Companies Mistake AI Deployment for Success, Study Finds

Organizations are celebrating artificial intelligence implementations that may be actively damaging their customer relationships, according to new research that exposes a critical gap between perceived and actual AI success.

A study from Laivly, an applied AI company focused on contact centers, found that 65% of organizations consider their AI initiatives successful. Yet the underlying data tells a starkly different story: 43% of AI projects miss their deadlines, more than half exceed budgets, and 28% of leaders report that AI has directly caused lost revenue by failing to handle complex customer support issues effectively.

The disconnect stems from what companies choose to measure. Jeff Fettes, founder and CEO of Laivly, explained in an interview on Amazing Business Radio that organizations typically celebrate visible milestones—chatbot launches, reduced headcount, implementation dates—rather than actual improvements in customer experience.

Why it matters

This measurement problem has real business consequences. Nearly half of organizations in the study reported increased customer friction from their AI support solutions, including more transfers and customers having to repeat information. When companies convince themselves they've succeeded based on deployment metrics alone, they miss the warning signs that customers are growing frustrated—often until those customers defect to competitors. With 43% of boards of directors already dissatisfied with AI progress and demanding proof of success, executives need frameworks that measure genuine value creation, not just technology adoption.

The friction paradox

The Laivly research uncovered a troubling pattern: AI solutions intended to streamline customer service are instead creating more obstacles. Customers report having to navigate multiple transfers and restart their explanations, generating the exact friction these systems were meant to eliminate.

One in five leaders acknowledged they know revenue is being lost but cannot quantify the damage. This blind spot becomes particularly dangerous when companies go "all in" on AI automation, replacing human agents entirely based on cost projections that look attractive on paper but ignore the customer experience deterioration driving churn.

Fettes emphasized that AI should not fully replace human agents. The goal must be improving customer outcomes, not simply processing more interactions through automated channels.

Measuring what matters

The study, first reported by Forbes contributor Shep Hyken, draws a parallel to Hans Christian Andersen's "The Emperor's New Clothes." In that tale, an emperor parades in invisible garments while courtiers praise his magnificent outfit, unwilling to challenge the illusion. Similarly, organizations celebrate AI milestones internally while customers experience a fundamentally different reality.

Fettes warns that leaders often "over-believe" in their AI solutions when capabilities are overpromised and underdelivered. The real feedback comes from customers, who vote with their business by moving to competitors.

The solution requires centering customer needs and feelings in every AI decision and measuring success by improved outcomes rather than deployment checkpoints. Technology creates value only when it demonstrably enhances the customer experience, not merely when it's installed.

The greatest AI risk, according to the research, isn't outright failure—it's the illusion of success that persists until customer defection makes the truth undeniable. Details of the findings were first reported by Shep Hyken writing for Forbes.