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Knowledge workers spend about 41% of their time creating and preparing documents [1], ultimately wasting valuable time that would have been spent doing more important tasks. The same applies to technical writers who spend countless hours gathering and validating information.
However, things are bound to change as more organizations begin use AI for repetitive tasks. For instance, the use of AI in technical writing and documentation has completely changed how technical content is created, managed, and delivered. AI technologies like Natural Language Processing (NLP), Machine Learning (ML), and Generative AI can automate different parts of the documentation process, making it easier to handle complex information and create clear, concise, and factual documents.
Keep reading to learn about the role of AI in technical documentation, the benefits it provides and some of the best AI tools revolutionizing technical writing and documentation.
While artificial intelligence technology is still far from replacing human intelligence, it can already do certain tasks more accurately and efficiently. For instance, AI is quite proficient in natural language processing, pattern recognition, and decision-making – all of which can greatly benefit technical writers.
Over the past few years, the technical content creation industry has seen growing demand for AI-powered technical writing assistants. These tools streamline the technical writing and editing process, making them invaluable tools for technical writers looking to lighten their workloads.
Traditional grammar and spelling checkers have also gotten an AI upgrade, enabling them to not only spot spelling and grammar errors but offer correct suggestions as well. These features are mostly notable in tools like Grammarly and Quill Bot which leverage AI to enhance the quality and clarity of any piece of technical writing.
Besides the obvious benefit of creating better technical content, technical writers who use these tools correctly also get a chance to discover and improve their technical writing ability as they gain a deeper understanding of grammar and other rules of technical writing.
There’s also the issue with the rapidly evolving tech sector. Any technical writer looking to stay relevant must learn how to properly leverage AI for technical documentation lest they be replaced by those who can.
The benefits of leveraging AI for technical documentation aren’t just limited to increasing productivity and quality of work. They also transcend into several other areas, including:
Some of the greatest challenges in technical writing are gathering, formatting, and organizing information – it’s no wonder it takes so much time and effort to create a single page. AI can automate these processes, freeing up technical writers’ time to focus on more crucial tasks.
Humans, despite our best efforts, are inherently prone to making errors. These errors may range anywhere from inconsistencies in the information to factual incorrectness. AI can effectively identify and correct these errors, enhancing document quality.
76% of consumers get frustrated when they don’t get personalized interactions, which increases the likelihood of losing business. [2] Artificial intelligence can tailor documentation based on specific user needs and preferences, creating more engaging experiences.
The success of any technical content is measured by the value readers gain from it. A wide majority of the audience may also judge the document as irrelevant if it doesn’t meet their formatting and readability expectations. [3]
Artificial intelligence can analyze a technical writer’s style and suggest improvements for better clarity and conciseness, promoting a better user experience.
Document processing is time-consuming and requires tremendous human resources. This means that businesses have to hire additional staff to create, manage, and process documents. Ultimately, this translates to additional operational costs, which can strain the business financially.
By using AI, businesses can replace some of these positions with tools that can automate processes. While the initial costs of implementing AI may be high, using it translates to lower operational costs in the long run.
Collaboration improves how your team works together to solve problems. When done right, it can improve innovation, processes, and communication, streamlining the technical documentation process.
Some of the best AI technical documentation tools also support real-time collaboration and document tracking, leading to transparency and better outcomes.
AI technical documentation use cases cut across various scenarios. Understanding these use cases can help you make better use of these tools.
Some of the most notable scenarios where you can use AI for technical documentation include:
Developing user manuals and knowledge base articles takes a lot of work. First, you need a thorough understanding of product features. You also need to be able to explain technical concepts in clear, concise language. Doing this while minimizing the risk of errors takes a tremendous amount of time and effort.
AI can streamline and simplify these tasks significantly. AI’s remarkable capability to analyze existing documentation, product usage data, and user feedback from support tickets can enable you to develop comprehensive, straightforward user manuals and knowledge-based articles without the hustle of doing the hard bits yourself.
Capturing the entire discussion or key takeaways in a meeting can be a hustle. And, even if you do manage to do it, you’ll still have to spend a lot of time summarizing and compiling the minutes.
Fortunately, you can leverage AI transcription tools to analyze audio or video recordings of the meeting and automatically generate summaries. Some AI tools can also analyze past meetings to create agendas for future meetings, saving time and ensuring consistency and continuity.
Creating and maintaining SOPs can be challenging, especially if you operate in a fast-paced environment. But, with AI tools, you can significantly simplify the process by leveraging AI features like analytics.
Basically, an AI tool can analyze an industry’s best practices and refer to internal knowledge bases to suggest relevant protocols and procedures based on pre-defined parameters. This ensures that all SOPs produced are comprehensive, current, and compliant with industry standards.
Technical documentation is crucial for providing instructions to the users of a product or service and other important information for supporting its development and maintenance. Take the tech sector, for instance. Technical documentation is widely used throughout the software development lifecycle to explain product functionality, plan project activities, and provide clarity on final objectives. [4]
Unfortunately, the process is quite challenging and requires a great deal of time and effort. However, you can use artificial intelligence to analyze system configurations, code samples, and structures, or even use API references to generate technical documentation.
