(gigaom.com) — When I founded IPsoft in 1998, one of my main goals was to decrease the incredible amount of time IT professionals spent managing applications and tools. Over the previous decade, IT experts had become so entangled in mundane, repetitive chores, that they ended up losing the passion and creativity that drove them to the industry in the first place.
That was 14 years ago. It is much worse today. According to a recent study by performance management solutions provider BlueStripe Software, 68 percent of IT executives have invested in more than three separate application and transaction management tools, and 64 percent have invested in more than six. The result: 78 percent said their management system had become so unwieldy that they could not pinpoint where transactions slow down.
IT has entered a state of bloated chaos. Luckily, there is relief ahead. Companies like us, as well as IBM, HP and NASA, are shedding light on a new era of IT. Enter the era of autonomics.
Autonomics offer many benefits to IT departments. As the name implies, autonomic technologies eliminate or reduce human intervention required to resolve problems. Immediately after implementation, they begin to observe how engineers troubleshoot problems and execute tasks. Once the learning curve is complete, the virtual engineers become the employees.
Their adaptive nature allows them to look at each task individually and use their accumulated knowledge to execute the task in the most efficient and effective manner. And as a result, they are able to execute and oversee large amounts of routine and level one and level two IT tasks, such as database management, life-cycle application support and systems monitoring. They offer the best of both worlds, combining the work capabilities of a human with the low error rate of a computer.
But most importantly, autonomics uplift human engineers. Freed from routine and menial tasks, IT professionals can focus on creative and innovative pursuits.
It is helpful to visualize autonomic technologies as an immune system layered on top of an IT department. Most of the time, the immune system allows things to run smoothly. However, the inevitable agitator will rear its head. Like antibodies attacking a virus, autonomic systems will attempt to fix problems based on how similar situations were resolved in the past. The system will only alert the owner if all the attempted remedies have failed. While your immune system might make you aware of intruders via a runny nose, autonomic technologies usually send a more blatant signal, i.e. an error report.
Part of the beauty of autonomic technologies lies in their ability to integrate with existing service platforms. Many enterprise customers already have ticketing tools in place, and they’re not open to replacing them. Instead of replacing a company’s ticketing system, autonomic technologies can make the system run more efficiently by learning which employee is best able to resolve a specific incident and assigning the ticket to him or her.
Budgets can also be drastically reduced, because artificial intelligence can now take much off the plate of employees. We have seen some of our clients successfully automate upwards of 83 percent of routine IT tasks after implementing the technologies for one year, helping them save one-third of their IT budget. These new technologies can also keep IT departments from devolving into a tangled web of separate systems.
As IT departments become increasingly essential to successful companies, executives will soon have to make important decisions about their future. Now is the time to start looking for ways to reshape the department to perform the same tasks more quickly and efficiently. Autonomic technologies are a glimpse into an optimal future for IT, where assignments are executed by technologies, and employees have time to develop ideas that drive business.
Chetan Dube is the president and CEO of IPsoft, a provider of autonomic IT services to corporations worldwide. Prior to founding IPsoft in 1998, Chetan was an assistant professor at New York University, where he focused on deterministic finite-state computing engines.
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