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Why 85% of AI initiatives fail—and how leaders are fixing it

From Qualcomm to Marriott, companies are rewriting the rules of AI adoption. The secret? Empowering employees—not just executives—to lead change.

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Why 85% of AI initiatives fail—and how leaders are fixing it

A recent study by Boston Consulting Group (BCG) and the Marketing and Media Alliance has shed light on the state of AI initiatives in enterprises. Only 15% of these projects operate cross-functionally at scale, delivering significant value. Meanwhile, a forum in San Francisco, hosted by Writer, highlighted successful AI transformations led by frontline workers and a shift in leadership mandates.

The research, led by Janet Balis and Lauren Wiener from BCG, along with Vas Bakopoulos from the Marketing and Media Alliance, revealed that most AI initiatives remain trapped in pilots or isolated functions. For these 85% of organisations, the path forward involves aligning the C-suite, focusing on meaningful wins, rethinking agency relationships, and reimagining talent. This echoes the findings from Writer's AI Leaders Forum, where executives from companies like Qualcomm, Microsoft, Amazon, and Samsung shared their experiences.

At the forum, held on November 4th at the Fairmont Hotel in San Francisco, speakers including Qualcomm's Brent Summers discussed how AI can transform businesses. Summers' curiosity about AI during the pandemic led to a company-wide transformation that saves 2,400 hours monthly and boosts employee productivity and happiness. Other speakers from e.l.f. Beauty, Marriott International, Blue Federal Credit Union, and more, shared similar success stories, demonstrating a fundamental shift in how AI transformation occurs, with society reshaping itself around this new capability.

The BCG study and Writer's AI Leaders Forum highlight the need for enterprises to rethink their approach to AI. By aligning leadership, focusing on meaningful outcomes, and embracing a shift in how AI transformation happens, organisations can unlock the full potential of AI. This involves moving away from treating AI transformation like previous IT rollouts and instead pushing control to frontline workers, treating governance as velocity, and activating ecosystems.

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