在组织中成熟

ByJohn Gikopoulos，，，，Saibal Samaddar，，，，Nidhi Om Subhash，，，，哈里·凯尔·休斯（Harry Keir Hughes） December 2020 | POV | 16 min read |通过电子邮件发送这篇文章|Download

在过去的几年中，人工智能（AI）迅速发展，其在行业中的使用也达到了步伐。首先是Amazon推荐系统中使用的预测性AI。然后，全世界政府都将深度学习算法用于对象和语音检测。今年，AI的出血边缘涉及在整个AI生命周期中可以解释的生成AI，分布式学习和AI系统。那些使用AI井的公司可以将企业利润提高38％，并在2035年之前为公司提供14万亿美元的总价值。¹

这个值来自的确切位置在哪里?很多AI is being used to manage and automate IT infrastructure, glean new insights about customers, identify cyber threats, and even improve the hiring process. But more can be done. Leading AI organizations put the technology at the center of both their business and operating models, using it to discover, democratize and de-risk AI adoption. The hope here is that they will become both a knowledge- and data-driven organization, with agility built into their DNA so they can deliver better products, increase customer sentiment, and derive more value from their partner ecosystem. Indeed, better working capital management, superior handling of business risk, and a more lucrative supply chain are just some of the changes this sort of “live enterprise” can expect to foster. Further, by making AI a core tenet of productivity, the live enterprise can quickly sense changing business needs and evolve in response. The holy grail here is a seamless network of partners, suppliers, and customers who talk to each other in real time, intelligently, and at the speed of data.²

当公司开始迈向现场企业的AI之旅：数字数据大量可用，计算成本越来越低，并且算法变得越来越复杂。但是，大多数公司尚未取得AI优先的飞跃，大多数人使用AI来提高效率，而不是改变业务赚钱的方式。实际上，在发展期间Infosys应用的AI，他们发现问题是，即使对于建立敏捷，有效的治理和AI优先的公司愿景的良好公司来说，AI做对的事情也不是一件容易的事。³

在我们对150个定量业务指标的690多家公司的研究中，即使是领先的公司，即使是领先的公司，也是找到有效的人才，一种规避风险的文化，以及将AI技术与旧系统集成到旧系统的困难（也是如此的困难（图1）。

图1.所有公司在采用AI时面临的挑战

资料来源：Infosys

但是突破这个玻璃天花板值得付出努力。在我们的分析中，我们发现AI-First企业随着AI的进步而增加了3个百分点，在BFSI和消费者，零售和物流（CRL）行业中，其影响最高（图2）。对于美国的一家银行公司运营，收入为100亿美元，这意味着增加3亿美元的增加收入 - 这没什么大不了的。

AI-first enterprises increase operating margins by as much as 3 percentage points as they progress along their journey

我们的AI成熟度指数在战略方面以0-100的规模为受访者，对受访者的评分；技术;操作；和人才和组织（T＆O）。Firms fell into one of four categories – “watchers”, “explorers”, “performers”, “visionaries” – depending on the respondents’ self-analysis to questions like “How many AI-related technologies has your company brought to scale in the last 12 months?” and “Do you have an enterprise-wide AI strategy in place?” Watchers were laggard AI firms that made up 18% of the data, and had an average AI maturity index of 30.13 (Figure 3), whereas leading ‘visionary’ firms (8% of the data) had an average score of 94.2. Even though scores were given based on self-analysis, some key insights emerged.

图2. AI中的领导者增加了运营利润率多达3个百分点

资料来源：Infosys

图3.有远见的人在运营方面处于领先地位，尽管人才和组织仍需要改进（T＆O）

资料来源：Infosys注意：成熟度得分：0-100，策略，技术，操作，T＆O：0-5

Visionaries are much more effective at operations than other firms and exactly a third more competent in this dimension than “performers” (4.8 compared with 3.6). However, even within visionary organizations, improvement is possible in the area of T&O, receiving a score of 3.91 out of 5 — a full one point less than their score for technology. Still, as we will see in further analysis, even within this area, visionaries are far ahead of laggards with respect to effective change management processes and their ability to satisfy employees.

On the technology dimension, the more advanced companies had brought more AI-related technologies to scale, including IoT and drones, whereas the rest were still stuck in PoC or pilot mode across most initiatives (Figure 4).

图4.有远见的人在大规模运行超过九分之十的AI计划

资料来源：Infosys

有远见的人还引用了更多驱动力的人工智能旅程，其关键任务是使用AI和自动化来重新想象过程，建立强大的AI治理，使用AI来改变业务模式，并将不同的业务部门与跨职能团队组合在一起（有69％的有远见的人平均而言，所有其他公司的36％）（图5）。

图5.有远见的人在AI自动化，治理和创新方面取得了进步

资料来源：Infosys

We also found that digital natives such as Google and Facebook outperform digital immigrants (traditional companies beginning to add digital competencies) in their AI journey, with a significantly higher AI maturity index (Figure 6).

