Oct 27, 2022. By Anil Abraham Kuriakose
Managing and coping up with the recurring changes is a big concern in every enterprise IT. Managing and dealing with every change such as an OS update or system update or even a back up is a big task . Moreover when it comes to large enterprises, the number of systems to control, monitor and manage just gets adding up. And a single operator or an IT team won't be efficient enough to handle all this process at a time. They need to monitor the system for updates and backup. Manually this can fail at some point. Moreover, just cause of the difficulty in handling these changes, the use of IT resources or elements cannot be compromised.
Let us consider a scenario, where all of these above mentioned issues for a change management to happen gets resolved . That is, some efficient mechanism is found to handle these issues in an enterprise IT. But the next quest arises here. That is managing the risk of having this change applied into the system. That is, no software or system OS update can have a 100% guarantee that upon the installation into the system may cause some error or break something. This is the area where the concept of risk management comes into the picture.
Change management is always associated with the concept of risk management. That is, any change such as OS updation or doing a recurring task manually has its own risk. The concept of risk meant here is that, the after effects of implementing these changes. That is to be simple, some changes can fix something and while some can break something. This risk should be pre-defined or pre handled very effectively and also should be addressed effectively, so as when such a change is about to happen, the risk for that particular change can be noted and based on that , a decision can be made whether to have that done or not. But, the major concern faced here is, to analyze this risk manually which is practically impossible. And that to predicting the risk of having a new change implied to the system is also difficult. So, what is the right approach here? Or How can we efficiently manage the change management in an IT enterprise looking into the risk factor too?
Artificial Intelligence and Risk Management:
The right solution for all the above problems is Artificial Intelligence. Yes, implementing AI into the system, where in which AI will handle all the change management process. More efficiently handle the risk of the system to implement the particular change. The AI based system are highly capable of automating the process of change management such as any OS update or efficiently managing the entire system backup that is required. That is, the system will be capable of understanding the different IT environment elements and monitor them closely to understand if any OS updation or if there is any task that needs to happen continuously. Now ,taking the the part of risk management. Lets see how efficiently AI can handle the concept of risk management with the corresponding change management.
AI based risk management, is a very fancy concept to hear. But can this really benefit? Yes, it does. AI is highly capable of pre-defining or analyzing if there is any risk factor for a particular change to happen. AI based risk model will be trained and deployed into the system, which will continuously monitor every change request that is accounted in the system. Each of these changes will be analyzed by the risk model. And this risk model will provide a corresponding risk score for each of the change request. The risk score can vary from high, medium and low. Based on this analysis, the IT team or the IT operator can effectively understand the risk of implementing such a change. Lets consider for example, a new OS update was noted as a new change request to the system. The AI based model will at first analyze the change request and on knowing it is an OS update, it will check across the risk model which is deployed. The risk model are made up based on data from historic changes and how the system respond to those changes. Based on the deployed model, the system identified that this particular system OS update can cause some unwanted issues into the system. So the system will initialize a risk score saying that the risk is HIGH for implementing this new change. Based on this analysis the IT operators team take the next efficient steps.
Artificial intelligence is totally taking up every part of the IT enterprise. The benefits it poses is great both in the operational side and also in business perspective. The AI based risk model assessment for change management is one such great benefit AI can bring into the IT industry.
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