Across industries, organizations are racing to integrate generative AI into their workflows. No one wants to fall behind competitors who are already leveraging AI to boost productivity and accelerate innovation. The promise is clear: faster output, greater efficiency, and more time for strategic work.

But there’s a growing tension beneath the surface. While AI can produce high-quality work at machine speed, it also has the potential to generate misinformation, fabricate sources, or misinterpret data—errors that often sound polished and credible enough to evade traditional review.

According to Wakefield’s (2025) research*, many companies are expanding AI adoption despite lacking governance protocols. Case in point, 75% of business leaders plan to increase GenAI use this year, yet 78% admit they aren’t fully prepared to manage its risks.

The result is a widening gap between the speed of AI-assisted work and the safeguards required to ensure accuracy at scale. Read on to see how organizations can keep pace with AI without sacrificing accuracy or reputation.

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