ORLANDO — With an AI-first strategy, data management vendor Atlan has shifted the tasks that internal workers, such as marketers and data engineers, do, showing that as AI advances, roles are changing across industries.
The India-based AI vendor has made internal changes requiring its engineering teams to teach AI agents to code rather than code themselves, using either Claude Code, Cursor, or another AI coding tool. On the marketing side, employees are encouraged to build agents that they train to build marketing campaigns, rather than building the campaigns themselves.
“Generally speaking, as a company, we’re all trying to embody the concept of everybody can be a builder,” said Austin Kronz, director of data and AI strategy at Atlan, during an interview at the Gartner Data & Analytics Summit 2026. “It makes our development process significantly more agile. It allows us to act on ideas a lot faster than we would have.”
The Great Concern
The change Atlan made in the roles of its data engineers and marketers is an example of how one company has responded to the pressure many organizations face as AI automates some jobs and tasks, such as coding. In recent months, many companies have eliminated jobs while blaming AI technology. It’s an employment crisis that even data engineers and data scientists are not immune to.
“They’re all worried about their jobs,” said Paul Bell, global head of data trust and integrity at Entain PLC, an international sports betting and gambling company, in an interview.
While that concern seems well-founded with headlines about tech companies like AWS and Block laying off people, and Oracle expected to eliminate teams and jobs, Gartner research has found that investments in data and analytics teams remain high. While AI is affecting jobs, it is more — for now — reorienting how jobs are perceived. Instead of employees being valued by the description of their jobs, they are now valued more by the skills they contribute and by how they work with AI technology and AI agents.
Humans and AI
“Your role may shift from being a developer to acting more as a validator, where you review and adjust work by others, humans and agents,” said Gartner analyst Georgia O’Callaghan, during a keynote presentation at the tech research firm’s conference.
“The value of human talent and skills will still sit at the core of delivery teams, but these teams will now combine human expertise with AI agents to make more productive AI-powered fusion teams,” O’Callaghan said.
Moreover, a ripple effect of many companies trying to use AI to automate is that they will likely have to upskill the employees they keep, because companies’ needs change depending on what AI is used for.
This is why enterprises and businesses must pay close attention to which areas they want AI to automate and which they want people to lead.
“That’s a tougher decision for most business leaders because they have to say strategically, ‘this is the area where we want AI doing the work, and we’re going to navigate the change and the implications of that effectively,'” Gartner analyst Helen Poitevin said during an interview.
She added that businesses will find success if they give their human workers a chance to help decide what automating with AI agents or AI technology looks like.
“If they’re motivated to say ‘Okay, let’s make that experience better and be part of designing it,’ they will feel more engaged and more ready to accept the substantial change it means for their day-to-day work,” Poitevin said.
Experience Versus Skill
Another change that’s happening comes on the hiring front. For many organizations, the talent they need is no longer as much about experience and more about the skills potential employees already have.
“We’ve refocused hiring individuals that are skilled with understanding how to prompt, specifically data professionals that understand the under-the-hood abstraction of what’s happening with these models and folks that are willing to test and learn and fail,” said Raj Tiwari, vice president of technology development and analytics at Stanley Martin Homes. “Curiosity … goes a long way. It’s really more of an individual perspective rather than tenure at this point.”
He added that, for the most part, Stanley Martin Homes is human led, but the company is developing AI systems that take the human completely out of the loop, such as creating a closing house journal (the document that provides the final terms of a house loan).
“What we’ve done is extracted that and essentially modeled end-to-end with automation back into our ERP system,” Tiwari said. “That’s low-value effort, and hopefully humans can move to higher-value efforts.”
The continuous change in hiring and work due to AI technology will always be in flux because of the immaturity of the technology, said Amy Lenander, chief data officer at Capital One.
“We’re all learning as we go through this,” Lenander said. “It’s yet to be seen what talent mix we’re going to need in this AI world.”
