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What Business Leaders Can Learn From Popular AI Test Cases In Use Today

09.02.24, 08:52, Msk

Advancement and innovation in technology can often come at a pace that businesses are unable to adapt to - for example, one of the most significant developments in the tech stack of 2023 has been the rapid emergence and development of artificial intelligence and machine learning (AI & ML) applications within a range of industries.

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For many business leaders, it can be difficult to understand how these powerful new technologies can uplift existing business operations. Fortunately, many lessons can be learned from organizations that have made the leap and published their AI test cases online, regardless of whether you’re a CEO or a Walsh University MBA graduate. From chatbots to preventative monitoring, here are five ways that the business leaders of today are using the technologies of tomorrow to enhance their business operations.

Enhancing the Customer Service with AI Chatbots

Let’s face it - no matter whether you operate in logistics, consumer goods, or retail, it’s very likely that your organization has some sort of customer service requirement. This is inescapable - while companies continue to innovate to address customer service needs, there are many scenarios where a human touch is required to handle complex situations. As organizations grow, the increased tech requirements of human operators can cause a range of operational and logistical issues.

However, for problems that do not require a human operator, modern chatbots can be a powerful tool in providing a first line of support for customer queries. These chatbots can assist in optimizing staff utilization in such a way that customer service agents can handle the most demanding of queries while leaving simpler, structured queries in the hands of AI-trained chatbots.

These technologies are advanced enough to handle queries such as password resets, product information, and technical support - areas of account management that may not necessarily need a human operator at all times. Chatbots don’t explicitly have to be externally facing - teams may find it beneficial to road-test new tools internally before publishing more broadly to the customer base.

One such company using AI chatbots to great success is the third largest credit union in the U.S. - the Pentagon Credit Union. Beginning their journey with the use of internal chatbots powered by their organizational Salesforce platform, the credit union today uses a range of bots that leverage internal knowledge articles to help end users with common tasks that don’t require a human touch.

The impact? Chatbots handle nearly 40,000 queries a month, reducing the workload on customer service agents, and improving call center response times significantly. The Pentagon Credit Union is a prime example of how modern technology can be used to enhance business operations - to great success.

AI & Cyber Security - New Innovations

Much can be said of the emergence of cyber attacks as a disruption to organizations of all sizes - posing a risk to customer data and organizational security. Innovations in AI technologies are allowing companies to harden their defenses against future cyber threats - enabling increased oversight of the cyber risks that are present within an organization.

Companies such as Honeywell are actively developing cybersecurity products that leverage a range of AI and ML monitoring technologies to defend systems against cyber intrusion. Honeywell’s Threat Defense Platform (HTDP) is an integrated solution, using a range of detection technologies and ongoing monitoring to provide an integrated solution for building controls such as IoT devices and HVAC systems.

Working hand in hand with external threat monitoring and automated systems testing, these new technologies look set to enhance the way that organizations protect physical assets in the future.

Predictive Maintenance in the Skies

Much can be said of the role of aviation in the modern world - from travel to logistics, the role of aircraft in passenger and freight travel should not be understated. For airliners, however, understanding when their plane engines may need maintenance can be of critical importance - unplanned maintenance disruptions can often cost airliners millions of dollars in additional expenses, not to mention increased maintenance costs.

Airline engine manufacturer Rolls-Royce utilizes data generated by several hundred data points across multiple engines to create a digital ‘twin’ of aircraft engines, allowing sophisticated AI models to analyze the impact of engine usage. Rolls-Royce is then able to use that data to feed information back to airlines - providing valuable predictive maintenance information, which can allow airliners to plan for maintenance and in some cases, prolong maintenance until engines are at a suitable state of wear.

The result? By avoiding unnecessary maintenance, Rolls-Royce can reduce the amount of parts wastage that occurs, improving sustainability. Additionally, this dataset can also be used in parts simulation - allowing for the testing and development of digital parts before creating physical equivalents for testing.

Process Automation - Simplifying Repetitive Tasks

In many organizations, there are many stakeholders that undertake repetitive tasks, that could be candidates for Robotic Process Automation (RPA). RPA uses a combination of artificial intelligence and machine learning to undertake activities that may have previously been undertaken by staff - but are reasonable targets for automation. Take, for example, intercompany requests that may require documentation within a company wiki. A process involving RPA could reimagine that process, allowing for documentation to be managed by an algorithm, while a staff member can work on more significant tasks.

One such company that’s using RPA to great success is Johnson & Johnson, a multinational healthcare provider. By creating an RPA process to standardize common finance procedures such as invoice creation, J&J was able to create a standardized process that validates data, loads it into an enterprise purchase order system, and then posts the information within the company system, in order to provide a clear trail of data from receipt to submission.

Putting it All Together

No matter whether you work in banking, healthcare, telecommunications, or transport, there are a range of potential innovations that can improve the volume, frequency, and quality of current work. From the implementation of AI-powered chatbots to support customer service agents in the finance sector, to the development of digital ‘twins’ that allow manufacturers to advise customers on the optimal way to use their products, innovations in artificial intelligence and machine learning look set to transform the way that organizations interact with not only their data but their underlying processes. As future AI & ML innovations look to gather pace in these industries and beyond, it’s an exciting time to imagine how automation could transform corporate America in the years ahead.