Published: 20 March 2024
数据和分析领导者需要评估生成式人工智能（GenAI）新投资的潜在收益和成本。虽然多数用例能以较低成本完成实验，但本文提供的决策框架可用于评估企业级GenAI项目的成本并实现其价值。
较早实现GenAI业务价值的企业机构在构建用例组合，主要包括三类用例，侧重点分别是通过渐进式改善维持竞争地位，通过扩展当前流程实现差异化，以及颠覆行业、核心流程和业务模式。然而，Gartner客户目前反映的多数GenAI投资属于前两个类型。
生产力的提高，是率先采用GenAI的企业机构发现的主要初始收益。生产力的提高主要影响反映未来价值的先行指标，而不是体现直接经济收益（如即时的成本削减）的指标。换言之，相比于直接的投资回报率（ROI），企业机构需要对间接的未来财务成果有更高的接受度。
生产力提高带来的收益对于短期和长期财务成果的影响，取决于领导者如何使用和主动管理新发现的生产力。
率先采用GenAI的企业机构面临价值归因的难题，而在试点、推广和生产阶段确定用户想通过生产力收益达成的意图，有助于解决这一挑战。
持续监控GenAI工作的价值和成本（包括持续跟踪影响成本的市场创新和定价），确保其实现预期价值，控制不确定的成本和风险。
较早与人力资源、金融、法务和公司战略团队协作有助于实现收益，确保变革管理所需的举措能够就位，从战略角度出发利用生产力提高所节约的时间，并且最大程度地降低AI造成负面影响的风险。
负责评估和实现GenAI价值的数据和分析领导者，应：
与业务领导者合作，确定使用AI的战略意图（对自身竞争地位和所在行业的防护、扩展还是颠覆），进而确定AI发展目标和投资重点。确保GenAI产品组合与发展目标保持一致。
通过投资于“防护型”用例（如GenAI生产力助手）来改善特定任务的生产力、完成周期和质量。
扩展和改进现有业务流程，通过在应用中嵌入GenAI和注入独特的企业数据来实现差异化、创造竞争优势。
通过投资于新的战略性GenAI产品、服务、核心流程和业务模式来改变甚至颠覆所在行业，或者创造新的市场。这要求企业机构采取更积极的投资策略，提高对风险和复杂性的承受能力，并且注重战略性收益而不是直接的战术性收益。
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Analysts:
Rita Sallam, Graham Waller, Matt Cain, Andrew Frank, James Plath, Adnan Zijadic, Pri Rathnayake, Bern Elliot, Nate Suda
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