What Should IT Leaders Know about Artificial Intelligence?
Artificial Intelligence (AI) is quite arguably the most widely discussed technological disruption occurring in the IT industry today. It seems everyone is talking about AI, but few people actually understand it and its use in a business organization. It is important for IT leaders and business-facing staff members not only to understand the underlying technology, but also the business-use cases being discussed and implemented across the industry. With this understanding, you are more likely to be an effective and trusted technology advisor.
Artificial Intelligence isn’t the same as Machine Learning
Machine learning (ML) is essentially a rules-based automation engine. An ML system is trained via rules definition to look for certain conditions and perform a pre-defined set of actions. Artificial Intelligence is built on an ML engine, but is focused on making comparisons, evaluating relevance and projecting potential outcomes as a means of initiating the best available set of actions (not just those scenarios for which it was programmed). This is important because AI is capable of interpreting spoken language (sounds), images (both still and video) and inferring data relationships that may not be explicitly defined. Conversely, ML just executes defined rules. These concepts are often confused, and it is frequently the responsibility of IT leaders to explain to both business partners and IT staff the difference.
Your business partners are hearing much about AI
Artificial Intelligence isn’t just an IT topic, it is increasingly being discussed at conferences and presented in publications for many business disciplines, including manufacturing, finance and marketing (just to name a few). When your business partners hear of an innovative technology that can make their job easier, they look to you as their IT leader to help them understand what is possible, where they should implement it and how to start.
You should be using AI as a part of your ITSM processes
Most of the discussion about AI within your company will likely be centered on business operations functions. IT is a function that can benefit from AI capabilities as well, to manage costs, risks and improve the performance of IT services. There are three key areas within your ITSM processes where you should be exploring how to leverage AI capabilities.
- Chatbots for end-user self-service support
- Monitoring of IT systems for outages, performance issues and security risks
- Change management impact assessments – identifying what systems, processes and locations would be impacted by a change
Eventually, AI will become an underpinning capability that will support all parts of your IT processes. During the near-term, you will benefit the most from it when managing/processing both a large number of transactions or events as well as relying on the subjective assessment of staff to identify the best course of action.
Risk management will be the high-value AI use-case for the next few years
Since AI is a relatively new technological innovation, there is much noise and chatter, such as “We could use it here, or there.” The reality is that most organizations aren’t ready for the disruptions AI is likely to cause to both operations and individual job roles. Risk management is the one use case where AI is uniquely suited to outperform humans, as it is both an urgent business need and not likely to result in much cultural resistance.
Risk management is a big guessing and estimation game – evaluating the likelihood, impact and cost of mitigation for various events or scenarios. Companies have limited resources, so the goal of the risk management game is to generate the most value possible with the available resources. The performance of risk management activities is greatly improved with larger and more diverse datasets being considered during the analysis – time is of the essence when it comes to making decisions. This is the ideal situation for leveraging AI to help.
As an IT leader, it is important to understand what AI is (and isn’t), where it can be used within your organization and the high-value use cases that will help you provide a justification for introducing enterprise-scale AI capabilities within your company.
Cover image by Saravana
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