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How businesses can thrive in the age of generative AI

2023-12-11 21:44:05
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Since the launch of ChatGPT, the corporate world has been abuzz about the possibilities of generative AI. As millions of users created prompts for the chatbot to write power ballads, poetry and persuasively worded high school essays, businesses worldwide began to consider integrating similar services into their workflows.

Generative AI used in business
While some businesses have been quick to adopt generative AI and use it prolifically, others have yet to leverage its potential. (Photo by Sompaen via Shutterstock)

Nearly a year on, Tech Monitor sat down with a selection of legal firms, IT giants and financial institutions to take stock of generative AI’s impact on their businesses, and whether it lived up to that early hype from late 2022. The discussion is captured in a new report, Thriving in the Age of Generative AI: Harnessing possibilities to maximise business value.

The initial conclusion from delegates was that it had, with some caveats. Most described their embrace of generative AI in their businesses as having derived from an early fascination with ChatGPT.

“It’s very rare when I start using something that I don’t move for three or four hours,” recalled one insurance executive, who ended up test-running several of their audit procedures through the model and pioneered the use of generative AI in comparing insurance policies and securely translating regulatory documents. Others lauded its ability to quickly produce summaries of complex security reports or monitor adverse media coverage – in short, to quickly churn through reasonably complex tasks that would have taken professional auditors or security analysts hours to complete.

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Generative AI poses risks

Few firms represented at the table, however, were willing to lean too heavily on generative AI. This was, it emerged, down to pervasive fears that such models continue to ‘hallucinate’ responses to questions they are not trained to answer, or fears that highly sensitive corporate data could be inputted indiscriminately into chatbots by employees at great risk to the company. “We soon discovered that lots of our staff were using it,” said the firm’s CISO. “And, on Valentine’s Day this year, we blocked it.”

That company only resumed its use of generative AI a couple of weeks before the roundtable, after a rigorous investigation into what new guardrails on its use would be appropriate to impose. “We set up a central AI accelerator function to look at the security, the risk, the compliance and legal implications,” said the CISO. The firm is now an enthusiastic user of Bing Chat Enterprise, and is “very pleased to be on the M365 Early Adopters Program”.

Implementing guardrails for AI

Similar investigations had taken place across other media, legal and financial institutions represented at the roundtable. Few of these guardrails, however, completely forestalled the use of generative AI in more traditionally sensitive areas of business, such as cybersecurity. One IT department head from a major high street bank, for example, described how he had championed the use of tailor-made generative AI models to instruct staff on how they had perpetrated minor internal policy breaches. “It’s not big money we’re saving,” they said, “but it will save security analysts hours of their time a week.”

One frequently cited challenge in implementing these kinds of bespoke generative AI solutions, however, was the quality and organisation of the corporate data used to train the model. “When we ask generative AI tools to surface our intranet and find me a policy on such-and-such,’ half the time it comes up with an out-of-date policy because we haven’t done a clean-up,” said one CISO. “That’s going to be a humungous undertaking.”

Finding solutions

Others were also concerned about the direct threat of cybercriminals using generative AI to breach their companies. In addition to the threat of AI-based phishing attacks, delegates highlighted the possibility of so-called ‘vishing’ attacks, wherein audio of senior leadership figures could be used to either trigger illegal fund transfers or manipulate stock prices. The risk of this happening had led at least one major financial institution at the table to force all client interactions to take place over video as such attacks, even without the use of AI, were “happening at least once a week”.

Even so, most figures at the table remained confident that the market would eventually produce solutions to these challenges. Delegates remained overwhelmingly convinced that generative AI had triggered positive changes to workflows within their organisations and welcomed new developments soon.

“We are going to have massive productivity improvements,” pronounced one CSO. This was especially true when it came to code generation applications, added, which were proving to be a boon for junior and mid-level programmers. “More senior developers probably don’t need it as much, but it brings everybody up to a much higher level of productivity and quality.”

