizations can deploy it in any environment and enjoy the benefit of using several modeling methods for all kinds of data. Using autoML, you can develop effective models or do many other tasks throughout the lifecycle.

H2O AI Cloud offers a unique combination of open-source and proprietary algorithms and helps you perform data drift detection in real-time. While providing you with real-time business forecasting, the tool also makes sure that you get the optimum CPU and GPU performance.

With the help of its ML Interpretability toolkit, you can perform time series analysis for business forecasting. Moreover, for petabytes, the tool uses distributed Machine Learning.

Neptune

Neptune is an experiment management tool that lets you track Machine Learning results. ML researchers and engineers can become more productive by using its single dashboard for decreased context switching.

Instead of arranging unnecessary meetings to share the AI forecasting results, logs, or even dashboards, companies can share them with colleagues through a simple link. As the dashboard is built on the ML model, you can easily find any data from there.

The same platform lets you compare your models and debug them. During model building and experimenting with them, you can control the process. Companies can learn about the source dataset and the parameters of each model.

Moreover, Neptune keeps all ML metadata, including charts and metrics, in one place. It offers integration with 30+ popular libraries of Machine Learning and IDE. Hence, businesses get the most out of the apps they use regularly.

DataRobot

DataRobot uses Augmented Intelligence technology to bring intelligence revolution to different industries. It utilizes machine learning models that need low code to generate real-time predictions.

By applying different AI features of this tool, businesses can facilitate data-driven and impactful decision-making. It is possible to align the AI with your company culture so that you receive reliable data predictions.

This platform lets you define rules, policies, and controls for production models. Moreover, using its automated time series, you can generate, deploy, and maintain effective forecasts for your company. This advanced business forecasting model builds resiliency and reduces uncertainty while delivering predictions at scale.

Obviously AI

Obviously AI is a no-code platform that can predict revenue and business outcomes using Artificial Intelligence. Companies can modify their supply chain and create tailored marketing strategies using business forecasting data.

Your team does not have to learn to code or spend months building AI models if they are using Obviously AI. You can readily integrate this tool with your favorite data sources, including Google Drive, Salesforce, Dropbox, Evernote, Hubspot, and CSV files.

As you choose the prediction category, Obviously AI will come up with the forecasts by using AI technology. With virtually unbreakable AES-256 encryption, your data remains fully secure. You can also use what-if scenarios to get predictions and understand the influencing factors.

On this platform, two types of AI forecasting are possible. The first one is AutoML, where you can effortlessly build AI models out of historical data for real-time data predictions. The second one is Time Series which uses the least possible data for time-bound predictions about important business events to a specific date.

Even if your data is not compatible with Machine learning technology, you can use the Data Dialog feature to modify the data and convert them in Machine Learning supported format.

After churning out the data forecasting model, companies can share it with the public or the whole team. The Low-code API is also available for real-time business forecasting from your own app.

Futrli

If you want to get quick business forecasting on business trends, revenue, sales, tax, operations, and staff, Futrli is here for you. With accurate predictions, it helps you with growth planning, future cash flow, and operations policy. The tool mainly caters to the needs of global accounting firms and accounting businesses.

Futrli Predict analyzes every business transaction of your company to make an informed forecast. It supports three types of predictions: freestyle forecasts, units forecasts, and repeating forecasts. The prediction assistant of this application can explain the reason behind each prediction.

In addition, the tool also generates scenarios that tell you what will and will not happen. Therefore, you can stay prepared for the best and worst in your business. This baseline forecast will get generated every day with the updated data.

Futrli also supports hot-linking Google Sheets templates with Futrli Predict for complicated predictions like payrolls. You can also toggle off the tool prediction anytime and add your data.

The tool also supports direct integration with Xero and Quickbooks. Post integration, Futrli will import data from these apps every 24 hours.

Pecan

Pecan generates predictive analytics data for operations and sales teams. Thus companies can come up with solutions to their business problems. Using its BI-friendly data, companies can get better sales and revenue while offering an optimized user experience to their customers.

From resource and production planning to distribution and packaging, from customer acquisition to retention—this platform assists you in designing future-ready strategies on metrics that are crucial in your industry.

Use Pecan, and you do not have to hire additional data scientists for business forecasting. Your existing team of analysts can make the most of the automated processes of this platform to develop AI-powered sophisticated predictive models. This tool also helps you cut the cost of code model building by the data scientists from the beginning.

Whether it is to discover unforeseen opportunities or overcome challenges of transforming conditions, Pecan utilizes the data the right way. As a result, you will notice a significant boost in your KPIs only within two weeks due to accurate AI forecasting.

Qlik Sense

Qlik Sense empowers businesses with active analytics so people of any skill or expertise level can make informed decisions. It offers you the best-in-class data analytics experience at a broader scale.

This business forecasting platform goes beyond generic dashboards and query-based analytics with superfast calculations, contextual predictions, and an interactive user interface.

Qlik offers AI-driven augmented analytics that people can leverage to improve human-centric analysis. Now, its features like AI-generated insights, natural language interaction, and AutoML predictions assist you in making better business decisions while focusing on your business.

In addition, this tool broadens the data model reach and provides easily accessible interactive forecasts. Its Insight Advisor feature automatically generates advanced insights and helps you in the processes of preparing data and creating analytics.

AutoML automatically generates models and tests what-if scenarios to come up with forecasts through a code-free process. You can also publish the data on different cloud platforms, including Qlik Sense.

Dataiku

Whether you belong to a code-driven technical community or a low/no-code business, Dataiku is here to help you make data-driven and AI-powered decisions. There is no need to perform data cleansing manually as this tool can analyze the data more quickly and efficiently to suggest key transformations.

It facilitates 109 types of data transformation, including aggregating time series, geospatial data transformation, aggregation across various sources, etc. After building a data pipeline in SQL, you can schedule it for calculations. Its interactive GUI lets you access the necessary data with a few clicks.

Using Dataiku AutoML, teams can create high-class data models with numerous algorithms and parameters. Besides having 32 core algorithms, Dataiku supports popular ML engines—Python, H2O, Spark, and TensorFlow.

The business forecasting platform lets you explore the visual models and understand key metrics such as stats, errors, and insights. Thus, you will realize the rationale behind every prediction and create your strategy accordingly.

On Dataiku, companies can develop and visualize different types of analysis. These include principal component analysis, univariate analysis, bivariate analysis, correlations analysis, and statistical tests.

Conclusion 👩‍🏫

The business world is getting more competitive each day, and every company needs to put in its best efforts to stay in the race.

Business forecasting is an approach that helps businesses get an advantage over others. AI forecasting makes the whole process sophisticated and cuts manual effort.

We discussed some of the best AI-powered data prediction tools in this article that businesses of all sizes can use for forecasting.

Using these solutions, you can have a better understanding of future scenarios generated from the relevant historical data.

If you are interested in the development and think AI could be a good option, read about AI-powered code completion tools.