Introduction
Artificial intelligence (AI) has the potential to transform society and improve lives through advancements in fields like commerce, healthcare, transportation, and cybersecurity. It can drive economic growth and support scientific breakthroughs that enhance our world. However, these benefits come with significant risks. AI technologies can negatively impact individuals, groups, and even the environment.
Similar to other technologies, these risks can emerge in various ways and can be either long-term or short-term. From biased algorithms that reinforce systemic discrimination, to opaque machine learning models making high-stakes decisions without human oversight, the risks posed by poorly governed AI systems are not theoretical, they are unfolding in real time.
Regulators across jurisdictions are responding with new frameworks such as the EU AI Act and updates to ISO standards, signaling a shift from innovation-at-any-cost to responsible AI deployment. But stream of these rising risks, the most forward-thinking organizations understand that governance is not just a regulatory checkbox; it is a strategic capability. In this piece, we examine the structural elements of a mature AI governance program, highlight leading practices and frameworks, and offer actionable insights into how businesses can build effective controls that scale with their AI ambitions; without stifling innovation.
The goal is not to fear AI, but to govern it wisely.
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