The Dark Side of Automation: How AI is Replacing Human Workers - Vishwak Tummala_ISA 1

By - Vishwak Tummala

Although programming and coding skills are in high demand, ChatGPT and other AI technologies may eventually fill some of the voids. According to, software developers, web designers, computer programmers, hackers, and data scientists are among the tech occupations that are "very susceptible" to AI technologies "displacing more of their labor." This is due to the fact that artificial intelligence (AI), such as ChatGPT, is capable of pretty precise number crunching.In fact, , cutting-edge technology like ChatGPT may be able to create code faster than people, allowing for the use of fewer workers overall.

What required a group of software developers may just require some of them, he continued. Tech companies are already thinking about using AI to replace software engineers, such as ChatGPT maker OpenAI. Nonetheless, professor Oded Netzer of Columbia Business School believes that.

 ChatGPT and similar types of AI might have an impact on all media positions, including those in advertising, technical writing, journalism, and any position involving content creation. This is so because AI is proficient at reading, writing, and comprehending text-based data, she continued. "You'd expect generative AI technologies to scale up on analyzing and interpreting massive volumes of language-based data and information," Madgavkar added. Paul Krugman, an economist, wrote in a New York Times opinion piece that ChatGPT might be "more efficient than humans" in reporting and writing. AI-generated content is already being tested by the media sector. Several articles on the tech news site CNET were written using an AI technique similar to ChatGPT, despite the publisher's protests.

The fact that IT is not entirely responsible for implementing the AI-based advancements that will impact everyone from manufacturing employees to office administrators puts it in an unusual position. Also, IT is in charge of utilizing AI inside to boost the effectiveness of how its own staff provides technology and services. This is especially true for IT operations, which manage increasingly complex IT systems and hence introduce subtler errors into them. According to Will Cappelli, the CTO of Moogsoft and a former Gartner analyst who created the term "AIOps" as a shorthand for AI operations, this is leading to a large data volume problem that can only be solved by machines. Specifically, this entails removing "noisy" data produced by IT systems and determining whether data.

Others believe that the more IT applies AI to operations problems, the more important it will be for humans to pull all the puppet strings. At the end of the day, machines need domain experts to tell them how to operate in certain situations.     

Software developers may be programming the machines, but operators will be the ones distilling organizational and systems knowledge into "run books" that AI will apply to various IT Ops problem sets, said Patrick Zimmer, principal at WholeStack, an IT services firm that manages and operates systems.

According to Robert Reeves, co-founder and CTO of Datical, a company that sells tools to simulate database setups, a fair rule of thumb is to assume that any position that reacts to tickets will see an impact. AI is already being extensively used by several firms to lower ticket counts. According to data it has obtained, AIOps vendor BigPanda is witnessing some organizations cut tickets by 75% to 99%. According to ServerCentral Turing Group's Caulfield, front-line support roles will see the largest changes as ticket-based operations models fade. He clarified that Caulfield is explicitly referring to the initial point of contact with a client or end user.

A good rule of thumb is to presume that any position that responds to tickets will have an influence, says Robert Reeves, co-founder and CTO of Datical, a business that sells tools to simulate database installations. Numerous businesses have already made substantial use of AI to reduce ticket counts. BigPanda, an AIOps vendor, reports that certain organisations are reducing tickets by 75% to 99%. Front-line support positions will undergo the biggest changes, according to ServerCentral Turing Group's Caulfield, as ticket-based operations models disappear. He made it clear that Caulfield's reference to the first point of interaction with a client or end user is explicit.

 

Availability and performance management will have to shift from observation to analysis, incident management will largely disappear, and problem management will have to shift from actually doing diagnostics to validating results, Cappelli said.