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CIOs: Don’t rush to AI to solve IT operations management problems

At Friday’s Wikibon Weekly Research Meeting, we discussed applying artificial intelligence and machine learning at the discipline of information technology operations management. But before jumping on the latest trend, we suggest three things that chief information officers should consider before jumping into the hype.

For background and summary, let’s review the operations management problems IT organizations face today and the business impact that improvements will have. IT is often criticized for being too slow to react to operations issues and that has affected a laundry list of things in the business. To name a few:

  • Application availability
  • IT and business productivity
  • Data quality
  • Application performance

The impact of these and other issues is increased business risk and cost. Practitioners in the Wikibon community express a desire to be proactive to address these issues and vendors are promising that their tools will allow them to be more anticipatory. Customers want to reduce false positives and minimize the number of trivial events they must chase. And of course the cloud complicates all this.

The vendor community has promised end-to-end visibility on infrastructure platforms, including clouds, and the ability to discover and manage events and identify anomalies in a proactive manner. Maybe they can even automate necessary remediation steps. These are all good and important features. Furthermore, these capabilities must align with and map to critical business processes so that customers can prioritize and of course this must extend to cloud resources.

Is AI and ML the Answer?

Wikibon is encouraged that bringing analytics to ITOM disciplines has great potential, but we suggest that organizations look at three things before making the leap:

  1. Understand that most outages on infrastructure come from failed or poorly applied changes, so start with good change management and you’ll attack probably 70 percent of the problem, according to Wikibon estimates;
  2. Narrow down promises and get service level agreements firmed up so you can meet and exceed expectations, and build credibility with an organization before taking on wider responsibilities. Don’t take on too much because in our experience organizations will inevitably hit a skills gap. We recommend finding a sweet spot of services and not spreading too thin.
  3. Start acting like a cloud provider. Be clear about the services that you offer, clearly communicate the SLAs agreed upon and appropriately charge for those services so that you can fund your operations.

Do these three things before you start throwing technology at the problem.

The clip below excerpt this summary from the research meeting.

Image: GDJ/Pixabay

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