How AI Is Reshaping IT in 2020

How AI Is Reshaping IT in 2020

AI has been given a major trial-by-fire in 2020, one that no one could have predicted. The increasing use of AI tools and automation comes as a result of the remote work necessary in response to the ongoing global pandemic. Enterprise and IT teams are tasked with doing more with less while maintaining supervision of key performance metrics. This demanding climate, which offers little wiggle room for failure, has prompted many IT leaders to turn to AI-backed tools to keep productivity high and the risk of business disruptions low.

“COVID-19 has shown us the power of IT,” expressed Jamal Robinson, in a recent Forbes interview. Robinson, who  has headed AI projects with Intel and Amazon Web Services, went on to say, “[…]Having the right technology solutions available allows all enterprises to more easily pivot their business operations with market changes, even changes as unexpected and disruptive as a global pandemic.”

In recent years, AI advancements have moved from theoretical and experimental projects to practical applications with AI. The availability of deployment-ready, vendor-based, and cloud-hosted solutions has brought AI to a broader range of IT organizations. Use of AI is increasingly vital in a business world that expects agility as well as reliability. AI-based operations models tend to be more lean and also more robust, capable of producing results that are optimized for efficiency with targeted outcomes that aim for maximum results with minimum effort.

Amidst these advantages, use of AI-powered analytics and other technology has a specific set of requirements. There is a strong need for constant calibration, model training, and troubleshooting, and many AI projects need firm ethics guidance to prevent unintended consequences. These necessities limit the ability for AI-backed solutions to be truly ready for “off the shelf” use and mass consumption.

“The power of AI is still largely untapped,” writes DevOps Magazine, adding that, “It is already creating a massive shift in how we work, and that is only the beginning.” 

AI implementation remains highly tailored, and it operates best when customized for specific organizational use cases. Once these requirements are met, the advantages AI can bring IT can benefit the whole organizations they serve.

AI Use Is Growing, Both in IT and Organization-Wide

Thirty-four percent of organizations have invested $5 million or more in AI projects, reveals a Deloitte survey. And 80%  of respondents reported a positive ROI of at least 10%, while 11% report an ROI of 40% or greater.

Deloitte’s survey also revealed that most people believe that the biggest gains from AI will occur in the next two-to-three years. This may sound like an exciting prediction, but it can also act as a warning – organizations have a limited window to use AI as a differentiator. Missing that window means playing catchup, rather than establishing yourself as a market leader.

Despite the excitement surrounding AI, its current state of use shouldn’t be overstated. Just 40% of respondents in a survey published in Forbes in January 2020 said that they are currently implementing at least one AI project or plan, or that they plan to do so in the near future. However, in the same survey, over 90% of respondents indicate that they plan to implement one of the patterns of AI in the short term, if not already.

Use of vendor-delivered solutions has shortened launch windows, lowered startup costs, and hastened time to value. The SaaS sector is particularly keen on delivering AI-based tools that are continually optimized.

“Cloud vendors are stoking demand for AI technology by offering a growing number of tools and services that make it easier to develop, test, enhance, and operate AI systems without big upfront investments,” writes a panel of Deloitte analysts. They cite machine learning-optimized hardware, APIs for speech recognition/NLP, productivity-boosting automated machine learning modeling tools, and AI development workflow platforms, concluding that, “All this is making it easier for enterprises working in AI to adopt cloud-based AI services.”

Implementation of AI Across the Organization Requires Greater IT Efficiency

Growing use of AI in other departments has admittedly created a high support burden and a need for top talent in IT. In order to manage this workload, IT can automate some of their own processes, gaining efficiency and enhancing productivity.

“By embracing AI augmented automation, IT teams can better learn the skills of AI and position themselves to have more effective partnerships with peripheral business units,” observes Gartner. They predict that, by 2023, 40% of I&O teams in large enterprises will leverage AI-backed automation, “Resulting in higher IT productivity with greater agility and scalability.”

One example of this type of productivity-boosting automation comes in the form of change risk prediction. ITIL CAB review processes are manually intensive, and they can also use highly subjective assessment techniques. The need for approval for each deployed change dramatically slows down business performance and hinders agility. AI/ML models can automate the process of discovering risk factors, scoring risks, or approving low risk changes so that the CAB can concentrate on helping teams reduce or mitigate change risk.

Use of AI can uncover opportunities for innovation in IT, allowing for the discovery of better processes, new workflow platforms, and insights that lead to improved performance across all enterprise markers. 

“The next evolution of automation will be smarter, more aware, and more contextual,” opines Jiayi Hoffman of Tech Beacon. “AI and machine-learning technologies will discover hidden resources and threats, uncover patterns, filter the noise, and aid decision making.”

Hoffman also predicts that machine learning algorithms will accelerate the development of built-to-purpose AI tools, allowing IT leadership to find answers to their problems faster while receiving prescriptive recommendations on how to optimize performance, even as conditions fluctuate.

“Jobs involving data entry and ticket management will shrink,” Hoffman anticipates, adding that, “This is good news: The algorithms will do more of the grunt work while people will focus on more strategic jobs related to managing and analyzing the data.”

On the whole, most people anticipate transformative benefits to IT and the organizations they serve. According to one survey, 87% of respondents agree that AIOps tools are delivering value, “Through proactive IT operations and improved hybrid infrastructure resilience.”

IT Can Act as Trailblazers for Productive Organization-Wide AI Use

AI use is growing, both in experimental and practical capacities. Use of vendor-developed tools offers greatest speed to value and the potential for landmark process shifts. 

Organizations increasingly rely on IT to ensure that their AI projects can be profitable and operated with minimal tradeoffs. Use of internal AI tools will make IT more efficient, and capable of managing it all without becoming overburdened. The efficiencies afforded by AI frees up resources for innovation, allowing IT to be a driver of value within the organizations it serves. 

IT leaders will be tasked with using their knowledge and proximity to AI tools to push organizations in a more ethically-driven direction, helping prevent unintended consequences that can come from biases and other emergent flaws. As partial gatekeepers of which solutions enter their organizations, IT can also level demands at vendors to introduce specific ethics guardrails.

IT leadership should see AI not just as something that can benefit them, too, but also something for which they can be the true drivers of value and ethics-based decision-making within their organization. Assuming a leadership role will improve implementation of AI as its presence in our industries ⁠– and society as a whole⁠ –  grows.

Want more information on how AI & ML Can Help You Deliver Better, More Reliable IT Services Faster? Watch our recent webinar: “Artificial Intelligence in IT Service & Change Management: A Primer

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