By: Rakesh Shukla, Founder & CEO, TWB_
Natural Language Generation and Natural Language Processing are going to be the third stage of Automation. Are you ready?
The machines are coming. Not only to automate content that has been in play with Enterprise Content Management (ECM) for many decades but to generate it as Natural Language Generation (NLG).
Content automation has been growing in banking and insurance too, with standard operating procedures to be made available in a regulatory environment across languages and geographies.
Enterprise Content Automation
Why does an enterprise need content? For the simple reason that better content makes for better decisions both, by external as well as internal customers. Nearly everyone has come across poorly presented content, and recognizes the reach of its impact, whether it takes place before purchase, during use, or while troubleshooting. This could impact consumers such that they may not buy the product, or if they do, they may not recommend it to others.
Content quality depends on professionals and teams with three principal attributes: great English, a good grasp of the technical domain, and the understanding of tools and technologies to present content. As any C-level executive or hiring manager will tell you, this combination of skills isn’t easy to find. Content quality has always included the dimensions of style, accuracy, consistency, and ease of comprehension.
Content Automation allows for enterprises to meet their deadlines, while matching the quality and pace of production of content that is required in today’s business world. Beyond solving today’s problems, content automation can also enable a company to be more agile including the ability to create new information products and communications dynamically, as well as quickly support new generations of devices and formats such as eyewear displays, smart watches, and more.
As AI becomes stronger, non-data-led content recognition and generation will explode. Already the capability to create product descriptions for e-commerce, datasheets for print and PDF exists.
How should enterprises go about Automating Content?
If enterprises want to start on Content Automation, first prepare the groundwork. It starts with creating a Content Automation strategy.
Laying down the strategy should be simple: figure out the structure, pour your content in, automatically extract content as needed, and publish it everywhere. Once that is achieved, create engines that generate content to fill in. Therein lies the complexity.
Pre-automation stage: First, create the framework to provide the right content to the target customers at the right time. Few brands know how to do this well. If you want to create an exceptional experience, you need to figure this out.
Content Automation: Second, we need processes and workflows to manage all this content. While quality content is always a priority, we also need to figure out how to automate what we can so that our efforts scale.
Automating content generation: Once this is achieved we figure how to generate content; make it distributable as marketing content, learning content, and technical content; and make it ubiquitous across distribution channels.
AI can research swathes of data far quicker than a person, and compile relevant information and present it in suitable ways. The technology relies on two things: smart algorithms and data points to create the context base on which to parse and understand context. Language Processing and AI subsequently help organizations globally streamline their content processes, and enable them to deliver business-critical content with precision typically with the use of an Enterprise Content Management system.