While there is widespread speculation that AI will drastically reduce customer service headcount, currently only 20% of leaders have reduced agent staffing due to AI, according to a survey by Gartner, Inc, a business and technology insights company.
A Gartner survey of 321 customer service and support leaders conducted in October 2025 reveals a more nuanced reality: 55% report stable staffing levels while handling higher customer volumes—underscoring AI’s role in boosting efficiency rather than eliminating jobs.
“Customer service and support leaders should avoid framing AI initiatives solely around headcount reduction,” said Melissa Fletcher, Senior Principal, Research in the Gartner Customer Service & Support practice. “Instead, focus on incremental transformation and workforce augmentation. Leaders should plan for new roles, leverage central resources, and communicate transparently about AI’s impact to manage expectations effectively.”
The survey also found that 42% of organizations are hiring specialized roles—including AI strategists, conversational AI designers, and automation analysts—to support AI deployment and management. Looking ahead, Gartner forecasts that by 2027, half of organizations anticipating major AI-driven workforce cuts will abandon those plans as the vision of ‘agentless’ service proves elusive.
Gartner AI Use Case Insights is an interactive tool that helps technology and business leaders efficiently discover, evaluate, and prioritize AI use cases to potentially pursue. Clients can search over 500 use cases (applications of AI in specific industries) and over 1,000 case studies (real world examples) based on industry, business function, and Gartner’s assessment of potential business value.
That said, as AI usage increases, Gartner experts also warn of the importance of being aware of possible AI-related blind spots stemming from overlooked risks and unintended consequences of generative AI (GenAI) adoption.
Gartner experts opine that Chief information of officers (CIOs) must proactively address these hidden challenges to ensure GenAI value realization and avoid AI project failures.
“GenAI technologies and techniques are evolving at an unprecedented pace, matched only by the surrounding hype, which makes it challenging for CIOs to navigate this dynamic landscape,” said Arun Chandrasekaran, distinguished VP analyst at Gartner.
While organizations often focus on immediate GenAI challenges such as business value, security and data readiness, they may overlook critical blind spots because these are second- or third-order effects that are not often visible upfront. Risks like shadow AI, technical debt, skills erosion, data sovereignty demands, interoperability issues and vendor lock-in represent hidden undercurrents that can undermine long-term success.
Gartner predicts that by 2030 these blind spots will create the dividing line between enterprises that scale AI safely and strategically and those that become locked in, outpaced or disrupted from within.
“To address these risks, CIOs should define clear enterprise-wide policies for AI tool usage, conduct regular audits for shadow AI activity and incorporate GenAI risk evaluation into their SaaS assessment processes,” said Chandrasekaran.
Gartner delivers actionable, objective business and technology insights that drive smarter decisions and stronger performance on an organization’s mission-critical priorities.
To learn more, visit gartner.com.
‘GenAI technologies and techniques are evolving at an unprecedented pace which makes it challenging for CIOs to navigate this dynamic landscape.’ – ARUN CHANDRASEKARAN, Gartner
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