Is AI automation? Or, is Automation AI?
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The adoption of AI to drive greater automation provides impactful and measurable results, but that doesn’t mean it comes without challenges. More often than not, your systems may be dated and not quite compatible with the visions of artificial intelligence dancing in your head. There is also the ongoing concerns that bringing AI and related technologies into businesses, people will be out of work. So, to ensure your organization has fully thought through the future adoption of AI and automation, here are five considerations to start you on the path to success.  

1. Understand how the adoption of AI and automation will impact your team 

It goes without saying, but the adoption of AI will not only change the technology your team is using but also how they operate together and with your technology stack. Ensuring your team in comfortable with the changes and quelling any resistance to interactions with these new technologies. A bit of a cultural shift will be needed for success in adopting AI and automation. It’s critical to ensure you have a communication strategy around training, goals, and addressing concerns employees may have about AI. 

2. Make a plan and stick to it  

Change management has always been a key to your ITSM strategies. Not to sound like a broken record, but a giant part of change management is communication. Not everyone will understand how AI may impact their current work methods, nor how it could provide new benefits to their work day. As you build out your AI implementation plan, the technology steps are your outline but design and implementation programs are the color you will need to fill in to ensure your team is onboard.  

3. Availability of quality data 

AI and automation technologies will only act upon the data provided. If the data in your systems is of poor quality, then the result from the introduction of AI and automation will also be of poor quality. If you have a bunch of data, it’s easy for it to become disorganized and, thus, get overwhelming. Be proactive in keeping everything in order so that as you implement AI and automation technologies, your data is helping vs. hindering. Your data should be adaptable to new information that comes in, and flexible enough to be able to address new capabilities. Perform basic risk assessment, compliance checks, and measure the quality and potential value of each source. 

4. Ensure buy-in and adherence to your governance structure   

How will your organization ensure that the outputs delivered from AI and automation comply with policies and regulations? As with any other technology, organizations cannot follow an ‘implement and forget’ approach to AI. A formally defined approach to governance is needed to ensure that AI delivers the expected benefits to the organization. Successful implementation of AI and automation greatly depends upon support throughout not just the IT organization but the greater enterprise. However, without some level of executive support, this major change to your technology stack could fail. The success of any major initiative, especially in the realm of governance, depends upon landing that executive support. 

5. Don’t forget to plan the design 

As a part of your planning process, design is a key for success with AI and automation projects. Implementation planning is great, and typically the major focus. However, don’t ignore the critical aspects of design. Analyzing the operating model, determining which tasks to automate first, and ensuring that automation integrates with existing control points are just as important (if not more important) as configuring AI software. 

AI and automation will not exist in a vacuum, and neither will the processes that are enhanced with AI and automation. Spend some time assessing these five considerations within your organization before taking the plunge into the great application of AI and automation within ITSM.

Practical use cases of artificial intelligence and automation in ITSM

Source : https://www.symphonysummit.com/artificial-intelligence/is-ai-automation-or-is-automation-ai/