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15 Top AI Use Cases for Enterprise Companies in 2024

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Interested in how your enterprise can best utilize AI in 2024?

As AI has got more advanced, I’ve noticed more and more companies looking to adopt it alongside their team to improve their operational efficiency.

In this article, I’ll review 15 use cases of AI, going over how they are used, and what results other organizations are achieving.

What Are The Best AI Use Cases For Enterprises in 2024?

#1: Content Generation

Content generation is one of the best use cases for enterprise companies in 2024.

AI technology is now capable of:

  • Browsing the web to conduct in-depth topic research.
  • Structuring content in an SEO-friendly format.
  • Using advanced marketing frameworks, such as ‘’PAS’’ (pain, agitation, solution).
  • Self-editing its output, humanizing it, and making sure it’s not plagiarizing existing content.

As a result of this advancement in content quality, organizations that use AI for content creation see a 60% increase in productivity and a 30% improvement in content quality.

💡 Tools like Team-GPT (that’s us) let you further improve your content quality and humanize it by creating custom instructions for your preferred AI model (such as ChatGPT or Claude).

Your team can add instructions for brand voice, language, and writing style to make sure that you can scale your content production without having to heavily edit it.

Alternatively, tools like Jasper AI let you access pre-made writing prompts to write optimized SEO content and offer integrations with SEO tools like Surfer SEO.

Apart from SEO, AI tools can generate social media posts, advertising campaigns, and copy for email marketing.

Case Study: The Washington Post uses AI to produce short-form news reports and updates to scale their content production.

The news corporation has fed an AI algorithm its policies, brand guidelines, and writing styles to ensure quality content output at scale without sacrificing quality.

#2: Data Analysis

Artificial intelligence can enhance your existing data analytics platforms by analyzing large chunks of customer data.

The technology is helping businesses make better-informed decisions about customer needs and marketing and sales performance.

The way it works is that the AI algorithms utilize machine learning to analyze large volumes of customer data to identify patterns and create AI models.

➡️ Instead of hiring data analysts to manually sift through large amounts of data, you can feed your data to a Custom GPT model that can analyze it for you and extract results.

For example, some real estate agents are using generative business intelligence tools like Luzmo to analyze data at scale and provide them with answers quickly.

Additionally, platforms like Google Cloud’s BigQuery ML and Microsoft Azure Machine Learning provide organizations with integrated tools for more advanced data analysis tasks.

Case Study: A client of Trigyn used their AI-powered analytics platform to transform how they interacted with their enterprise data.

The client was able to see a reduction in requests for ad hoc reports, as their employees were able to get instant access to the data they needed, achieving a high adoption rate throughout the company.

#3: Marketing Campaign Planning

You can reduce guesswork and marketing planning time by utilizing AI to help you develop marketing campaigns in minutes.

AI technology helps you plan and launch high-performing campaigns that take care of the brainstorming, content planning, and content creation for you.

There are AI tools like Evercopy that let you share your campaign brief, where you can input your campaign objective, timeline, and features to highlight to further personalize the details.

Example: I tried experimenting with free generative AI tools like Perplexity.

I put detailed explanations of what my email campaign should look like, who I am trying to target, and what my product is about to see what level of output I get:

The tool planned a multi-sequence email campaign that I agree needs some refinement, but it saved me an hour of planning.

To make matters simpler for your team, you can use Team-GPT’s collaborate AI feature to collaborate with your team and build marketing campaigns together.

#4: AI-Powered Automation & Workflow Optimization

AI technology can transform your business with time-saving automations for tasks like data entry and customer service (more on that later).

It can automate and reduce errors in:

  • Decision-making.
  • Repetitive tasks, such as data entry.
  • Data processing, as it enables you to access deeper insights and analysis.
  • Complex tasks, such as document processing and customer interactions.

The way AI automation works is that it uses Large Language Models (LLMs) and integrates them with your organization’s proprietary data.

You can familiarize yourself with AI’s 16-step automation workflow in more detail in LeewayHertz’s in-depth article on how AI automation works.

Case Study: IBM utilizes its Robotic Process Automation (RPA) to automate some of its business processes.

The AI algorithm can automate repetitive tasks, such as data entry and transaction processing, improving their efficiency and data accuracy.

#5: Predictive Analytics & Forecasting

One of my favourite use cases of AI is its ability to forecast and predict.

The way AI’s predictive analytics and forecasting work is that it analyzes historical and current data to make educated predictions.

For example, the technology can analyze past sales data alongside market trends to forecast sales in a quarter.

This helps businesses plan for rises in demand, or decreases in demand, to manage their inventories, while online companies prioritize leads effectively and allocate resources.

Image source.

Case Study: Coca-Cola has implemented an AI sales forecasting system that has improved its forecasting accuracy by over 20%.

This has helped the brand better manage its inventory, predict demand, and think more strategically about its logistics.

#6: Data Categorization

As human error accounts for 75% of data loss, AI data management tools can help you reduce the likelihood of error caused by humans.

AI-powered tools can automatically categorize data based on content and context rather than using pre-defined rules (what it was previously).

This helps your brand handle data better, and save time in the process from manually sifting through thousands of data points.

AI technology uses Machine Learning and Natural Language Processing to learn from data patterns and contexts, enabling the technology to categorize unstructured data with a high degree of accuracy.

Image source.

Data categorization and classification have their use cases across e-commerce and SaaS brands. 

For example, there are e-commerce brands that utilize product recommendation systems where AI categorizes products based on user behavior, preferences, and purchase history.

Case Study: PayPal uses the AI classification tool Simility to flag fraudulent activities for further investigation.

The way it works is that if a credit card transaction deviates from a customer’s spending pattern, the AI model automatically flags it and raises it for manual inspection.

#7: Email Inbox Management

AI helps organizations better manage their leads with automated email chains, saving them time and improving their close rates.

The way it works is that you can set up AI-powered integrations to manage leads, set up automatic replies, and draft responses using generative AI.

Corporations also use AI to detect fraudulent emails and detect spam.

Case Study: Someone I follow on LinkedIn, Sam Bastiaens, shared a cold email inbox automation that he has set up using AI:

The agency founder uses Smartlead to save 1-2 hours of his time every day by automatically managing the cold email inbox and replying to leads.

💡 Sam built this automation in Make, which sends all interested replies from Smartlead to Slack and has ChatGPT draft a response to the lead.

#8: Image & Video Generation

Getting more mature with time, AI technology is also capable of producing images and videos for your brand.

Organizations of all sizes can utilize AI content creation tools like InVideo to create on-brand video content with text instructions.

You can type out a topic and supporting information on what video you need, and the tool will generate a video with script, visuals, subtitles, voiceover, and music.

As for image generation, I’ve noticed brands use DALL-E to generate quality images for marketing campaigns.

The tool is receiving an increased adoption rate by both designers and marketers, as it helps them craft advertising materials and build visuals out of their products.

Case Study: Edelman worked with DALL-E 3, alongside ChatGPT to ideate new physical products to bring to market.

The brand did not replace their designers, but instead used AI as a great starting point to conceptualize new products.

#9: Large-Scale Personalization

AI can also be used to personalize your advertising campaigns, make personalized product recommendations and serve a tailored home page experience.

The way it works is that machine learning algorithms personalize the customer experience based on user behavior on the website and product preferences.

This helps organizations improve their conversion rates and improving customer loyalty.

One of the downsides of deep personalization is that it requires a good amount of customer data to work with.

💡 That means it may not be optimized for first-time users, but online retailers can maximize the value of each returning visitor.

Case Study: Netflix utilizes generative AI to create personalized content previews and thumbnails that are tailored to i