Estimated reading time: 3 minutes
The swift adoption of AI across businesses, both within the software engineering function and beyond, is increasing the need for managers, according to a recent piece of research.
“As firms adopt AI, there’s a shift towards [adding] more managerial positions,” says Mireia Gine, professor at IESE Business School, who conducted the research alongside three co-authors. “Firms become more management-intensive overall.”
AI systems are typically trained to take on more rote tasks, and require ongoing monitoring, tuning, and integration into business processes, creating more manager-level work.
The adoption of AI by companies also changes what to look for in managers. Gine says that past discussion about ‘soft’ and ‘hard’ skills among workers should be replaced by a new understanding of cognitive skills.
“We have to recognize that AI is radically different from prior enterprise technologies,” Gine adds. “AI is a technology that mimics recognition, and helps learn to take decisions and actions. Understanding how to manage teams in a way that AI can reflect and amplify the best elements of that process, and not the worst, will be vital.”
Changing the face of management
The researchers analyzed 370 million job vacancies across the United States of America between January 2010 and December 2022, encompassing the entire evolution of AI applications in the workplace.
The study found a clear shift in the desired qualities for management positions to focus on creativity in problem solving, stakeholder management, and focusing on revenue growth. “Those are the skills that came out as being significantly more in demand as firms adopt AI,” says Gine.
While it’s difficult to pinpoint the direct impact of AI alongside macroeconomic shifts during this period, the researchers used statistical models to try and isolate how much of an impact AI adoption had on the changing demand for managers during this period.
Some of the most desirable skills, including the ability to manage people and to see projects through to completion, remain the same. However, the change in how code is produced and deployed will require engineering managers to shift their approach.
“If you are interacting with AI algorithms in-house or outside, you’re going to have to be thinking about how you integrate the workflow between the humans and the AI protocols,” says Gine. “You’re going to be developing strategies to supervise these two workforces.”
The impact on engineering
“We will certainly see similar trends for software engineering managers and product managers, in that critical thinking, decision making, and interpersonal skills will be more important than now-automatable rote tasks,” says Rachel Cohen, chief operating officer at the software agency Silicon Society.
Cohen believes that software engineering managers will have to demonstrate a new skillset – the ability to review and detect AI-written code, and parse through it to ensure that engineers that work under them have properly checked their work.
Cohen’s colleague, Frank Fusco, CEO of Silicon Society, foresees a similar shift in the software engineering space. “As more and more pure engineering tasks become automatable, the ROI equation shifts heavily toward deciding what to build and why, coordinating a mix of human and AI resources,” he said. “Managers of technical teams will continue to be hands-on and product-oriented, and the role will continue to evolve significantly in ways we can’t predict now.”