图6.数字本地人的成熟度指数明显高于数字移民

资料来源：Infosys

Focusing on governance and the employee

为了提高操作效率，需要增长运营利润率。此外，需要建立有效的治理，以使AI更加透明，并确保有效执行策略。在我们的数据中发现了与操作效率相关的三个有趣的主题，即AI伦理，员工满意度和员工重新锻炼。做对了，这些主题共同提高了业务弹性，并使公司更加有利可图：

Focussing on both the employee and the customer can increase operating margins by 2 percentage points

1. 专注于AI伦理与更高的成熟度指数相关，而有远见的人的表现优于25％。
2. By focusing on the employee and the customer, operating margins can be increased by 2 percentage points.
3. 重新杀伤劳动力的能力使领导者与众不同，与小组的其余部分相比，运营利润率增加了1个百分点。

因此，人工智能转化的人方面是成功的关键属性。根据Korn Ferry的专家的说法，99％的战略取决于执行，这反过来依赖于高技能的人才生态系统。为了使客户启动自己的AI-NABEREMENT旅程（下面讨论），作为我们自己的AI成熟度评估的一部分，Korn Ferry将其专业知识向组织，人才，变更管理和组织的四个“人民战略”方面进行审核文化。（图7）

Figure 7. The Korn Ferry maturity audit looks at firms across four “people strategy” dimensions

资料来源：科恩渡轮

今天的业务存在于复杂且不可预测的环境中。庞大的变化和变化速度是如此的影响，以至于在不仔细关注的情况下，它会破坏甚至使业务策略脱轨。

Consequently, transforming the business requires identifying potential gaps in organization structure, people and culture. This means gaining clarity on how well the organization is set up to implement its AI strategy, raising questions such as:

• How well is the organization aligned with its strategy, especially in this new era of AI?
• AI策略是否与组织的目的保持一致？
• Is the right talent in place?
• 员工了解公司的策略吗？
• Is the strategy and culture of the firm aligned?

将运营效率（有效的AI治理）和业务弹性（更好的AI伦理，提高员工满意度，员工满意度，员工提高工作）的组成部分汇总在一起，可以绘制一个框架，以表面进一步的见解。

发现了与我们数据相关的这些维度的关键组件领域，包括有效的变更管理，知识共享和外部合作伙伴的使用（图8）。

图8.为了提高运营效率和业务弹性，企业应集中精力使AI民主化和变更管理

资料来源：Infosys

有效的变更管理是必要的，以照顾员工并确保AI系统负责。从我们的数据中，我们发现有96％的有远见者具有有效的变更管理流程，而57％的探险家和只有32％的观察者（图9）。

At Infosys, the Live Enterprise initiative is putting员工满意度在业务和经营模型的中心。使用应用的AI，自动化流程减少日常任务的分辨率时间。跨企业和更广泛的生态系统的连接数据确保所有数据都是通过自动方式进行了策划，清洁和连接的物理组合（通过知识图）。新见解是从这个连接网络中得出的，然后成为业务驱动力，以提供不断扩展的服务，以积极影响人，利润和星球的三重底线。该平台还确保通过知识共享门户将数据和分析被民主化。随着时间的流逝，该计划将在合作伙伴组织之间实施。

Figure 9. Leading firms have better change management and care more about employees

资料来源：Infosys

使人工智能民主化或提高技能？

使员工更快乐是从数据中出现的一个线程。能够重新使用先进的AI（在Infosys术语中）使用先进的AI也是至关重要的。

As we wrote in our report on数字雷达2020，成为探险家要比成为一家有远见的公司要容易得多。这样做的主要原因是技能不足。此分析也是如此。尽管有远见的人在T＆O维度上苦苦挣扎（图1），但对于其他小组而言，缺乏人才更为明显（35％的人说，缺乏人才是一个重大挑战，而只有9％的有远见的人）。这样做的原因之一是，有远见的人已经开发了内部专业知识来提供AI技术（91％），而落后者则取决于外部支持（69％）（图10）。

图10.十分之一的有远见的人在内部能力发展，而其余的十分之一取决于外部支持

资料来源：Infosys

公司可以通过两种方式之一来阻止这种人才短缺：通过高技能或使AI易于使用。63％的有远见者具有组织任务和领导力向UPSKILL员工开车（图11），许多人使用Wingspan（Infosys）或Maxis（通用汽车）等数字平台（通用汽车）⁴确保始终学习。对于观察者来说，这个数字降至15％，这是一个显着差异。

Figure 11. Anywhere, anytime learning is much stronger for visionaries than for watchers

资料来源：Infosys

Making AI easier to use is often a better strategy in the long term as it has the knock-on effect of bringing business and IT together earlier on in the AI journey, rather than trusting a few superstar data scientists with developing capabilities. Visionaries do this very effectively, sharing data science knowledge throughout the organization 17 percentage points more rigorously than performers in our study.