This helps ensure consistency and eliminates the risk of human errors, which is quite common when creating and updating technical documentation.
Contract lifecycle management is one of the most challenging aspects of business operations. Everything from creating documentation and signing and storing contracts to terminating or renewing them requires great attention to detail to avoid non-compliance.
Using AI for contract documentation can significantly simplify the process and minimize the possibility of errors. For instance, you can use AI to create customized contract templates for specific details, enabling you to streamline the contract creation and management process.
You can also use AI to automate reminders for renewals, track contract lifecycle stages, and flag potential issues for review.
Creating and managing business reports is a strenuous, time-consuming, and resource-intensive process that requires you to gather extensive data, analyze trends, and create insightful narratives.
AI technical documentation enables you to streamline business report documentation by automating some of the most labor-intensive tasks in the process. For instance, you can extract and analyze data from different sources like CRM systems, identify key trends, and extract insights from the data, enabling you to create a strategic report narrative.
The past decade has seen a significant rise in the number of AI tools for technical documentation. These tools aren’t just crucial for technical content development; they could also help enhance the quality of documentation and streamline the entire technical documentation process.
Some of the best tools for technical development include:
Grammarly is arguably one of the most popular AI writing assistants on the market. It can quickly identify grammar and spelling mistakes in your documentation and provide writing style suggestions to make the content better.
The AI writing assistant also enables you to set your technical writing goals and the tone you wish to communicate with your audience.
Grammarly also comes with a few other beneficial features like grammar checking, plagiarism detection, essay checking, and many more.
What’s even more impressive is Grammarly is free to use and is accessible through different platforms, including your web browser, as an add-on browser application, Microsoft Word extension, and much more.
The paid plans come with added benefits. For instance, Grammarly Business comes loaded with tons of business tools, Grammarly Education helps with academic papers, and Grammarly Premium offers advanced proofreading tools, plagiarism detection, and various other features.
HyperWrite’s main motive is to change how people interact with written words. This AI writing assistant has become an important resource for researchers, technical writers, and professionals in various fields – a trend that can mostly be attributed to its cutting-edge features and easy-to-use interface.
HyperWrite learns from your learning style and adapts to your preferences. It also has the capacity to promote collaboration and knowledge-sharing. With HyperWrite, several members of your team can work on documents simultaneously and in real time, facilitating seamless commenting and editing.
The platform also has various formatting options and customization tools that enable users to quickly change how their documents look by simply selecting from a wide range of styles, fonts, and layouts. You can also edit multimedia components like video, images, and audio files.
This makes HyperWrite effective in multiple technical writing and documentation use cases, including academic writing, professional documentation, and content creation.
Jasper.ai is a must-have tool for writers. This AI-powered writing assistant is transforming the way technical writers create and manage content by reducing tedious tasks and producing high-quality content quickly.
The AI writing assistant enables technical writers to overcome writer’s block, increase productivity, and improve workflow. The easy-to-use interface enables writers to create outlines, check for plagiarism, and optimize content for different audiences. You can also use Jasper.ai to keep track of your notes and research during the content creation process.
Jasper.ai also comes with various other capabilities, including the ability to generate personalized responses for digital ads and reviews, generate whole documents, and rephrase text to make it easier to read.
The AI writing assistant works well with Microsoft Word, Google Docs, and Grammarly’s grammar checker program.
The technical documentation sector is poised for significant changes with advancements in AI technology. Some key developments to look out for include:
Customers are now demanding more integrated systems in the tech sector, and technical writing software will likely follow suit with more deeply integrated AI tools. This will result in advanced features for content optimization, and the potential for AI to generate content drafts based on outlines provided by the user.
The capability of AI to analyze user preferences will open up new possibilities for highly personalized technical documentation. This may include everything from documentation that adopts the user’s knowledge level, to interactive elements that engage users and enhance learning.
Technical writers can leverage big data through AI technologies to gain insights into user behavior and preferences, ultimately informing documentation strategy in several ways, including:
Technical writing and documentation have taken a major leap with the introduction of AI technical writing assistants and other tools that enable technical writers to create, manage, and share content seamlessly.
This transformation will transform content creation and enhance the applicability of documentation across various sectors. It will also present other business benefits, including cost savings, improved productivity, and enhanced collaboration.
References
[1] Hbr.org. Make Time For the Work That Matters. URL: https://hbr.org/2013/09/make-time-for-the-work-that-matters. Accessed on October 18, 2024
[2]Csgi. com. Enhancing Customer Experience Beyond Personalization. URL: https://tiny.pl/j67nxh2j. Accessed on October 18, 2024
[3] Onlinelibrary.wiley.com. The Effect Of Document Readability On Perceived Familiarity And Relevance. URL:
https://asistdl.onlinelibrary.wiley.com/doi/full/10.1002/meet.14504201282. Accessed on October 18, 2024
[4] Altexsoft.com. Technical Documentation in Software Development. URL: https://www.altexsoft.com/blog/technical-documentation-in-software-development-types-best-practices-and-tools. Accessed on October 18, 2024
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