New data reveals that 41% of Gen Z workers are actively working against their employer’s AI strategy.
Companies face internal struggles during AI adoption. Existing generative AI tools struggle in the workplace. According to Writer, the enterprise generative AI platform—72% of company leaders report struggling to integrate AI tools. Forty-two percent of executives admit these struggles have caused significant internal friction.
The main blockers for this friction are misalignment and poor collaboration. These factors result in a pile-up of uncoordinated solutions.
“Let’s face it, AI adoption is a bit like herding cats—everyone’s moving in different directions,” says Kevin Chung, Chief Strategy Officer at Writer. “And even harder, making this change stick is near impossible. Employees are left in the dark, unsure and unsupported.”
Its disruption becomes inevitable with technology that extensive. However, Chung believes it is a problem that should be tackled head-on and not dismissed as ‘growing pains’.
The disconnect is evident, 71% of executives say their company’s AI tools are built in isolation. “IT can’t complete the job alone; it’s like doing a relay race without a baton,” says Chung. “Lack of alignment leads to distractions and lowered trust.” Siloed AI solutions can create roadblocks for companies in need. “They may not integrate well into workflows, missing out on opportunities and building inefficiencies,” Chung says.
Divison was exacerbated when 62% of leaders believed it would take years to see the return on their investments. Nearly one-third saw AI adoption at a loss. Growing pains run deeper; employees reach a breaking point. Thirty-five percent of employees resort to spending their own money on AI tools. This costs them financially but worsens security risks to their employers.
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Fear of AI discourages honest worker-tech relationships. “Some employees fear losing value or creativity to AI,” Chung says. “Others have concerns over AI unfairness and ethical issues.” Gen Z workers, natively digital, are more wary of this tech than other generations. “Add discontent with AI quality and unexpected increased workload, and you’ve a recipe for rebellious AI,” Chung says.
Chung offers these steps to make AI adoption friendlier:
Natural leaders emerge with enthusiasm for AI mostly likely to embrace it and spread its potential. “First, acknowledge and reward the AI role models—but provide more than recognition,” Chung says. “Equip them with the latest AI technology and training.”
Building a corporate voice resonates with employees. “Let AI champions design AI solutions,” Chung says. “Phase in their skills and insights; invite them to play a part in nurturing AI.”
Then allow them to pass on this knowledge. “AI champions should shape and guide internal training programs—internal communications devoted to AI,” Chung says. “Seeing their peers leading the way helps employees to follow.”
The trust deficit—41% of Gen Z workers actively sabotaging their employer’s AI strategy—reveals a messaging gap far deeper than a slump in enthusiasm. Smart leadership must know the offense to build up its defense: challenge this generation head-on about their AI ignorance, not just their AI fears.
Siloed AI initiatives preemptively sabotage unified growth. Dependability and efficient onboarding spotlight this issue: who is on board with strategy, attempting to integrate the opposing tools while concurrently trying to purchase the dysfunctional pieces.
The multi-barrier issues for the employee and workplace speak to how disjointed adoption can fire back, economically sinking so many companies. To finally see genuine ROI in AI tools, leaders should consider a more concerted effort from stakeholders about the investment—above and beyond a financial ROI.
Many executives underestimate the impact of AI on the culture of the workplace—its effect on morale, trust, and efficiency. Those that reward AI adoption are likely more successful, both financially and operationally. The bottom line: investing in AI must be both monetary and cultural.