是否upskilling或更容易地使用人工智能pace of change of technology means that employees will need to be given space to learn, unlearn and re-learn. Even simple and intuitive user interfaces that are powered by AI require a cohort of employees that ask the right questions at the right time. In this organizational set-up, employees across the spectrum will need to play both interlocutor and teacher, providing a space where AI-related questions are answered in confidence, and learnings up-voted at scale. To aid in this, AI training sessions should no longer act as a one-way monologue, but rather act as a platform to test new ideas and processes throughout the firm. These sessions will also be best served as an iterative and exploratory canvass for discussion, held throughout the year to act as a funnel for emerging ideas, while allowing less tech-savvy employees to upgrade their understanding. However, while anytime, anywhere learning will make these sessions more viable, the role of teacher will grow in importance; wherever possible, firms must introduce AI tutors, helping listeners interpret, question and analyze the content under discussion.

通过卓越中心进行操作

The data also shows that companies don’t do operations well enough, an area ripe for external support. And the money to be made here is vast. Organizations leading in AI operations, including greater in-house competency to scale AI technologies and the ability to work effectively across siloes, outperformed the rest by as much as 6 percentage points of the operating margin (Figure 12). To put that into a dollar figure, that’s $600 million extra cash for a $10 billion revenue company.

Figure 12. Effective AI operations can increase operating margins by up to 6 percentage points

资料来源：Infosys

也就是说，即使有远见的人也引用了遗产系统，一种规避风险的文化以及不足的业务/IT合作是他们在执行有效运营策略方面最大的挑战。这些问题不仅是AI问题。实际上，当我们要求我们的云专家列举建立卓越云中心的主要原因 - 以及云旅程中众多的选择和膨胀期望的压倒性解决方案时，最终的原因是渴望增加治理并通过将技术，金融和业务团队汇总在一起，降低成本。有远见的公司可以通过设置利益相关者参与的枢纽来优化其投资，这将以最佳的方式使用人才，资本支出和OPEX支出来使组织保持一致。莱加德公司还可以使用这种结构来培训员工，建立有效的变更管理，并确保该公司内部的AI辜负炒作。

Your own maturity assessment

COVID-19 has accelerated the implementation of AI initiatives, with firms doing more work in six months than they might have done in years. In this new paradigm, the employee has become the linchpin on which success will depend. Getting change management right and ensuring the workforce is engaged can massively impact the bottom line.

Before a firm can put in place an effective playbook for how to become more like a visionary organization, it is necessary to first determine the as-is state. At Infosys and Korn Ferry, we have developed a tool for firms to do just that. Using an online portal, executives will be asked a series of questions that will score their firm across our maturity indices. Along with a performance scorecard and industry benchmark, they will then be provided with a high-level roadmap with a set of prioritized capabilities to launch their应用的AIenablement journey. Further, a dollar figure will be assigned to the impact that this journey will have on their bottom line (increased revenues, cost benefits) over a defined time horizon.

AI现在正在改变业务。借助Infosys应用AI，我们正在帮助企业规模和未来的AI驱动投资。您准备好前进了吗？

Interested in taking the assessment? Emailsaibal.samaddar@infosys.com或者tristan.schulhof@infosys.com。

Methodology

We studied the AI journey of 690+ organizations, analyzing 200+ quantitative and qualitative metrics. Maturity indices were derived by scoring firms from 0 to 100 across the four dimensions of strategy, technology, operations, and T&O (Watchers, Explorers, Performers, Visionaries).

The respondents were C-suite executives, directors, SVPs, VPs, and AVPs.

企业各个领域，地理，数字保有权和收入乐队的分裂如下：

参考

1. Implementing AI in Business – Challenges and Resolutions，，，，哈里·凯尔·休斯（Harry Keir Hughes）& Isaac Labauve, November 2019, Infosys Knowledge Institute
2. InfosysLive Enterprise – A Continuously Evolving and Learning Organization，穆罕默德·拉菲·塔拉夫达（Mohammed Rafee Tarafdar），杰夫·卡瓦诺（Jeff Kavanaugh）和哈里·凯尔·休斯（Har亚搏电脑登录ry Keir Hughes），2019年7月，Infosys知识研究所
3. Infosys数字雷达2020：从数字成熟到活企业，Jeff Kavanaugh＆Chad Watt，2020年，Info亚搏电脑登录sys知识研究所
4. 敏捷的数据智能：重塑业务，，，，Dr. N.R. Srinivasa Raghavan & Harry Keir Hughes, June 2020, Infosys Knowledge Institute

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Korn Ferry是一家全球组织咨询公司。我们与客户合作设计其组织结构，角色和职责。我们帮助他们雇用合适的人，并就如何奖励，发展和激励他们的员工提供建议。而且，我们帮助专业人士驾驶和促进他们的职业。亚博双赢棋牌