组织文化可以促进或阻碍数字化计划的实施。但是，当转型项目采用正确的人工智能来实现有益的结果和有凝聚力的员工队伍时，胜利就不言自明了。
新项目可能会引起员工的恐惧，而引入变革的整体文化将反映出这种警惕是如何表达和处理的。但一些共同特征是人工智能转型成功的关键。英国数据和人工智能解决方案咨询公司Northell Partners的创始人彼得•韦斯特(Peter Verster)在其著作《商业人工智能:商业领袖从人工智能中获取价值的实用指南》(AI for Business: A practical guide for Business: A practice guide for Artificial Intelligence)中摘录了其中的四种方法。 数字化转型网（www.szhzxw.cn）
一、敏捷性
大约86%的软件开发公司是敏捷的，这是有充分理由的。采用敏捷思维和方法可以让你比竞争对手更有优势，这样做的公司收入和利润平均增长60%。我们的研究表明，敏捷公司在数字项目上取得成功的可能性要高出43%。
实施敏捷会带来如此不同的一个原因是快速失败的能力。敏捷思维允许团队克服挫折，将失败视为学习的机会，而不是停止的理由。敏捷团队具有弹性，在尝试构建和实施人工智能解决方案时，这对于成功至关重要。
表现出这种毅力的领导者实现预期结果的可能性要高出四倍。如果人们认为领导团队在将人工智能嵌入公司方面的承诺是真诚的，那么在领导团队中培养重组和推进的决心就会容易得多。领导者可以通过倾听团队的声音，并在出现问题或恐惧时支持他们，来消除障碍。这意味着在发生变化时主动适应，无论这是否涉及更多的授权，引入外部支持，还是重新确定资源的优先级。
这应该从高层对新的工作方式的承诺开始，并在技能、流程和专门的职位上进行投资，以扩展敏捷行为。使用这种方法应该导致整个组织的变化，将敏捷原则嵌入到团队中，然后需要习惯于通过sprint、快速升级和快速失败和学习方法进行跨功能工作。 数字化转型网（www.szhzxw.cn）
二、信任
我们发现，有一件事几乎是普遍正确的，那就是人工智能转型伴随着大量劳动力的恐惧，这可能成为人工智能技术更广泛采用的障碍。因此，在这个过程的早期解决同事的担忧是很重要的。
为了帮助人们适应这种潜在的转变，我提出以下建议:
1。保持诚信:有几种方法可以帮助你减轻整个组织的担忧，但首先诚实是至关重要的。如果人工智能会导致失业和重新部署，那就坦率地面对吧。建立信任始于诚实和正直。尽早给人们一种确定性，无论是让他们放心，还是为重新部署提供支持，都将有助于减少人工智能的焦虑。
2． 创造性地支持员工:看看你在整个业务中需要的技能，创造一个持续学习的环境，专注于使技能和角色适应业务的未来形态。让员工获得数据科学、数据分析、机器学习和项目管理方面的技能。还要考虑工作分担、兼职时间或不适合重新部署的灵活合同。
3． 探索应用:鼓励团队成员寻找AI可以帮助他们提高效率和增加价值的方法。帮助他们将人工智能视为他们可以使用的另一种工具，而不是作为他们能力的替代品，并使他们能够获得知识、技能和经验，以便在未来的工作场所保持现状并茁壮成长。
三、顾客导向
以客户的易用性和体验为中心的人工智能项目的组织往往会看到更成功的结果。在开始之前，问自己这三个问题，并尝试一些建议: 数字化转型网（www.szhzxw.cn）
1. 我该如何改善客户旅程?
考虑为你自己的流程做一个“神秘商店”，以了解摩擦发生的地方。当你有一个可以改进的领域的想法时，看看AI可以用来消除障碍或不便的方法。例如，Zara在店内尝试自助结账时，最初遇到了阻力，但当顾客开始从更短的等待时间中受益时，他们很快就接受了这种成功的改变。
2. 我怎样才能节省客户的时间和金钱?
尽管电力巨头菲利普斯不是一家能源公司，但他还是聪明地回应了客户对能源成本的担忧。通过为客户提供智能家居技术和节能解决方案，他们找到了一种利用人工智能帮助客户节省时间和金钱的方法(远程启动洗衣机、智能恒温器、占用传感器)，同时鼓励他们购买菲利普斯的产品。
3. 我怎样才能更好地使我的产品和服务符合客户的需求?
试着调查你的客户，找出他们想从你的产品或服务中得到什么。很容易假设你知道他们的痛点是什么，但是在今天的数字世界里，随着客户期望的迅速变化，客户的需求也在迅速变化。英国网上银行Monzo向客户询问他们想要什么样的支持，绝大多数人的回答是帮助他们增加储蓄。作为回应，Monzo实施了人工智能来分析客户交易数据，并自动对费用进行分类，提供支出摘要、储蓄目标和实时通知，以帮助客户跟踪他们的支出，确定超支的领域，并鼓励更好的储蓄习惯。
四、创新
鼓励和奖励各个层面的创新思维的公司在人工智能和数字项目中取得了最大的成功。将创新融入到一个组织中通常需要改变思维方式——在这种思维方式中，实验得到奖励，失败的项目被视为学习过程的重要组成部分。要创造一个鼓励创新的环境，重要的是允许人们失败，并授权他们承担适当的风险。
因此，考虑你的业务的以下方面，以了解它是否是一个创新可以蓬勃发展的地方:
是否有激励措施鼓励创新思维和解决问题的能力?
员工是否觉得自己有权做决定或向经理反馈意见?
团队成员是否因为害怕后果或态度而不愿冒险?
是否有一个团队或论坛来研究和支持整个企业的创新?
领导者是否愿意听取团队成员的想法和反馈? 数字化转型网（www.szhzxw.cn）
当新想法被提出时，领导者是否会引入和/或支持新想法，他们自己是否愿意改变?
通过这四个核心原则为创新奠定基础，将以一种有益的、战略性的、持久的方式为人工智能的实施奠定稳定的基础。这是成功项目的特征，也是组织正确评估他们对人工智能的准备情况的地方。
英文原文：
4 core AI principles that fuel transformation success
Organizational culture can either facilitate or hinder implementation of digital initiatives. But when transformation projects incorporate the right AI to enable beneficial outcomes and a cohesive workforce, the wins speak for themselves.
New projects can elicit a sense of trepidation from employees, and the overall culture into which change is introduced will reflect how that wariness is expressed and handled. But some common characteristics are central to AI transformation success. Here, in an extract from his book, AI for Business: A practical guide for business leaders to extract value from Artificial Intelligence, Peter Verster, founder of Northell Partners, a UK data and AI solutions consultancy, explains four of them.
1. Agility
Around 86% of software development companies are agile, and with good reason. Adopting an agile mindset and methodologies could give you an edge on your competitors, with companies that do seeing an average 60% growth in revenue and profit as a result. Our research has shown that agile companies are 43% more likely to succeed in their digital projects.
One reason implementing agile makes such a difference is the ability to fail fast. The agile mindset allows teams to push through setbacks and see failures as opportunities to learn, rather than reasons to stop. Agile teams have a resilience that’s critical to success when trying to build and implement AI solutions to problems. 数字化转型网（www.szhzxw.cn）
Leaders who display this kind of perseverance are four times more likely to deliver their intended outcomes. Developing the determination to regroup and push ahead within leadership teams is considerably easier if they’re perceived as authentic in their commitment to embed AI into the company. Leaders can begin to eliminate roadblocks by listening to their teams and supporting them when issues or fears arise. That means proactively adapting when changes occur, whether this involves more delegation, bringing in external support, or reprioritizing resources.
This should start with commitment from the top to new ways of working, and an investment in skills, processes, and dedicated positions to scale agile behaviors. Using this approach should lead to change across the organization, with agile principles embedded into teams that then need to become used to working cross-functionally through sprints, rapid escalation, and a fail-fast-and-learn approach.
