AI Use Cases for Business Leaders & Innovators

AI has been with us for years, but the extent of its capabilities is only now becoming apparent. The rise of GenAI tools such as ChatGPT has changed the perception of AI from futuristic science fiction to everyday tools. Awareness about AI and curiosity about what it can do have become widespread in the business world and beyond.

It’s clear that AI adoption will have a profound effect on the world economy. The McKinsey Global Institute estimates that generative AI will add between $2.6 and $4.4 trillion in annual value to the global economy every year.

Enterprises are eager to get ahead of this revolution, and they are finding myriad ways to leverage AI to benefit their businesses.

Some of these are already becoming widespread, such as the use of customer service chatbots to answer questions and solve common issues — fixing simple problems more quickly and freeing up human agents for more complex interactions. Another popular use of AI is in personalization, such as when a streaming service recommends content that customers should try based on their past preferences. GenAI applications that create content are also quickly becoming everyday tools at many businesses. AI content tools can help employees streamline tasks such as writing, putting together presentations and reports and finding information.

A growing number of enterprises are also adopting AIOps, which applies AI to IT operations to help companies manage infrastructure, networks, applications and processes. AIOps use cases include:

• Data management and analysis
• Maintaining uptime and website reliability
• Anomaly and threat detection
• Capacity optimization
• Ensuring app performance
• Reducing open incident tickets

These types of AI use cases are becoming familiar, but new ones are being developed every day. And AI tools are evolving. Bots, which lack natural language processing (NLP) and reasoning capabilities and are often limited to specific scripts, are being replaced by copilots that use GenAI and NLP for more flexible and dynamic assistance. Most recently, agentic AI has been on the rise. These AI systems have reasoning capabilities and can make decisions on their own to achieve human-directed goals without much human guidance. They can also interact with people in human-like ways.

AI use cases by industry

While many AI use cases are broadly applicable across industries, others are specific to certain sectors or even organizations. This adaptability is one of the advantages of AI, as it allows enterprises to develop bespoke solutions. Here’s a sampling of some of the ways companies in different industries are using AI to boost their business.

Consumer goods and retail

AI can help companies in the consumer goods and retail space with both back-end and customer-facing functions such as:

• Customer service
• Understanding user preferences, behaviors, and contextual cues
• Pricing strategies
• Demand prediction and inventory planning
• Scheduling and tracking deliveries
• In-store product finding assistance
• Virtual fitting rooms

Edmunds, a trusted guide in online car shopping, embraced generative AI capabilities to revolutionize their approach to identifying and moderating “dealer quality of service” reviews. By employing a GenAI model, the company has automated analysis of hundreds of daily reviews for quicker online publication, saving valuable staff time and enabling them to focus on more essential tasks.

Creative

AI advancements for creative work over the past few years have been high-profile and game changing. The launch of GenAI tools such as ChatGPT, DeepAI and DALL E 3 have introduced unprecedented opportunities for creating high-quality written, musical and visual content with natural language prompts. Creative AI use cases include:

• Automated video editing
• Visual effects enhancement
• Film pre-production
• Interactive storytelling
• Graphic design
• Editing and proofreading

Established creative tools have also expanded their capabilities with the help of AI. Adobe, for example, offers Firefly, a suite of GenAI design models that extends the powers of tools such as Photoshop, Illustrator, Express, and enterprise products. These models boost efficiency and productivity for tasks such as editing, personalized content, and conversational experience. The company has also launched Adobe Sensei GenAI, a copilot for customer experience workflows, to enhance productivity in Adobe Experience Cloud.

Energy/Chemical

AI use cases are also being adopted in the energy and chemical industries, including:

• Aggregating key metrics across production systems
• Smart grid management
• Drilling and exploration optimization
• Quality control
• Identifying potential hazards to enhance safety

DuPont employs AI for predictive reliability and maintenance, production scheduling and sales price optimization. While the company had previously tried chatbots for both customer and employee purposes, the results were disappointing. New large language models (LLMs) have made chatbots faster, more accurate and more effective overall.

