AI Could Cause a Shakeup in $58 Billion Productivity Tools Market, Predicts Gartner
As AI adoption becomes more widespread, new research released by Gartner demonstrates the ways the technology will transform hiring, workflow, and data and analytics in the next few years.
“In 2026, the boundaries between human, machine and organizational intelligence will continue to blur,” Gartner distinguished VP analyst Rita Sallam said in a statement. “Businesses rely on data in unprecedented ways, with AI systems not just supporting us, but collaborating as partners. These predictions offer leaders a roadmap to prepare for the opportunities and challenges that lie ahead.”
Gartner predicts that by 2027, generative AI will cause the first true shakeup in the $58 billion productivity tools market in 30 years. D&A leaders will seek tools with interfaces, plug-ins and formats suited to working with agentic AI. But the technology will still only be as good as the organization using it.
“Expecting AI or Gen AI to compensate for delayed upgrades, siloed teams and years of technical debt is wishful thinking,” Gartner director analyst Georgia O’Callaghan said in a statement. “D&A leaders must make sure their data is AI-ready, prevent exposing the wrong data to the wrong people, and avoid inaccuracies, misunderstandings and hallucinations with a well-designed context layer.
A Gartner survey of 353 D&A and AI leaders conducted from November to December 2025 found that one in five worried about the costs of investing in AI.
“D&A leaders must achieve clarity and focus on ROI to better achieve the growing AI goals and ambitions of their organizations,” Gartner VP analyst Adam Ronthal said in a statement. “D&A leaders must realize they are responsible for delivering real value in the midst of all this AI hype and fears of an AI bubble that might burst.”
With the technology quickly changing, teams need to budget for training employees to keep up with new tools.
“By focusing on skills, mindset and behavioral change, they can unlock both individual and collective potential,” Ronthal said. “This will increase employee engagement and productivity, making their organization more adaptive to change.”
Gartner analysts predict that testing for workplace AI proficiency will be part of 75% of hiring processes by 2027.
“D&A leaders should encourage rigorous, data-driven measurement of skills to surface deficits that stand between their AI ambition and IT workforce readiness,” Sallam said.
AI-native startups have the potential to achieve enormous capital efficiency by embedding AI into their workflows and developing proprietary AI and intuitive user interfaces that can produce measurable business improvements.
“D&A leaders can learn from these AI-first start-ups that grow and get to profitability quickly by focusing on fewer employees with significant ownership, instead choosing technology-agnostic, full-stack engineers and generalists who can quickly adapt to new AI tools,” Sallam said. “This approach allows companies (and teams) to scale efficiently with fewer resources.”
