AI projects often fail when their scope is unclear and team capabilities are overestimated. Without focus, workers can get stretched too thin and miss key priorities, according to John Callery-Coyne, chief product and technology officer at ReflexAI, a company that sells AI-powered training and quality assurance tools for crisis hotlines, emergency responders, and customer service centers.
The key to success: clear goals, internal champions
A more effective approach to agentic AI deployment focuses on clear goals, set budgets, and with strong internal champions — often supported by external vendors who deliver fast, measurable ROI, Callery-Coyne said. “Regardless of approach, it’s essential that the AI tools are deployed within regular workflows so there is sustained utilization that drives long-term results,” he said.
Despite early hurdles, agentic AI does mark a major leap for genAI, enabling smarter automation, efficiency, and innovation beyond traditional bots, Gartner said in its report. The research firm predicts at least 15% of day-to-day work decisions will be made autonomously through agentic AI by 2028, up from zero in 2024. In addition, a third of enterprise software applications will include agentic AI by 2028, up from less than 1% in 2024.
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