8 AI Use Cases Every CxO Should Know About

Artificial intelligence is changing from promising concept to a core technology businesses will need to use going forward

While reading about tools and frameworks can give C-level decision-makers ideas for incorporating the technology, it’s also worth exploring how others are making use of AI; after all, it’s important to close gaps created by your AI-adopting competitors. Here are a few AI use cases executives need to explore.

Fraud and Theft Detection

Dealing with fraud is all but inevitable when working in the financial sector. Retail stores assume some amount of theft as part of doing business. Classic monitoring is still essential for detecting fraud and theft, but AI systems can go a step further and detect problems while they’re underway. Modern AI systems are trainable and when given one or more sets of data, they can detect patterns that are hard to spot using more traditional techniques. By feeding systems banks of legal and banks of fraudulent data, these systems can be trained to detect fraud as it occurs. Likewise, AI in retail can detect popular locations for theft and, in some cases, even determine the time when theft is most likely to occur. This data gives store owners and managers useful information for improved store monitoring.

The AI-Enabled Office

Today’s offices are filled with technology. However, it’s easy for employees to become overwhelmed with technology, and the urge to multitask can lead to poorer performance. AI-based voice assistants and robotic processes can let employees disconnect from monitors for a moment to complete tasks. AI can also serve a purpose in intra-office communication; AI can alert users when changes are made to collaborative works, and it can help route information to the employees who need it most. AI is already being used for time management systems, and it can help employees schedule their days more effectively. The smart office is coming along, piece by piece. For executives and others focused on employee productivity and satisfaction, it’s important to take a more holistic view of AI and find out how it can be integrated to create a truly modern workplace.

We recently spoke to Mihir Shukla, CEO and Co-Founder of one of the market leaders in robotic process automation, Automation Anywhere.

Customer Service

Telephone helplines of the past have a well-earned reputation for being hard to use, and their infamy has poisoned the well when it comes to automated assistance. However, AI is increasingly playing a role in customer service, and recent reviews of modern technology are far more positive. By reading through past interactions with customers, modern systems are better able to sort through human language and determine what the customer is asking for. In addition, these systems can improve over time, as each new interaction provides more data to improve performance. While some customers will always prefer to speak with a human, many people claim to prefer interacting with a chatbot or other automated interface. Although these bots will lack the so-called human touch for some time, they can access large databases that are easy to update instantly, which can lead to better overall assistance.


Jobs throughout much of the developed world are becoming more intellectually demanding, and they’re becoming more specialized. Even though online recruiting and online resumes have helped companies connect with potential employees, the task of hiring the right person has become more of a challenge. AI tools are better able to sort through potential candidates and provide valuable heuristics to recruiters. Benefits don’t end after an employee is hired: AI systems are valuable tools for onboarding new hires, and they can even replace a number of human resources tasks. Companies don’t have to develop all of this technology internally, as a number of companies now provide AI-based recruiting services that can perform nearly everything up to an in-person interview, letting HR employees spend their time on other tasks.

Logistics Management

The value of computer technology is clear when it comes to logistics, and this is especially true when it comes to dealing with warehouses and shipping. As more and more customers expect free shipping, reducing logistics costs will be essential. Computerized inventory management and tracking is effectively mandatory in many fields, but AI is able to use this data to provide useful information and let companies find means of cutting costs. These cost savings tend to be incremental, but they add up over time. One area in which AI excels is finding counter-intuitive information. Shipping routes that no human or traditional computer system would even consider might have some unexpected benefits that machine learning can uncover. Furthermore, there may be subtle annual trends that are easy to miss in the data, and AI systems might be able to uncover unforeseen yet reliable trends.


The internet is invaluable for businesses of all sizes. With the power of the internet connectivity, however, comes a number of risks, as hacks can be expensive and lead to lost customers and a drop in reputation. The fundamentals of cybersecurity haven’t changed with the dawn of AI, but AI-based tools are better able to detect threats as they occur and take preemptive steps to halt would-be attackers. AI tools are also able to audit systems and find bugs that humans might miss. It’s worth noting that hackers are often among the first to adopt new technology, and it stands to reason that AI will lead to more sophisticated attacks in the coming years. It’s important to first focus on basic security, but executives should explore if AI-enabled cybersecurity is worth the investment.

Callsign’s Intelligence Driven Authentication (IDA) protects identities and defends against data breaches. We recently spoke to their commercial VP Daniel Grimes.

Energy Management

Computing has long-assisted energy management, from power stations down to the lines to customers’ homes and businesses. AI provides even better capabilities for detecting power usage patterns and ensuring data is routed properly. Multiple plants can share data to optimize their operations, as can regulators. Customers can benefit as well: AI-derived data can inform customers about their energy usage and to help them make more informed decisions about their consumption. For C-level decision-makers, energy management serves as a shining example of how cooperation, even among competitors, can make better use of resources. Two companies depending on shared resources can often save on expenses by combining their efforts to provide faster and more precise resource allocation. Similarly, providing customers from the type of transparent information AI is good at delivering can serve as a win-win for both parties.

Leveraging IoT Technology

The software dealing with IoT devices is complex, and many of the most popular tools rely on AI and machine learning to provide base functionality. However, AI can do so much more when fed data from IoT devices. Some IoT devices will inevitably fail, and AI algorithms can detect when a device is likely to break in the near future, allowing for preventative maintenance. Furthermore, AI can detect use modes that lead to bugs and other problems, enabling companies to request software fixes. Perhaps the most powerful technique, however, is to let AI roam free across IoT data and look for correlations. While correlated data doesn’t necessarily show causation, it’s often the case that unexplored metrics have more of an impact than initially imagined. Machine learning, in particular, can be great for finding unexpected knowledge buried within volumes of IoT-generated data, and it’s worth exploration.

Currently, AI today is far less human-like than experts predicted in the mid-20th century. But while we haven’t quite reached the singularity yet, hardware has become many orders of magnitude faster and cheaper, and the economic benefits of AI are making it a red hot field for research. While we’re just at the beginning of what many believe is an AI revolution, companies of all sizes need to take note of how the technology is advancing and how others are leveraging the technology. For C-level decision-makers who prefer to defer decisions to others, it’s time to personally take a closer look at what AI can do.