1.AI for customer experience, service, and support

One of the most common enterprise use cases for AI revolves around customer experience, service, and support.

For example, chatbots use both machine learning algorithms and NLP to understand customer requests and respond appropriately. And they do it faster than human workers, and at a lower cost.

AI also supports recommendation capabilities, which use customer data and predictive analytics to suggest products that customers are most likely to need or want and therefore buy.

2.AI for targeted marketing

Online search providers, online retailers, and other internet entities use intelligent systems to understand users and their buying patterns so they can select ads for specific products they are most likely to want or need.

3. Smarter supply chains

Organizations across industries are using AI to improve the management of their supply chains. They are using machine learning algorithms to predict when and what will be needed and the best time to deliver supplies.

4. Operate smarter

AI is being embedded across the enterprise as developers of business process applications build AI-enabled capabilities into their software products.

5. Safer operation

AI is being used by many industries to improve safety.

Construction companies, utilities, farms, mining interests, and other entities working on-site in external areas or within a wide geographic area are collecting data from endpoint devices such as cameras, thermometers, motion detectors, and weather sensors. Organizations can then feed this data into intelligent systems to identify problematic behaviors, dangerous situations, or opportunities, and then make recommendations or even take preventive or corrective action.

6.AI quality control and quality assurance

Manufacturers have been using machine vision, a form of artificial intelligence, for decades. However, they are now advancing this use by adding quality control software with deep learning capabilities to improve the speed and accuracy of their quality control functions while controlling costs.

These systems are providing more precise, improving quality assurance capabilities as deep learning models create their own rules to determine the factors that define quality.

7.AI for contextual understanding

Businesses are also using AI for contextual understanding. Linden pointed to the insurance industry's use of surveillance technology to offer safe driving discounts as a good example. AI is used to process data about driving behavior to predict whether it is low-risk or high-risk. For example, it's safe to drive at 65 miles per hour on a highway, but not in urban neighborhoods; Intelligence is needed to understand and report when and where fast driving is acceptable.

8.AI for optimization

Optimization is another use case for AI that spans industries and business functions. AI-powered business applications can use algorithms and modeling to turn data into actionable insights into how organizations can optimize a range of capabilities and business processes—from worker planning to pricing production products.

9.AI and more effective learning

The potential impact of AI on education is enormous, and many organizations are already using or exploring intelligent software to improve the way people learn.