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3 ways for CIOs to improve their positioning with AI | 7wData

3 ways for CIOs to improve their positioning with AI | 7wData

Understanding the role of IT through the eyes of organizational stakeholders is an effective technique for determining how IT may need to change. For the longest time, IT was viewed as a cost center, with a primary emphasis on performance and cost. Over the past 10 years, IT’s role has been elevated in many organizations. IDG’s 2020 State of the CIO survey personifies this trend: 75% of surveyed CIOs identified themselves as business strategists or transformation agents, and 67% claim revenue generation among their job responsibilities.

However, in the era of digital transformation, CIOs need to work harder (and smarter) to secure or maintain the right to be viewed (and funded) as a differentiator. Enter artificial intelligence. AI is changing the definition of “doing the basic things right,” blurring organizational boundaries, and changing the pace at which CIOs can achieve an enviable position on their leadership teams.

Stephen de Campos, the recently appointed CIO at Hunt Consolidated, a multibillion-dollar oil and gas exploration and production company based in Dallas, has partnered with me on this article to illustrate how CIOs can use AI to optimize IT operations, create new ways to win for their organizations, and boost perception of their company in capital markets.

Many CIOs graduated from service provider to business partner by getting the basics right: providing high-quality service in traditional IT Ops domains such as network, infrastructure, and help desk. However, those traditional strategies cannot keep up with the exponential demands of cloud, IoT, and big data that far exceed human capacity. To prevent IT Ops from becoming a limiting factor on your digital transformation, you have to reinvent the basics.

AIOps, which represents the union of AI and IT operations, is how several CIOs are doing just that. AIOps platforms aggregate data from various monitoring and service management sources and apply machine learning to contextualize data, identify patterns, and unlock new levels of intelligence and automation for IT Ops. Early adopters may initially focus on identifying patterns in monitoring data to proactively deploy patches to prevent unexpected downtime. More advanced organizations may deploy virtual service agents, or “chatbots,” that automate key IT service management functions such as ticket analysis and password resets.

In either case, the deployment of AIOps can save time for IT by automating commoditized tasks, lowering mean time to resolution, and limiting unplanned work. The business also gets higher productivity by avoiding manual reboots and receiving higher quality service that is enhanced by AI. In a Forrester study, a composite telecommunications company deployed AIOps and experienced approximately $7 million in labor savings over three years. These savings create a self-funding mechanism that can extend IT’s brand and influence across the organization.

With a self-funding mechanism established, look to your IT business partners to start a consultative dialogue with their business stakeholders. Start by asking about the key metrics they are targeting. For example, a sales function may be focused on increasing conversion rate, while a customer service function may want to optimize average handle time. Work with business stakeholders to deconstruct metrics into their underlying processes to identify steps that can be enhanced by AI.

Start by looking for steps in the process that can be automated. These are typically steps that are highly dependent on repetitive manual data entry or require toggling between multiple applications to look up different types of information.

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