“The entire history of software engineering is one of rising levels of abstraction,” says Grady Booch, IBM chief scientist of software engineering, and premier thought leader in the technology space.
If you have used ChatGPT, you probably gave thought to the construction of your query — but no thought at all about the construction of its supporting infrastructure — servers, databases, networks, or even its large language models.
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Welcome to the age of abstraction. And the pace of abstraction for both technology and business professionals is accelerating just as quickly — to the point where one no longer requires in-depth knowledge of the plumbing underneath applications and devices — or, increasingly, even the data science.
Some refer to the emerging constellation of technologies — artificial intelligence, machine learning, and advanced robotics (both software and physical) — as the “new automation,” which will handle many rote or low-level tasks, but increasingly taking on more complex jobs. The catch is that it’s going to take a range of skills, now in short supply, to effectively introduce the “new automation.”
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Greater automation across the board means more self-service for all. A recent survey of 439 IT managers and operators, published by Stonebranch, finds self-service automation is booming for both technologists and non-technologists. Just about all, 92%, empower end-users from data, cloud, development, and line-of-business teams to execute their own workflows, tools, and processes.
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AI is already playing a part in handling technology tasks. A survey released by OpsRamp finds more than 60% of companies adopting AIOps, which applies AI to monitor and improve IT operations themselves. The greatest IT operations challenge for enterprises in 2023 was automating as many operations as possible, cited by 66% of respondents. The main benefits of AIOps seen so far include reduction in open incident tickets (65%); reduction in mean time to detect or restore (56%), and automation of tedious tasks (52%).
