Service and Support Leaders Expand Human Agent Responsibilities

Eighty-five percent of customer service and support leaders are expanding human agent responsibilities as artificial intelligence reduces contact volume and shifts work toward higher-value tasks, according to Gartner.

Just 31 percent have implemented or are planning frontline workforce reductions through layoffs in response to AI through the first quarter of 2027, the firm says.

Gartner also found that workforce transformation is under way, with 80 percent of service and support leaders saying they are under pressure to make workforce changes as AI reduces contact volume and improves agent efficiency.

“Service and support leaders need a plan for how they will reshape their workforce for AI’s impact; otherwise a plan will be handed to them,” says Kathy Ross, a vice president analyst in the Gartner Customer Service & Support Practice.

Rather than pursuing widespread job cuts, more organizations are taking a measured approach to managing these shifts, the firm says, noting that 63 percent of service leaders are reducing frontline headcount gradually through attrition, while reallocating agent capacity toward higher-value responsibilities that support growth, loyalty, and long-term efficiency.

“As AI begins to automate simple work, that success creates a new challenge,” says Eric Keller, a senior director analyst in the Gartner Customer Service & Support Practice. “Service leaders must decide whether to simply do the same work at lower cost or to redeploy human agents into roles that AI cannot replace and that customers value most.”

Rather than using AI efficiency gains solely to reduce costs, most organizations are expanding and redefining the role of the human agent, the survey found, with 85 percent of service leaders adding tasks and responsibilities to frontline agent roles, while 75 percent shift agents into entirely new roles within the service and support organization.

Despite external expectations for rapid workforce reductions, large-scale layoffs remain the exception rather than the norm, Gartner says further, underscoring a broader shift toward workforce redesign rather than elimination.

As agent roles evolve, human interaction continues to play a critical role in customer trust and decision making. But a separate Gartner survey found 54 percent of customers trust human agents more than AI for product or service recommendations, compared with 32 percent who trust AI more, reinforcing the importance of human involvement in complex, high-stakes, or advisory interactions.

“Organizations that only use AI to reduce costs risk missing a strategic opportunity,” Keller says. “The real advantage comes from combining AI efficiency with human judgment, empathy, and experience to deliver outcomes that technology alone cannot.”

CMOs Allocate 15.3 Percent of Budgets to AI, but Only 30 Percent Can Scale AI

Marketing budgets remain flat as CMOs pressed to deliver AI-enabled growth and efficiency, Gartner finds.

C hief marketing officers are allocating an average of 15.3 percent of their marketing budgets to artificial intelligence initiatives, yet most marketing organizations lack the maturity to scale those investments, according to a survey by Gartner.

While 70 percent of CMOs say becoming an AI leader is a critical goal for 2026, only 30 percent report mature or fully developed AI readiness capabilities, Gartner reports.

“CMOs recognize AI’s potential as a force multiplier for growth, efficiency, and transformation, but most marketing organizations are not yet built to capture that value,” says Ewan McIntyre, a vice president analyst and chief of research in the Gartner Marketing Practice. “The risk is that CMOs invest in AI tools faster than they build the data foundations, processes, governance, and talent required to scale them.”

Gartner also found that marketing budgets remain effectively flat, rising only slightly to 7.8 percent of company revenue in 2026, up from 7.7 percent in 2025. This constrained fiscal environment is increasing pressure on CMOs to fund AI-enabled transformation through sharper prioritization and resource reallocation.

The survey found a clear gap between AI ambition and organizational readiness. Seventy percent of CMOs consider becoming an AI leader to be a critical goal for 2026. However, 70 percent also acknowledge that their internal marketing processes are not yet mature enough to effectively implement and scale AI.

CMOs whose organizations report mature or fully developed AI readiness capabilities are establishing an early advantage by pairing AI investment with stronger budget agility, innovation commitment, and organizational readiness, according to Gartner, which also found that these more AI-ready marketing organizations allocate 21.3 percent of their marketing budgets to AI initiatives, compared with the survey average of 15.3 percent. They also report average marketing budgets of 8.9 percent of company revenue, above the 2026 average of 7.8 percent.

“AI maturity is beginning to separate marketing leaders from laggards,” McIntyre says. “The most advanced CMOs are not simply spending more on AI; they are creating the budget agility, innovation capacity, and operating discipline needed to turn AI investment into measurable business impact.”

While overall marketing budgets have remained effectively flat, CMOs are still expected to deliver growth, efficiency, and AI-enabled transformation, according to Gartner, whose survey found that 56 percent of CMOs say their marketing organizations lack the budget required to deliver their 2026 strategies, while 54 percent report insufficient resources.

This resource gap is forcing CMOs to make sharper decisions about where to invest, what to deprioritize, and how to reallocate existing resources toward capabilities that can create greater business impact, Gartner says, noting that as AI takes up a larger share of marketing investment, CMOs must ensure those dollars are supported by the right operating model, governance, data foundations, and talent.

“CMOs are being asked to deliver growth, efficiency, and transformation without meaningful budget expansion,” McIntyre says. “Those who succeed will make deliberate, data-driven trade-offs and treat AI as a force multiplier.”