Dive Brief:
- Despite enterprise adoption of AI-powered software testing tools, leaders and IT staff want guardrails, according to a Censuswide survey commissioned by Leapwork published Tuesday.
- More than two-thirds of respondents indicated high levels of trust in tool performance, according to the survey of more than 400 IT leaders at U.S. and U.K.-based organizations. Just 1 in 10 organizations aren’t convinced AI tools will improve testing efficiency and effectiveness.
- Enterprises still want a human in the loop. Nearly three-quarters of organizations believe human validation has become a staple of the process and that will continue for the foreseeable future.
Dive Insight:
Though AI has long been associated with potential job losses, enterprises have shifted their focus to building skills within the existing workforce. Companies want a human-in-the-loop approach to validate accuracy and security, and the proliferation of AI-powered assistants has kept workers in control.
More than 7 in 10 CEOs say generative AI adoption will not fundamentally change the current number of jobs, and 27% believe the technology will create more jobs than it eliminates, according to a KPMG survey published last month.
Analysts have urged companies to use AI to augment workers rather than replace them.
The U.S. Bureau of Labor Statistics predicts software developers, quality assurance analysts and testers to grow at a “much faster” rate than the average of all occupations from 2023 through 2033. In its report, the agency credited AI, in part, for driving the increase.
About 140,000 job openings for software developers, quality assurance analysts and testers are projected for each upcoming year for the next nine years, according to BLS data.
But that doesn’t mean job functions will stay the same. A mass upskilling sprint is set to hit the engineering workforce, according to Gartner. As generative AI adoption reshapes workflows, around 4 in 5 engineers will need to build new skills by 2027, Gartner analysts predict.
Enterprises across industries have started assessing where and how to embed AI in the IT workflow, hoping to enhance the experience and boost productivity. Like with any initiative, pitfalls lie ahead.
“Even in organizations with mature practices, developers often use AI tools in the narrow context of generating code,” Gartner analysts said in an August research note. “Focusing solely on coding productivity will restrict the effectiveness of AI tools.”
