Is Your Company Ready For AI?

One of the biggest mistakes IT champions make when pitching trendy transformative technologies like AI, blockchain or quantum computing to executives is not doing their homework. They often fail to identify the problem they are trying to solve, determine whether it’s worth solving and understand whether their company is positioned to solve it.

This article proposes a simple four-part framework your champions can use to assess AI readiness so stakeholders can get a good early read on the likelihood of success before you invest too much time and effort in AI initiatives. To animate this framework, I will apply it to a real-world scenario — assessing organizational readiness for AIOps, or the application of AI technology to transform IT operations.

The framework comprises four elements.

    1. Problem Identification

How often does someone in a spirited meeting regarding a business or IT challenge say, “Wait a minute. What problem are we trying to solve?” Often, in-depth discussions about solutions become disconnected with problems, a major reason why technology initiatives often get shot down during executive review. It’s critically important that your champion is clear about the problem AI solves and its underlying cause.

To demonstrate to stakeholders that the problems an AIOps initiative will address are understood, champions should answer assessment questions like these:

  • Are there one or more key metrics or KPIs (e.g., downtime, service levels) that AIOps can directly impact?
  • Can identified IT operations problems and their causes be clearly linked to AIOps capabilities and benefits?
  • Is it clear that your current technology or process can’t be easily tweaked to solve the same problems?

Of course, you can generalize these questions and apply them to any IT initiative, not just AIOps.

  1. Strategy Alignment

Champions and sponsors of IT initiatives must establish a clear connection between chain-of-command priorities and technology solution investments. Without this, they are unlikely to gain executive traction for their initiatives. In the case of AIOps, it’s important to tightly link potential benefits with key priorities of the CIO and VP of operations such as reducing business disruptions or freeing up resources for strategic projects like cloud migrations or M&A.

Champions can establish strategic alignment by answering these assessment questions:

  • Are IT operations processes, challenges, pain points or use cases mapped to AIOps solution capabilities?
  • How are IT operations performance outcomes — such as fewer major incidents or faster mean time to resolution (MTTR) for incidents — linked to these process challenges?
  • How are key executive-level priorities, strategic objectives or key business initiatives linked to anticipated IT operations performance benefits?
  1. Business Case Viability

This focuses simply on determining whether a reasonable business case can be made. At a minimum, this means that your champion has identified key business drivers and is comfortable that the business value can be quantified in a relatively straightforward manner. A high-level business case with ballpark estimates of the potential value would be even better. A formal business case and ROI analysis that includes more validated estimates (e.g., after a PoC evaluation) comes later.

In the case of AIOps, this translates into validating that process improvements can be measured and quantified into financial benefits. This includes identifying major process areas where this can be reliably estimated like cost savings from automation, downtime reduction and savings from reducing the mean time to resolution for incidents.

While some technology initiatives are justified based on soft/qualitative benefits alone, you should assume that you’ll need harder justification to win executive approval for a program like AIOps.

Here are example assessment questions:

  • Can we reliably baseline current process performance and metrics such as team utilization and effort taken to complete specific tasks?
  • Do we know what success looks like and how to measure it? For example, can we strategically align and roll up measurable benefits such as cost savings, downtime reduction and process cycle time savings?
  • Will we be able to estimate process performance and metric improvement (e.g., effort saved due to automation, downtime reduction) based on a proof of concept or other approaches?

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