Recent advancements in artificial intelligence will soon represent the biggest leap in computer technology since the creation of the internet. Machine learning algorithms stand ready to revolutionize the way we interact with computer systems and assets, forever changing the way we look at the technology industry. These cutting-edge A.I.’s will take digital autonomy to a whole new level, creating unique opportunities to improve the efficiency and accuracy of current systems. Advanced A.I. will be able to bridge the gap between current autonomous ITSM software, like SysAid change management software, and an almost entirely self-sufficient software solution to manage ITSM on a larger scale than ever before.
Machine Learning and Artificial Intelligence
Machine learning is an old concept that has been around for a long time. In the early days of computer A.I., programmers could only dream about software that was able to interpret and learn from the data given to it. Machine learning, in essence, attempts to mimic the human mind and its ability to solve problems and draw conclusions from data and stimuli. The development of neural networks and the ability for these programs to make decisions is key to machine learning.
Neural networks are a huge development in software A.I., taking an entirely new direction in software creation. Instead of specific instructions and outcomes being fed to the machine to process, neural networks are given parameters to extrapolate conclusions based on probability. Feedback loops enable the program to begin to learn patterns in the data and modify future conclusions using these newly learned patterns. This opens entirely new applications for A.I. automation in almost every technology field.
While these terms are often used interchangeably, the subtle differences between traditional A.I. and machine learning software are distinct. The potential for machine learning programs to automate tasks goes well beyond what classic A.I. is capable of.
What Does Machine Learning Mean for the ITSM Field?
Automation in ITSM has grown by leaps and bounds in the last decade, allowing managers to reduce workload and implement service management procedures with accuracy and ease. ITSM software can drastically improve overall efficiency, creating organized lists of assets and their required upkeep. However, even with software handling a large portion of the analytical work involved with service management, the need for human input and control limits these programs. Even the most technically advanced ITSM software is still limited by the instructions laid out in its programming. It’s unable to learn and make its own decisions or recommendations to IT service management staff, or further automate service management tasks beyond data collection and minor maintenance scheduling.
Machine learning systems won’t be restricted by these boundaries. Not only will new A.I.’s be able to collect data, receive and file incident reports, and monitor assets for changes, they’ll be able to use predictive algorithms made possible by machine learning to suggest, or even implement, software and hardware change all on its own. Software is already capable of many of these tasks, but the new wave of machine learning software will take it to an entirely new level.
These systems will be able to spot patterns and recognize deficiencies in the same way a human would. Advanced ITSM systems able to predict future technology cycles, accurately predict end-of-life for current assets, and make intelligent decisions on new software, patch maintenance, and hardware upgrades is well within the realm of possibility. It’s not unimaginable to think that machine learning A.I.’s could handle nearly every task currently assigned to service management staff entirely on their own.
The Human Element
So where does this leave the future of human involvement in ITSM? The obvious answer is that a human being will still be needed to monitor advanced A.I. and ensure things are working smoothly. It’s unlikely that the consistently small size of it service management teams will be downsized with the integration of new, more intelligent software. The work these employees do will be adapted to fit the new system, and their involvement will still be critical to the success of these new programs. While these revolutionary new systems will bring dramatic changes to the ITSM field, it’s a certainty that the human element will still be necessary for them to function.
As research and development takes A.I. systems further into the future, the technology industry will begin to be shaped by these powerful new tools. Every field of expertise will need to adapt to the changes these systems bring about. Only time will tell just how these changes manifest themselves, but one thing is guaranteed – machine learning software is coming and it’s poised to revolutionize the way we interact with and use technology.