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Today, it appears IT leaders cannot open a web browser without learning how artificial intelligence (AI) and generative pre-trained transformer (GPT) technologies can save businesses time, resources, and money. Unfortunately, they might also come across stories about how enterprises have endured a disaster due to AI and GPT being applied in the wrong use case and with bad data. According to a recent Gartner webinar poll of more than 2,500 executives, 38 percent indicated that customer experience and retention is the primary purpose of their generative AI investments. This was followed by revenue growth (26 percent), cost optimisation (17 percent), and business continuity (7 percent). In addition, Forrester has warned that if generative AI makes things easier, it also makes doing bad things easier.
Many enterprise IT teams are now trying to decipher how to best take advantage of these technologies' without risk. One key attraction with sophisticated technology, is its promise to automate processes and reduce the work of gathering and correlating data across industries. For example, AI and GPT could lessen the time it takes IT to find and solve problems and communicate results in an undeniably human, conversational manner that will resonate with end users and customers. This is one of the many use cases for GPT in today’s sophisticated IT environments.
Automation is key
AI and GPT rely on the consumption of large volumes of data in an environment, as well as the ability to quickly correlate real-time events and alerts with known incidents and their respective fixes. These technologies can be used as embedded capabilities in experience and service monitoring tools, enabling IT teams to speed problem identification and resolution.
Essentially, AI and GPT technologies can quiet the noise of multiple events and alerts, while providing valuable insights to IT teams faster than humanly possible. The number of alerts generated from numerous monitoring tools has long been an issue when managing sophisticated IT environments. However, with GPT, IT teams have the tools to determine which alerts represent a critical incident and which can be disregarded as noise.
Identifying problems and intelligently resolving
Many IT environments have various monitoring tools that generate alerts when an incident occurs. However, when you factor in service tickets generated from end users, the task of relating the events to the service request can rapidly become overwhelming for IT teams. IT operators attempting to understand how to resolve problems and close the service tickets will benefit significantly from GPT technologies that can generate problem resolution.
AI and GPT can provide considered, plain-language summaries of how issues have been resolved in the past and how that knowledge can be applied in the current situation. For example, GPT can generate root-cause reports by deciphering a cluster of related tickets and distilling key resolutions from this. This eliminates wasted time for IT and speeds service availability for end users and customers.
Search is a useful tool, especially when delivering answers directly related to the search query. With AI and GPT embedded in search technologies, service managers and IT operators can place more
trust in knowing the search results will apply to the issue at hand. GPT can power service desk agents and end users in their quest for adequate, applicable answers with their company’s digital workplace. AI and GPT tools will deliver the best and most likely answer quickly, which speeds time to resolution for IT and employees alike.
Virtual agents get smarter
Because of its natural language processing, GPT can enable virtual chat agents to communicate more humanly than ever before. Using its access to volumes of enterprise data, GPT can search and find the quickest, best response for any query. On top of that, it can relay the information in plain language that is easy to understand and implement. Again, the power to speed issue resolution will provide infinite benefits to an enterprise company by easing the load on IT teams. This enables end users to help themselves, and gives customers access to the best information and smartest tools to answer their questions.
Changing risk prevention with DevOps
Organisations embracing development operations (DevOps) likely live by the “fail fast, fail often, recovery quickly” mantra when implementing changes. With GPT, failing is not an option because the technology can tell users what is likely to happen when they deploy specific changes. Generative AI-driven technologies can be integrated into the DevOps toolchain, which enables developers to see the potential impact of a change prior to releasing it. Drawing from the lessons of past failures, AI and GPT can anticipate the impact of a change or release to a business service and identify the change risk level, even before implementation.
AI and GPT is intriguing IT leaders as it evolves in readily available apps and within enterprise environments. Savvy technology leaders will learn how to apply the technologies in their companies to relieve human staff of tedious data collection and correlation, and speed up time to resolution and repair. End users and customers can also enjoy the benefits of AI and GPT when it empowers them with the knowledge to help themselves.
Going forward, AI and GPT will continue enabling enterprise IT departments to streamline problem identification, resolution processes, and much more. To gain these benefits, IT leaders must devise intelligent strategies to embed the technology within their organisations and harness its power to drive an autonomous digital enterprise.