For the longest time, business executives have complained about the inability of IT teams to keep pace with evolving business needs. Now, the proverbial shoe may be on the other foot.
A survey of over 1,000 senior executives at U.S. companies with more than $500 million in revenue, conducted by Infosys, finds nearly three-quarters (71 percent) are concerned that the pace of technology change is exceeding their organizational ability to incorporate it into operations.
More than a quarter (28 percent) said lack of internal technical skills prevents organizations from embracing new technologies. Two-thirds of respondents (66 percent) said they are increasing spending on upskilling and training to close any skills gap. More than three-quarters (77 percent) note they prefer an employee who is knowledgeable in many different technologies rather than an expert in just one.
Navigating AI implementation
Advances in artificial intelligence (AI) should make it possible for IT teams to manage a wider range of technologies. However, due to the size of internal IT teams, they are limited to master all required skillsets. In the short term, business consultants and their managed service provider (MSP) allies will play a critical role in helping organizations operationalize AI in all its forms.
Less clear is to what degree organizations leveraging AI will be able to manage various processes themselves. There is little doubt that internal IT teams, thanks to AI, will be able to programmatically provision IT resources and even troubleshoot them at much higher levels of scale. The depth of technical expertise needed to, for example, determine how a new type of cybersecurity attack may have compromised physical networks is likely to require some uniquely human expertise.
Even large language models (LLMs) will only recognize IT events they have been trained to. It’s also important to remember that all AI insights and recommendations are probabilistic rather than deterministic. This means humans need to check to ensure accuracy but also to determine why the AI model got something wrong.
The role of MSPs in the AI era
MSPs are most likely to diagnose the root cause of these types of issues rather than machines. Organizations will be keen to leverage AI to drive specific outcomes. However, when something goes awry, they will still need to call in a specialist. Given the level of scale AI will enable the number of things that might go wrong will be substantial. After all, it’s one thing to be wrong; it’s another to be wrong at scale.
MSPs should expect a certain amount of ongoing irrational AI exuberance in the months ahead. As business leaders navigate to optimize the use of AI to automate operations, these AI models will need to be supervised. Additionally, there will also be new classes of tasks that, without AI likely would have never existed. It should become much more feasible for many smaller organizations to leverage AI to compete more effectively than ever against larger rivals as they take advantage of AI-infused services.
Each MSP will need to determine how they will add value in the age of AI. There’s no turning back now since it’s clear the AI genie is never going back into the bottle.
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