AI for Business: Transforming the Corporate Landscape

Key takeaways

AI for business refers to artificial intelligence solutions that specialize in improving business processes, such as automating repetitive tasks. 

• Organizations that offer AI solutions include IBM, SAP, Microsoft, OpenAI, Salesforce, and HubSpot.

• Three careers that use AI business tools are business intelligence analyst, machine learning engineer, and big data analyst.

• You can use AI in your business for sentiment analysis, fraud detection, supply chain optimization, process optimization, and to automate customer service. 

Explore how companies apply AI technology for business purposes, including real-world examples of AI in action and potential careers in AI. If you’re ready to enhance your understanding of how to apply AI to business, enroll in the AI for Business Specialization from the University of Pennsylvania. In as little as four weeks, you can learn about responsible AI, data strategy, machine learning methods, AI product strategy, and more. 

What is AI for business?

AI for business describes artificial intelligence solutions that specialize in making business processes more efficient. Companies and organizations can use AI to automate repetitive tasks, gain actionable insights, reduce human error, and explore ways of innovating their industries. Depending on your industry, your business might use machine learning, natural language processing, robotic automation, or generative AI tools to drive outcomes and help your company meet its goals. 

AI models offer many potential benefits for businesses in diverse industries. AI for business can help your organization with automated customer service, personalized marketing efforts, supply chain and other process optimization, and much more.

How to use AI for business

Businesses can use AI for enterprise resource planning, supply chain management, procurement, human resources, marketing, fraud detection, and more. Companies and organizations in retail, education, health care, financial services, government and defense, energy and resource conservation, and manufacturing use AI to obtain insights from data, streamline processes, and reduce errors.

Some of the ways you can use AI for business include the following: 

• Automated customer service: You can use AI for customer service by, for example, deploying automated chatbots to answer customer questions at any hour of the day. 

• Recommendation engines: You can use AI to recommend additional products to customers based on their purchase history, browsing history, or interests. 

• Sentiment analysis: An AI model can help you monitor people's feelings about your brand by evaluating customer feedback and comments online or on social media. 

• Maintenance: You can use AI to predict when machinery will need maintenance, allowing you to prepare in advance and use preventative maintenance instead of being surprised by unexpected delays. 

• Fraud detection: You can use an AI model to detect fraud by learning the patterns of normal transactions and spotting anomalies that could be fraudulent. 

• Supply chain optimization: You can use AI to predict how many supplies you’ll need or how many customers you’ll likely have, allowing you to reduce the amount of supplies in your inventory and ensure you always have what you need. 

• Process optimization: You can use AI to create more efficient processes, either through automated repetitive tasks or by asking the AI to look for ways of making a process more efficient. 

• Customer relationship management (CRM): You can use AI to manage your CRM strategy, including customer interactions, sales, and data security. 

What is an example of AI in business?

Many companies have adopted AI solutions for their business in some capacity. For specific examples, consider the following case studies of how companies can implement AI to improve processes. 

HP uses AI for faster coding.

HP, a leading IT company, wanted to provide its developers with AI tools to increase their productivity and coding efficacy. The company implemented GitHub Copilot, a third-party tool, to provide the necessary resources to its team. Copilot could, for example, suggest code while developers type to speed up the tedious process of writing the correct syntax, allowing developers to focus more on innovation and creativity. After the company implemented the AI program, developers increased their productivity and found it easier to troubleshoot problems when they appeared. Today, the company allows its team of several thousand developers to access this technology and reports that it encourages a higher level of collaboration company-wide. 

Team Liquid uses AI to analyze data for better performance.

Team Liquid, the esports organization, wanted to improve its research process for drafting esports matches. This process was previously time-intensive and involved analyzing data from previous draft behavior to understand how different players would stack up against one another and what strategies would be most effective during the draft. The team used SAP AI Core to automatically analyze 6,000 professional and 1.6 million amateur esports matches to determine the best draft picks. Using this AI technology, Team Liquid can use its prep time to look at the data more granularly for analysis, increasing its competitiveness.

What is the 30 percent rule for AI?

The 30 percent rule for AI in business refers to the ideal 70/30 split between AI and human contributions to the organization’s workflow. Essentially, the rule states that while AI can handle 70 percent of the more repetitive and administrative workflow, human employees apply their creativity, empathy, collaboration, and critical thinking skills to the remaining 30 percent.

AI solutions for businesses

You have several options for implementing AI solutions in your business. Explore a few AI models to consider and how they can help your company or organization. 

• IBM: IBM offers a variety of AI solutions for companies, including IBM watsonx, IBM Granite, IBM Consulting, and a suite of other tools. These tools can help you build, optimize, tailor, and integrate AI models into your processes and workflows. 

• SAP: SAP offers an AI copilot named Joule, representing a suite of AI agents that deliver outcomes across your entire company. SAP also provides generative AI tools like SAP AI Core, SAP Launchpad, and SAP Knowledge Graph for intelligent data visualization. 

• OpenAI: OpenAI’s business tools include the GPT-4o plus the GPT-5.5 generative models, and DALL-E, an AI image generator. The organization also allows companies to customize a ChatGPT model for personalized output and data analysis. 

Read more: What Is AI Art? How It Works and How to Create It

• Microsoft: Microsoft offers AI tools like Microsoft 365 Copilot, a customizable AI model that can help employees and customers. Microsoft also provides generative AI models in Azure Cognitive Services and GitHub Copilot. This AI model can help you with generative AI code suggestions and help you learn your project documentation to become an expert collaborator in your project.

• Salesforce: Salesforce is a CRM company that offers an AI model named Einstein that can help generate sales content and action items, personalize marketing efforts to your audience segment, and gain better insights into your customers’ behaviors. 

• HubSpot: HubSpot offers an AI CRM model that can help you generate marketing materials like emails and create workflows and to-do lists, as well as an AI model called ChatSpot that can help you as you work. 

Who uses AI tools for business?

If you would enjoy a career where you can use AI business tools, three potential choices include business intelligence analyst, machine learning engineer, and big data analyst. Explore these roles, the median total salary you can expect in the United States, and the projected job outlook over the coming decade. 

All salary information represents the median total pay from Glassdoor as of June 2026. These figures include base salary and additional pay, which may represent profit-sharing, commissions, bonuses, or other compensation.

Business intelligence analyst

Median annual total salary in the US: $117,000 [1]

Job outlook (projected growth from 2024 to 2034): 9 percent [2]

As a business intelligence analyst, you will help companies collect, analyze, and understand data related to business operations. In this role, you may help determine what data sources will help your company gain the insights it needs. You will also analyze this data and report your findings to stakeholders within your company. 

Machine learning engineer

Median annual total salary in the US: $163,000 [3]

Job outlook (projected growth from 2024 to 2034): 20 percent [4]

As a machine learning engineer, you will help create AI models, technology, and devices that can help other people use AI to solve problems. In this role, you’ll communicate with your team and client to understand what the AI model needs to accomplish, after which you will use machine learning principles to build, train, and test the model. 

Big data analyst

Median annual total salary in the US: $117,000 [5]

Job outlook (projected growth from 2024 to 2034): 34 percent [6]

As a big data analyst, you will help companies and organizations collect, understand, and organize data, emphasizing large or complex data sets. In this role, you will work with data on a large enough scale that you will need to employ specific strategies for handling this volume of data, sometimes including semi-structured or unstructured data.

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