"Farrar is head of search at the UK-based SEO and web design agency Candour. Digital marketing, like nearly every other industry, is heatedly debating the topic of AI. And though her team is keen to embrace the benefits of working faster and more efficiently, and of clawing back time otherwise spent on less interesting tasks, it doesn't always work that way."
"Also: 95% of business applications of AI have failed. Here's why AI can generate product lifestyle imagery for clients who don't have any, but it hallucinates or misses key points when creating executive summaries of data. Refining a prompt to help assign categories to datasets could take so long, Farrar might as well have done the job manually. 'As a manager, I'm trying to get the team more on board with AI stuff, because it's the future of so many industries,' Farrar said."
Many teams experience inconsistent AI results: some workflows gain efficiency while others produce useless outputs or hallucinations. Prompt tuning and correcting AI outputs can consume as much time as manual work. A study found worker confidence in AI has fallen even as adoption rises, signaling anxiety and potential productivity risks. Insufficient training and unclear implementation strategies contribute to frustration among employees. Managers seek to increase AI adoption but face resistance when tools waste time. Organizations are testing approaches to reduce frustration, improve training, and align AI capabilities with realistic use cases.
Read at ZDNET
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