AI News 2024年10月18日
AI governance gap: 95% of firms haven’t implemented frameworks
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一项针对 600 多位来自美国、英国和德国的大公司 CEO、CIO 和 CTO 的调查显示,96% 的组织已经在利用 AI 支持业务运营,并且同样比例的组织计划在未来一年增加其 AI 预算。AI 投资的主要动机包括提高生产力(82%)、改善运营效率(73%)、增强决策(65%)和实现成本节约(60%)。报告中最常见的 AI 使用案例是客户服务和支持、预测分析以及营销和广告优化。尽管 AI 投资激增,但企业领导者敏锐地意识到 AI 为其组织带来的额外风险敞口。数据完整性和安全性成为实施新的 AI 解决方案的最大障碍。高管们还报告遇到了各种 AI 性能问题,包括数据质量问题(例如,不一致或不准确)、AI 算法中的偏差检测和缓解挑战,导致不公平或歧视性结果以及难以量化和衡量 AI 计划的投资回报率(ROI)。虽然 95% 的受访者表示对他们组织目前的 AI 风险管理实践充满信心,但报告揭示了 AI 治理实施方面的重大差距。只有 5% 的高管报告称他们的组织已经实施了任何 AI 治理框架。然而,82% 的人表示实施 AI 治理解决方案是一个有些或极其紧迫的优先事项,85% 的人计划在 2025 年夏季之前实施此类解决方案。该报告还发现,82% 的参与者支持 AI 治理行政命令,以提供更强大的监督。此外,65% 的人表示担心知识产权侵权和数据安全。

🤔 尽管 AI 投资激增,企业领导者敏锐地意识到 AI 为其组织带来的额外风险敞口。数据完整性和安全性成为实施新的 AI 解决方案的最大障碍。

🧐 高管们还报告遇到了各种 AI 性能问题,包括数据质量问题(例如,不一致或不准确)、AI 算法中的偏差检测和缓解挑战,导致不公平或歧视性结果以及难以量化和衡量 AI 计划的投资回报率(ROI)。

😔 虽然 95% 的受访者表示对他们组织目前的 AI 风险管理实践充满信心,但报告揭示了 AI 治理实施方面的重大差距。只有 5% 的高管报告称他们的组织已经实施了任何 AI 治理框架。然而,82% 的人表示实施 AI 治理解决方案是一个有些或极其紧迫的优先事项,85% 的人计划在 2025 年夏季之前实施此类解决方案。

🚀 该报告还发现,82% 的参与者支持 AI 治理行政命令,以提供更强大的监督。此外,65% 的人表示担心知识产权侵权和数据安全。

🌎 随着欧盟 AI 法案等全球法规即将出台,该报告强调了解除 AI 风险和仍需完成的工作的重要性。实施和优化专门的 AI 治理策略已成为企业寻求利用 AI 力量同时降低相关风险的首要任务。

🏆 该报告的调查结果是对组织的警钟,提醒他们要优先考虑 AI 治理,因为他们继续投资和部署 AI 技术。负责任的实施和强大的治理框架将是释放 AI 潜力的关键,同时保持信任和合规性。

Robust governance is essential to mitigate AI risks and maintain responsible systems, but the majority of firms are yet to implement a framework.

Commissioned by Prove AI and conducted by Zogby Analytics, the report polled over 600 CEOs, CIOs, and CTOs from large companies across the US, UK, and Germany. The findings show that 96% of organisations are already utilising AI to support business operations, with the same percentage planning to increase their AI budgets in the coming year.

The primary motivations for AI investment include increasing productivity (82%), improving operational efficiency (73%), enhancing decision-making (65%), and achieving cost savings (60%). The most common AI use cases reported were customer service and support, predictive analytics, and marketing and ad optimisation.

Despite the surge in AI investments, business leaders are acutely aware of the additional risk exposure that AI brings to their organisations. Data integrity and security emerged as the biggest deterrents to implementing new AI solutions.

Executives also reported encountering various AI performance issues, including:

While 95% of respondents expressed confidence in their organisation’s current AI risk management practices, the report revealed a significant gap in AI governance implementation.

Only 5% of executives reported that their organisation has implemented any AI governance framework. However, 82% stated that implementing AI governance solutions is a somewhat or extremely pressing priority, with 85% planning to implement such solutions by summer 2025.

The report also found that 82% of participants support an AI governance executive order to provide stronger oversight. Additionally, 65% expressed concern about IP infringement and data security.

Mrinal Manohar, CEO of Prove AI, commented: “Executives are making themselves clear: AI’s long-term efficacy, including providing a meaningful return on the massive investments organisations are currently making, is contingent on their ability to develop and refine comprehensive AI governance strategies.

“The wave of AI-focused legislation going into effect around the world is only increasing the urgency; for the current wave of innovation to continue responsibly, we need to implement clearer guardrails to manage and monitor the data informing AI systems.”

As global regulations like the EU AI Act loom on the horizon, the report underscores the importance of de-risking AI and the work that still needs to be done. Implementing and optimising dedicated AI governance strategies has emerged as a top priority for businesses looking to harness the power of AI while mitigating associated risks.

The findings of this report serve as a wake-up call for organisations to prioritise AI governance as they continue to invest in and deploy AI technologies. Responsible implementation and robust governance frameworks will be key to unlocking the full potential of AI while maintaining trust and compliance.

(Photo by Rob Thompson)

See also: Scoring AI models: Endor Labs unveils evaluation tool

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