The State of AI in Technical Writing

Embracing the world of content engineering at ConVEx 2024

I've been a bit off grid the last month or so moving house with my family ... packing boxes, hauling furniture. Navigating the chaos of moving houses is a task that AI hasn't quite mastered yet.

But amidst that chaos, I found the time to attend my first-ever conference organized by the Center for Information Development Management: ConVEx 2024.

As an academic, I often find myself immersed in the world of theory and research, with limited time to engage directly with industry professionals. But academia and industry must collaborate more closely to truly grasp the impact and potential of AI.

Academia needs to take a more active role in listening to those on the front lines of innovation. That's why I attended ConVex 2024 – to listen in on the conversations and discussions surrounding AI in the field of technical writing.

As I navigated the conference, I was struck by the level of enthusiasm, curiosity, and healthy skepticism in the sessions and interactions. Technical writers and content professionals are approaching AI with a critical eye, seeking to understand its practical applications, limitations, and impact on their work.

In this blog post, I'll share some of the key insights and takeaways from ConVEx 2024, focusing specifically on the state of AI in technical writing. Instead of fearing AI, most content professionals expect AI to enhance their work through intelligent augmentation, redefining the role of technical writing … a role that has been evolving long before GenAI.

Augmentation, not Replacement

One might expect a conference focused on technical writing to be filled with anxiety about job security. The popular narrative suggests that AI is poised to replace human workers across various industries.

The atmosphere at ConVEx 2024 told a different story. Non-attendees might be surprised there was little fear about AI stealing content professional jobs.

As Paul Mass pointed out, the demand for technical writers is actually on the rise. According to recent projections, technical writing jobs are expected to grow by an impressive 7% over the next few years, outpacing the average growth rate for other occupations by 133%.

This growth is due to the increasing complexity of products and services, the need for clear documentation, and the expanding role of technical writers in user experience design and content strategy.

Many attendees emphasized that AI should augment human capabilities rather than replace them, especially in this context. While AI can automate certain tasks, analyze data, and generate content, it still lacks the critical thinking, creativity, and empathy essential for effective communication across diverse contexts.

At ConVEx 2024, the consensus was that technical writers can use AI to tackle the growing content demands, improve quality and consistency, and free up time for strategic and creative work that matters most.

Content Quality Matters More Than Ever

During ConVEx 2024, speakers and attendees alike emphasized the crucial role of content quality in implementing AI systems, especially at corporate scale.

AI's effectiveness depends on its training data. If the input data is inaccurate, inconsistent, or poorly structured, the AI-generated output will reflect those flaws. In their panel "AI: Should You or Shouldn't You," Dawn Stevens, Val Swisher, Rob Hanna, and Sarah O'Keefe discussed the old adage "garbage in, garbage out" and stressed the importance of "cleaning your corpus" before feeding it to AI systems.

Technical writers and content creators now need to be more vigilant than ever about content quality. Ensuring accuracy, consistency, and adherence to style guidelines is crucial for leveraging AI effectively. Inaccurate or inconsistent data can lead to AI-generated content that is misleading, confusing, or harmful to users.

A key takeaway from the conference was the importance of "IA before AI" – focusing on information architecture before diving into AI. AI is not a magic fix for poorly structured content. Applying AI to a mess of unstructured data is likely to amplify the problems and create even more chaos.

Before starting AI initiatives, organizations must invest time and effort in creating a solid foundation of well-structured, semantically rich content. This involves defining content models, metadata schemas, and taxonomies that accurately reflect the relationships between different pieces of content. By establishing a robust information architecture, organizations can ensure that their content is machine-readable and optimized for AI processing.

The Rise of "Content Engineering"

ConVEx 2024 highlighted the rise of the "content engineer" – a new type of technical writer who understands the entire content ecosystem, from information architecture to user experience, and knows how to leverage AI tools effectively across these contexts.

In his talk "AI Took My Job (to the Next Level)," Patrick Bosek emphasized that technical writers are no longer just writers. He argued that our role is to create information experiences, not just documents. He emphasized that technical writers are custodians of the process of putting information in front of people who need it. This shift in perspective requires technical writers to develop a broader set of skills and competencies beyond traditional writing and editing.

A content engineer bridges the gap between technical and creative aspects of content creation. They understand the importance of structured content, metadata, and taxonomy, and how these contribute to AI systems' success. They are also skilled in using AI-powered tools to automate tasks, analyze data, and generate insights for content strategy and design.

Content engineers are adept at collaborating with cross-functional teams, including UX designers, data scientists, and software developers. They do more than write or communicate. Content engineers build knowledge and maintain the networks around that knowledge create personalized, engaging user experiences.

The rise of the content engineer reflects the growing recognition of content's strategic importance in the age of AI. In "Neuromancer," Joe Gollner noted that AI benefits from large, integrated stores of quality content that are sharply defined and controlled. He described AI as an "organizational brain" that requires a well-structured, semantically rich ecosystem to function effectively.

By embracing this role, technical writers can position themselves as strategic partners in their organizations' digital transformation and help shape the future of content creation and delivery.

Challenges and Opportunities

ConVEx 2024 gave insights into the current state of AI in technical writing and the opportunities it presents. However, like any new technology, AI poses challenges we must navigate carefully.

One main challenge is what some speakers referred to as the "jagged frontier" of AI capabilities, where AI tools vary in sophistication and limitations. Some are advanced at specific tasks, while others are quite rudimentary.

Understanding what AI can and cannot do is crucial for successful implementation. We need to be realistic about AI's capabilities and set appropriate expectations. This requires a deep understanding of the technology and a willingness to experiment and learn.

Integrating AI tools into existing workflows is a challenge that needs careful planning. We need to strategize how AI can improve our processes and skills without disrupting our mission of creating high-quality, user-centric content. This may require rethinking our roles, tools, and collaboration models, and being open to change and adapting as AI technologies evolve.

Despite the challenges, the opportunities presented by AI are immense. Embracing AI as a tool for augmentation and innovation can elevate our work, tackle complex content challenges, and deliver more value to our users.

The rise of the "content engineer" role highlights exciting possibilities for technical writers to expand our skill sets, lead strategic initiatives, and shape our field's future. We can be at the forefront of this transformation and drive positive change in our organizations.

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As for what's next, I'm eager to dive deeper into these topics and share more insights with you. Cyborg's writing has been a bit quiet lately as I've been moving house with my family and finishing the semester. But I'm excited to start things up again and explore the fascinating world of AI in content work with all of you.

In the coming weeks, I plan to:

• Finish developing my Substack course on AI Operations for paid subscribers.

• Share my automation strategies for creating AI systems.

• Continue to create tutorials and demos of useful AI tools.

• Continue my series on AI Literacy for Tech Comm with Content Wrangler, including the next one on May 14th with Nathan Baschez about the AI writing

  tool landscape.

  

These initiatives will provide practical guidance and hands-on examples of how to leverage AI in your work as a technical writer or content specialist. We can address the challenges and opportunities of AI in our field by learning from each other and sharing our experiences.

As always, I invite you to share your thoughts, experiences, and questions. Let's continue to work together to harness the power of AI for good in our field. The future of technical writing is promising, and I'm excited to be on this journey with all of you.