IT teams, don't fall behind the AI curve

In the new age of AI, companies are looking for ways to integrate the groundbreaking technology cross-functionally to enhance efficiency, innovation and inform decision-making. Like any business department, IT teams are eager to learn how AI and automation can help alleviate more of the menial and burdensome tasks that consume large portions of their workday.

IT professionals are overworked, burnt out and feeling increasing pressure to do more with less. According to a recent survey of IT professionals, 78 percent reported that work stressors are preventing them from upskilling, and 44 percent said their workload is outweighing their ability to be productive. AI and automation can significantly help alleviate these burdens, but they must be implemented strategically and securely.  

Challenges in AI Adoption

Before AI can truly be embraced, one of the biggest issues to overcome is data governance. To make AI effective, you need context, which can’t be achieved unless you input your own business data. However, you need clear policies and procedures around what data can be fed to AI platforms and assign individuals specific responsibility for ensuring only the right data is exposed to AI, and done so securely. You cannot put your business data at risk for the pursuit of leveraging AI. Preparing data to be fed to AI can be a highly manual process -- it takes significant time and deep knowledge not only around the data itself but also how it will be used to inform AI. Introducing data governance practices that have regular intervals of data review should be implemented so data does not become stale or inaccurate. You need to ensure you know where your data is, and enforce proper governance and AI access to gain the context you need.  

Another significant barrier to AI adoption is the ever-expanding role of the IT manager. These professionals are constantly burdened with more and more responsibilities, and preparing their company to embrace the AI era is yet another task added to their plate, without being able to offload any other burdens.  For example, the printers that break are still breaking and must be fixed; there is an endless barrage of network configuration changes that must be managed and properly documented; the users who need help resolving a connectivity issue still need help -- all of these tasks continue to add up as new technology is introduced, but seemingly no tasks are ever unloaded. 

The FUD around AI is another serious challenge to AI adoption. Everywhere from the media to the water cooler, there is too much focus on replacing jobs and human workers with AI, which can be a deterrent for IT professionals. Why should workers be eager to learn and implement technology that could replace them? 

Then there is the significant skills gap. There is a fairly steep learning curve when it comes to AI -- knowing what tools are available, how to use them properly and the best/most effective use cases. Plus, the rate of change when it comes to AI is unlike any major technology shift we’ve seen to date. Just when you think you’re mastering one aspect of effectively leveraging AI, the landscape changes and you’re back to playing catch-up. Confounding the matter, there are not many formalized training programs and certifications available to help professionals gain the skills they need in AI. 

Overcoming the hurdles

While each of the above issues pose a hurdle on the path to embracing AI, they can be overcome. When it comes to data governance and struggling to make the time necessary to do this task correctly, IT professionals have no choice but to turn to automation to help free up more of their time. There are plenty of automated tools available today that are uncomplicated and fit seamlessly into existing workflows, and can free up vast amounts of time. Think proper configuration changes, documentation, backups, ticket processing, onboarding and offboarding users, etc. Integrate the right tools so you have the time needed to prepare your company’s data and dedicate more time to learning AI.  

In addition to leaning on automation, IT professionals need to look at outsourcing tasks that aren’t seen as critical to advancing organizational transformation. For example, everyone expects the network to simply work -- IT professionals can’t be spending precious hours of their day ensuring this is the case. Get the proper tools and if needed, outsource this task, so that it’s considered a given without eating into time you could be spending on AI and other transformative initiatives.

When it comes to addressing the FUD around AI and automation, educate yourself and your teams with accurate, timely information. The reality is, AI is not going to massively replace human workers. The efficiency of AI is high, but its creativity is low -- humans are creative problem-solvers, AI is not. IT professionals must help lead the mindset change not just among their own teams, but across other departments as well. AI will support workers to be more productive, effective and innovative, which has the opposite effect of putting jobs in jeopardy. IT teams are burdened with not only leading the charge in implementing AI in their own department, but also working with other departments to determine the best use cases and areas in which AI can help. IT may need to go through the same process of alleviating job replacement fears with other workers that they had to do for themselves.  

To close the AI skills gap, IT professionals must be very proactive in learning AI skills. You cannot afford to get behind the eight ball, or you’ll never catch up to competitors. The rate of change is simply too fast. To learn the skills, get involved with industry associations that offer certifications and trainings. Find YouTube tutorials. Let AI teach you how to use AI -- seriously, have conversations with these platforms to learn what it can do and what its limitations are. You have to be your own teacher, give yourself assignments and relevant reading for homework, conduct your own experiments with AI to get a feel for what will be the best use cases in your organization. Waiting for someone to come along, take you by the hand and show you the AI ropes is not going to get you anywhere.   

Finally, it is critical to quantify your results of early work with AI. Whether in the IT department itself or in another department like compliance, legal, HR, etc. -- figure out what can really help move the needle in terms of success and productivity, find the quick wins using AI, and quantify your results to demonstrate clear ROI. This will help build confidence in AI among critical stakeholders, from the C-suite to department heads, and win you more support for dedicating additional time and resources to finding other areas of the business that can be positively impacted by AI. In the process, you’ll be adding even more value to your own role and will be seen as even more essential to the organization.

For most organizations, the benefits of AI might feel slow and limited at first -- but the drawbacks of failing to implement AI will be felt acutely. Companies cannot afford to fall behind the AI curve while their competitors experiment with and eventually master AI. It will be incredibly difficult, if not impossible, to ever catch up. IT professionals cannot afford to wait for more formalized training programs to become available, or use the excuse that they don’t have enough time in their day to take on AI. Take the initiative to learn, take ownership of your time and lean on tools that can free up more of your precious time, and forge your own path forward in the AI era.

Image credit: AndreyPopov/depositphotos.com

John Harden is Director of Strategy & Technology Evangelism, Auvik.