Finance and insurance

AI offers a variety of applications in the world of finance and insurance, including:

• Collecting data for regulatory compliance and monitoring
• Detecting potential fraud and financial crime
• Extracting insights from data
• Monitoring and managing trading
• Accelerating underwriting

Allianz Direct online insurance company uses GenAI to hand off mundane customer service agent tasks to AI, empowering contact center agents to spend more time building personal customer relationships that drive lifetime value. A new AI-powered application agents use for customer questions was 10% to 15% more accurate than the previous version.

Healthcare

In the healthcare arena, AI has the potential to not only improve patient outcomes, but to assist employees in this short-staffed, stressful industry. AI tools have made important contributions to medical research, and other AI use cases include:

• Collecting and analyzing patient data in real time
• Providing more accurate diagnoses and treatment plans
• Streamlining tasks such as transcribing medical notes and answering medical questions for consumers
• Making healthcare administrative processes more efficient
• Improving robotic surgery outcomes

Automation and predictive analytics also show great promise. Kansas City VA Medical Center in Kansas City, Missouri, has tested a model to assess the 24-hour risk of whether a patient admitted to the hospital will need to be transferred to a higher level of care. The hospital found that using the model significantly improved the accuracy of risk assessments, potentially leading to a significant reduction in mortality.

Manufacturing

AI is being leveraged to help manufacturers with every stage of business, from design to delivery. AI applications within manufacturing range widely and include:

• Assessing and solving process bottlenecks
• Copilot assistance for technicians
• Enabling conversational interactions with machines
• Natural-language troubleshooting
• Providing proactive field service
• Auto-generating and adapting contracts, purchase orders and invoices

Forecasting is a key area for AI improvement. When it comes to supply chains, for example, AI can help organizations better predict long- and short-term supply needs and shipping times for improved efficiency and customer experiences.

JetBlue is using AI and ML across its business and actively using GenAI for internal operations as it seeks to be the “most data-driven airline.” The company has created an ecosystem of models called BlueSky, a continually refreshed network with embedded LLM and real-time components for frontline staff to enable decision making.

Media and entertainment

Many organizations in the media and entertainment realm have used AI for years to curate content — for example, Spotify uses it to make music suggestions based on what the customer has liked in the past, YouTube creates a personalized video feed based on customers’ previous choices, Netflix offers targeted viewing suggestions and LinkedIn filters customer newsfeeds based on customer history.

Showtime collects huge volumes of subscriber data such as shows watched, time of day, devices used, subscription history and more. The company uses machine learning to gain insights from this data that allow it to predict subscriber behavior and improve scheduling and programming to drive viewer engagement and reduce churn.

AI use cases in this industry also include:

• Intelligent search
• Real-time content quality feedback
• Predicting content popularity
• Customizing video game challenges
• Audience targeting and segmentation
• Content classification and categorization

Travel and hospitality

With AI, organizations in the travel and hospitality sector can use technology to enhance experiences in the physical world. AI use cases include:

• Dynamic pricing
• Logistics such as baggage handling
• Facial recognition
• Guest experience analysis and optimization
• Integrated inventory and purchasing

EasyJet uses GenAI to enable non-technical business users to ask questions in natural language and gain insights from the company’s rich datasets. Business users now interact with data using natural language and base decisions on the insights provided by LLMs.

Building the right foundation for AI use cases

As AI continues to grow, AI solutions will follow suit. But organizations that want to keep up will need to have the right foundation. They need a data infrastructure that empowers them to realize the full value of their data while keeping it safe and secure. The Databricks Data Intelligence Platform, built on lakehouse architecture, represents the latest evolution in data storage. It helps companies deliver data and AI initiatives faster while reducing costs.

Enterprises also need advanced solutions to aid in implementing AI use cases. Databricks Mosaic AI provides unified tooling to build, deploy, evaluate and govern AI and ML solutions — from today’s predictive ML models and GenAI apps to future AI solutions yet to be imagined. Built on the Databricks Data Intelligence Platform, Mosaic AI enables organizations to securely and cost-effectively build AI systems integrated with their enterprise data.

Databricks is also working to democratize AI for companies of all sizes by open sourcing DBRX, a general-purpose LLM that outperforms all established open-source models on standard benchmarks, enabling customizable, transparent GenAI for all enterprises that won’t compromise their data.

See why over 10,000 organizations worldwide rely on Databricks for all their workloads from BI to AI where you can test-drive the full Databricks Platform free for 14 days. Try for free or take the Generative AI Fundamentals On-Deman Training