Nearly three in four CEOs expect AI agents to report directly to employees within five years, according to an IDC survey. The shift is expected to dramatically alter data analytics and business intelligence workflows, but resistance from workers and lingering trust issues threaten its adoption.
Megha Kumar, research VP for analytics and AI at IDC, said business intelligence and customer relationship management will see the biggest changes. "Business intelligence and analytics teams are generally short-staffed," Kumar said. "AI agents can help with data preparation and quality monitoring, query analysis, anomaly detection, and the generation of proactive insights and alerts." Kumar added that natural language queries through platforms like Teams and Slack will reduce the team's dependency on centralized data teams and cut context switching.
The goal is faster, more informed decision-making. When teams can get insights on demand and AI agents can recommend specific actions, the cycle from question to action shrinks. Management teams overseeing these changes need to understand the capabilities and limits of AI Agents & Automation to judge whether their outputs are reliable.
But trust is a major hurdle. An IDC/SAS survey found that 46% of respondents have significant trust issues with AI, stemming from poor data infrastructure, unstandardized governance, and fragmented data pipelines.
Kumar stressed that organizations must ensure AI agents provide correct, context-relevant responses. "Trust in AI agents' responses will be critical," she said. "This can be achieved by ensuring that the responses provided by the AI agents are explainable and auditable. There will also need to be investments in AI literacy training." Currently, Boomi reports that only 29% of organizations provide regular AI training. For managers responsible for Data Analysis teams, closing this literacy gap is a prerequisite for getting value out of the technology.
Why this matters for management
The C-suite, driven by the CEO expectations identified in the IDC survey, will push for AI agent adoption. But middle and upper management will be responsible for making these systems work in practice. The data shows a clear disconnect: CEOs want AI agents embedded in the workflow, but the workforce lacks both trust and training. Investing in data governance and AI literacy programs is not a secondary concern - it is the primary enabler of the promised productivity gains. Without addressing the trust gap, the push for agentic AI will encounter increasing resistance and fail to deliver on its potential.
Your membership also unlocks:
