人工智能遭遇文档及人员障碍：数字化和流程数字化
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* Improvement of processes that have previously been manual to be centered on digital exchange of information (i.e. digital signatures)
One way to handle the movement of paper and human-based processes to digital ones is to capture and automate existing processes. Robotic Process Automation (RPA) **** technology provides benefits here by taking existing processes that have previously required manual activity via computer interfaces and transitioning them to automated software-based processes that accomplish repetitive tasks. While RPA solutions don’t aim to modify existing workflows as a primary benefit, they do help to remove the human element from the equation, making those processes more efficient and effective. 处理纸质流程和基于人的流程可以向数字流程转化，其中的一种方法是捕获现有流程及对其进行自动化。机器人流程自动化（RPA）技术可以在这一块提供不少好处，采用手动操作的现有流程可通过计算机界面转换，重复的任务将在基于软件的自动化流程里完成。RPA解决方案的主要目的并不是修改现有的工作流程，但RPA确实有助于移除人为因素，可以令这些流程更加高效。 In addition to process automation, companies looking to digitalize processes can also use process mining and discovery software to analyze existing workflows, provide insights into opportunities to improve and make more efficient those workflows, and add more monitoring and management to human- based workflows as they exist. These “ **Process Capture** ” tools are capable of recording and documenting existing human-based workflows into a machine- understandable format for later automation or analysis. 一些公司除了在做流程自动化方面的工作之外还希望将流程数字化，这些公司可以使用流程挖掘和发现软件分析现有的工作流程，可以找机会进行洞悉改进及提高这些工作流程，在基于人的工作流程中增加更多的监视和管理。这种所谓的流程捕获工具能够将现有的基于人的工作流程以机器可理解的格式记录下来存档，以后可以再对其进行自动化或分析。 **The Relationship between Digitalization and Digital Transformation ** 流程数字化与数字转型之间的关系In addition to the concepts of digitization and digitalization, there’s another term that often gets wrapped into and confused with those terms: digital transformation. **Digital transformation** is a broad idea that has been around for several decades. The concept of digital transformation is the strategic and fundamental change to an organization’s operations such that they are driven by digital processes, technologies and methods to enable high rates of efficiency and operation. Forward-thinking organizations are taking advantage of the tremendous advancements in computing, storage, and software technology to digitally-enable their workforce, and in the process achieving substantial productivity, time savings, and improved citizen or customer satisfaction. 上面讨论了数字化和流程数字化，另外一个术语经常与数字化和流程数字化搅在一起：数字转型。 数字转型是个广泛的概念，存在了几十年。数字转型概念是指组织运营的策略性和根本性变革，组织的运营将以数字化流程、数字科技和数字方法为驱动力，实现高效率和高运营率。具有远见卓识的组织利用计算、存储和软件技术方面的巨大进步对旗下的生产力数字化，同时还在整个过程里实现显着提升生产力、节省时间及提高公民或客户满意度。 Digital transformation rests on a foundation of digital information (digitization) and digital processes (digitalization). It builds upon these to change the very nature of the operation to move beyond simply storing more data and automating existing systems and processes by adding intelligence to their strategies and put the power of cognitive technology to work addressing the more complicated challenges in their work environment that simple automation won’t achieve. Organizations that have successfully digitally transformed their operations have reduced the friction between customer and stakeholder needs and the ability for the organization to satisfy those needs efficiently. 数字转型的基础是数字信息（数字化）及数字流程（流程数字化）。数字转型以其为基础改变营运的实质，超越了以前的营运模式，不再是简单地存储许多数据及将流程自动化，而是在公司策略里加入智能及发挥认知技术的威力，在简单的自动化无法实现的工作环境里应对更复杂的挑战。那些成功实现了数字化运营的组织减少了客户和利益相关者需求与有效满足这些需求的能力之间的摩擦。 **Digitization as a necessary first step for many AI projects** 数字化是许多AI项目必不可少的第一步At first glance, it may seem that digitization has nothing to do with AI. However, digitization is a necessary first step to extracting value from data that is locked in non-digital assets or human-based processes. By first digitizing and then digitalizing processes and documents, greater value can be applied to business organizations letting them tackle increasingly harder business problems of increasingly more strategic value. Without the foundational layer of digitization, organizations can’t apply higher level technology such as AI and ML to extract additional value. After all, data is the foundational layer upon which information, understanding, and insights can be gathered. （编辑：应用网_阳江站长网） 【声明】本站内容均来自网络，其相关言论仅代表作者个人观点，不代表本站立场。若无意侵犯到您的权利，请及时与联系站长删除相关内容! |
