
Although the rise of artificial intelligence has had companies racing to adopt the trendy new technology, three quarters of executives admit that their own AI strategies are "more for show," than connected to any tangible business strategy.
According to a survey from AI platform Writer of 2,400 executives and employees, nearly 40% of execs said that they lack a formal plan to use AI tools to drive revenue. Another 48% of execs called their own AI adoption a "massive disappointment," citing a lack of connectivity between their strategies and company goals.
Writer's survey also identified how the advent of AI has created a "two-tiered workplace," where 92% of C-suite executives have been focused on building a new class of "AI elite" employees, all while 60% plan to lay off those who either can't or won't adopt AI.
Read More: Survey Finds Companies Race to Adopt AI, But Lag Behind in Readiness
"This divide is widening," Writer noted. "AI super-users were three times more likely to get a raise or promotion last year, and five times more productive than those slow to adopt."
That, in turn, promotes an environment where trust breaks down between management and employees, with 29% of workers, including fully 44% of Gen Z staff, admitting to sabotaging their company's AI strategy. Additionally, 73% of CEOs reported feeling stress or anxiety from AI, while 64% feared losing their jobs over failed AI transitions.
And despite the gains in worker productivity from AI, just 29% of organizations reported significant return on investment from generative AI, with that number falling to 23% for AI agents. On top of that, a lack of planning around security and governance has 67% of execs reporting that their company has already suffered a data leak or breach due to unapproved AI tools, with 35% admitting that they wouldn't be able to immediately shut down a rogue AI agent.
"The gap between individual wins and organizational outcomes reveals what’s missing: structural transformation, not just tool deployment," Writer said.
Addressing those gaps, Writer added, requires companies to connect everyday AI tools to real-world results, so that employees can better understand why the technology is actually needed. By putting that framework in place before expanding AI across a company, organizations can create a clear system for accountability, oversight and expectations for executives and employees alike.



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