2. Trust
One thing we’ve discovered to be almost universally true is that AI transformation comes with a considerable amount of fear from the greater workforce, which can act as a barrier to wider adoption of AI technology. So it’s important to address colleagues’ concerns early in the process.
To help people adjust to the potential shift, I suggest the following:
1. Maintain integrity: There are several ways you can help ease worries across your organization, but first it’s crucial to be honest. If AI will lead to job losses and redeployments, be upfront about it. Building trust begins with honesty and integrity. Giving people a sense of certainty as early as possible, whether that’s reassuring they’ll be retained or putting in place support for redeployment, will help reduce AI anxiety.
2. Support people creatively: Look at the skills you require across your business and create an environment of continuous learning, focusing on adapting skills and roles to the future shape of the business. Empower employees to gain skills in data science, data analytics, ML, and project management. Also consider job shares, part-time hours, or flexible contracts where redeployment isn’t appropriate.
3. Explore applications: Encourage team members to find ways AI will support them to be more efficient and increase their value. Help them visualize AI as another tool they can work with, rather than as a replacement for their capabilities, and enable them to gain the knowledge, skills, and experience to stay current and thrive in the workplace of the future. 数字化转型网（www.szhzxw.cn）
3. Customer orientation
Organizations that center their AI projects around customer ease and experience tend to see more successful outcomes. Ask yourself these three questions and try some of the things suggested before starting:
1. How can I improve the customer journey?
Consider doing a ‘mystery shop’ of your own process to understand where friction occurs. When you have an idea of areas that could be improved, look at the ways AI could be applied to remove barriers or inconveniences. Zara’s trial of self-checkouts in their stores, for instance, was originally met with resistance, but when customers began to benefit from shorter waiting times, they soon accepted the change as a success.
2. How can I save my customers time and money?
Electrical giant Phillips cleverly responded to customer concerns about energy costs, despite not being an energy company. By pivoting toward smart home technology and energy-efficient solutions for their customers, they found a way to use AI to help customers save time and money (remotely starting the washing machine, smart thermostats, occupancy sensors), while encouraging them to buy Phillips products. 数字化转型网（www.szhzxw.cn）
3. How can I better align my products and services to customer needs?
Try surveying your customers to find out what they look for from your product or service. It’s easy to assume you know exactly what their pain points are, but as customer expectations rapidly shift in today’s digital world, so too do customer needs. British online bank Monzo asked their customers what support they’d like, and the overwhelming response was help with increasing savings. In response, Monzo implemented AI to analyze customer transaction data and automatically categorize expenses, offering spending summaries, savings targets, and real-time notifications to help customers track their expenses, identify areas of overspending, and encourage better saving habits.
4. Innovation
It’s companies that encourage and reward innovative thinking at every level that see the most success with their AI and digital projects. Embedding innovation into an organization often requires a change in mindset — one where experimentation is rewarded, and failed projects are seen as an important part of the learning process. To create an environment that fosters innovation, it’s important people are permitted to fail and empowered to take calculated risks.
So consider the following aspects of your business to understand if it’s a place where innovation can thrive: 数字化转型网（www.szhzxw.cn）
- Are there any incentives in place to encourage innovative thinking and problem solving?
- Do employees feel empowered to make decisions or feed back ideas to their managers?
- Are team members disincentivised from taking risks due to fear of repercussions or attitudes?
- Is there a team or forum in place to research and support innovation across the business?
- Are leaders open to hearing ideas and feedback from their team members?
- Do leaders introduce new ideas and/or support ideas when they’re presented, and are they themselves open to change?
Setting the groundwork for innovation through these four core principles is what will create a stable foundation for AI implementation in a way that’s helpful, strategic, and lasting. This is what characterizes successful projects, and where organizations properly assess their readiness for AI.
本文由数字化转型网（www.szhzxw.cn）转载而成，来源于CIO.COM；编辑/翻译：数字化转型网宁檬树。
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