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参考译文
企业如何在生成式人工智能时代蓬勃发展
自ChatGPT推出以来,商界一直围绕生成式人工智能的潜力展开热烈讨论。随着数百万用户通过提示生成强大的叙事歌曲、诗歌以及措辞具有说服力的高中作文,世界各地的企业开始考虑将类似服务整合到他们的工作流程中。虽然一些企业迅速采用生成式人工智能并广泛使用,但另一些企业尚未充分挖掘其潜力。(照片由Sompaen通过Shutterstock提供)将近一年后,《Tech Monitor》采访了多家律师事务所、科技巨头和金融机构,评估生成式人工智能对其业务的影响,以及它是否实现了2022年末初的预期效果。这番讨论被收录在一份新报告中:《在生成式人工智能时代蓬勃发展:抓住机遇最大化商业价值》。初步结论是,它确实实现了,但有一定条件。大多数受访者表示,他们对生成式人工智能在企业中的应用,源于对ChatGPT的初期好奇。一位保险公司的高管回忆道:“我很少遇到能让我连续使用三四个小时的东西。” 他最终通过模型测试了多项审计程序,并率先使用生成式人工智能来比较保险政策和安全地翻译监管文件。其他人则赞赏其能快速生成复杂的网络安全报告摘要或监测负面新闻报道——简而言之,它能迅速完成一些专业审计师或安全分析师需要数小时才能完成的相对复杂任务。**免费白皮书:《在生成式人工智能时代蓬勃发展:抓住机遇最大化商业价值》** 由Hexaware-Technologies提供 请输入您的信息获取免费白皮书: 国家* 阿富汗 阿尔巴尼亚 阿尔及利亚 美属萨摩亚 安道尔 安哥拉 安圭拉 阿根廷 亚美尼亚 阿鲁巴 奥地利 阿塞拜疆 阿富汗 巴哈马 巴林 孟加拉国 巴巴多斯 白俄罗斯 比利时 伯利兹 贝宁 百慕大 不丹 玻利维亚 波斯尼亚-黑塞哥维那 博茨瓦纳 波韦岛 巴西 英国印度洋领土 文莱 捷克共和国 丹麦 吉布提 多米尼加 多米尼加共和国 厄瓜多尔 埃及 萨尔瓦多 赤道几内亚 埃塞俄比亚 法罗群岛 斐济 法国 法属圭亚那 法属波利尼西亚 法属南部领地 加蓬 冈比亚 亚美尼亚 德国 加纳 直布罗陀 希腊 格陵兰岛 格林纳达 圭亚那 哈伊杜岛和麦克唐纳群岛 梵蒂冈城 国家 约旦 哈萨克斯坦 肯尼亚 基里巴斯 韩国 哈萨克斯坦 马来西亚 马尔代夫 马里 马尔代夫 马耳他 马绍尔群岛 马提尼克 毛里塔尼亚 毛里求斯 马约特 马里 墨西哥 微软 纳米比亚 瑙鲁 尼泊尔 荷兰 荷属安的列斯 新喀里多尼亚 新西兰 尼加拉瓜 尼日尔 尼日利亚 纽埃 恩克里夫岛 北马里亚纳群岛 挪威 阿曼 巴基斯坦 帕劳 巴勒斯坦被占领土 巴拿马 巴布亚新几内亚 巴拉圭 秘鲁 菲律宾 皮特凯恩群岛 波兰 葡萄牙 波多黎各 卡塔尔 留尼旺 罗马尼亚 俄罗斯 莱索托 瑞典 瑞士 突尼斯 土库曼斯坦 土耳其 土耳其 突尼斯 瓦利斯和富图纳 西撒哈拉 也门 赞比亚 赞比比斯 了解更多关于我们的服务,包括New Statesman Media Group如何使用、处理和共享您的个人数据,以及您的个人数据权利和如何取消订阅未来的营销通信,请访问我们的隐私政策。 我们的服务面向企业客户,您确认提交的电子邮件地址是您的公司电子邮件地址。 **下载免费白皮书** 感谢您。请查看您的电子邮件,下载白皮书。生成式人工智能带来的风险 然而,与会的大多数公司都不愿意过度依赖生成式人工智能。他们表示,这是因为普遍存在这样的担忧:这些模型仍然会“幻觉”回答那些它们未被训练的问题,或者担心敏感的企业数据可能被员工随意输入聊天机器人,从而对公司造成巨大风险。该公司的首席信息安全官(CISO)表示:“我们很快发现,很多员工都在使用它。今年的情人节,我们将其封锁了。” 该公司在圆桌会议前的几周才重新开始使用生成式人工智能,此前经过了对其使用新限制条件的严格调查。CISO表示:“我们设立了一个中央人工智能加速部门,来研究安全性、风险、合规和法律影响。” 该公司现在是Bing Chat Enterprise的积极用户,并且“非常高兴加入M365早期采用者计划”。 实施人工智能的限制 其他媒体、法律和金融机构的圆桌会议也进行了类似的调查。然而,这些限制措施并不能完全阻止生成式人工智能在传统上较为敏感的业务领域(如网络安全)中的使用。例如,一家主要银行的IT部门负责人描述了他是如何倡导使用定制的生成式人工智能模型来指导员工了解他们如何造成了轻微的内部政策违规。“我们节省的钱不多,”他说,“但这可以每周为安全分析师节省很多时间。” 然而,在实施这些定制的生成式人工智能解决方案时,一个经常被提到的挑战是用于训练模型的企业数据质量和组织方式。一位CISO表示:“当我们要求生成式AI工具浏览我们的内部网站,找到某种政策时,一半时间它会给出一个过时的政策,因为我们没有进行清理。这将是一项巨大的任务。” 寻找解决方案 还有人担心,网络犯罪分子可能会直接利用生成式人工智能入侵他们的公司。除了AI驱动的网络钓鱼攻击外,与会代表还提到了所谓的“语音钓鱼”(vishing)攻击的威胁,即利用高管的声音录音引发非法资金转移或操纵股票价格。这种风险促使与会的至少一家大型金融机构强制要求所有客户互动都通过视频进行,即使不使用AI,这些攻击“每周至少发生一次”。尽管如此,大多数与会者仍然对市场最终能解决这些挑战充满信心。代表们普遍坚信生成式人工智能已经触发了他们公司工作流程中的积极变化,并期待未来的发展。“我们将迎来巨大的生产力提升,”一位首席安全官宣布。这一点在代码生成应用中尤为明显,他补充道,这对初级和中级程序员来说尤为有帮助。“高级开发人员可能不需要它那么多,但它让所有人都能提高到更高的生产率和质量水平。” **本文主题:赞助**
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