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1 minute read
Generative AI holds the potential to push us far beyond the confines of outdated measurement paradigms, offering fresh ways to unearth genuine impact. However, adopting AI tools alone is insufficient. Organisations must rethink their entire approach to evaluation, re-examining everything from entrenched biases and data policies to how they involve employees in AI-driven change. The goal is a profound mindset shift in which measurement becomes a catalyst for learning, purpose, and real transformation.
Leaders should be prepared to question and abandon deeply rooted practices if Gen-AI reveals contradictions or missed opportunities.
Ethical considerations must remain central, guiding how data is collected, analysed, and used. When handled carefully, AI can bridge the gap between slick numerical metrics and the rich, human realities of impact—unearthing both success stories and hidden problems that conventional figures have long concealed.
Ultimately, the challenge is to harness these emerging tools responsibly and imaginatively, so that “impact measurement” evolves into something that truly informs and advances our most important aims. If we insist on sticking to the familiar comfort of outdated metrics, we risk failing those who depend on us for meaningful progress. By embracing critical questions, fresh perspectives, and the insights that AI can unlock, we can finally venture beyond measuring what is convenient towards capturing what genuinely matters.
