--- title: "12 predictions for tech comm in 2026" date: 2026-01-01 description: "1. AI hype levels off 2. The virtuous cycle starts to become apparent 3...." canonical_url: https://idratherbewriting.com/blog/tech-comm-predictions-for-2026 --- # 12 predictions for tech comm in 2026 ![Predicting paths for the future](https://s3.us-west-1.wasabisys.com/idbwmedia.com/images/predictingpathsfuture.jpg) See also a podcast where I discuss these predictions and others with Fabrizio Ferri-Benedetti: [Podcast: Tech comm predictions for 2026 (Phase One)](/blog/predictions-2026-tech-comm-podcast) ## 1. AI hype levels off **In 2026, the hype around AI will level off and a more practical view will take hold.** Productivity gains from AI aren’t on an exponential curve. The velocity/productivity boost from AI has a ceiling, and people will start to recognize this. Instead of thinking that tech writers can be entirely replaced by AI, companies will adopt a more realistic view that AI, in the hands of a skilled tech writer, can augment their output at most by a factor of 1.5 or so. When I look at my own changelist stats for the year, I think I see about a 10% increase from the past year (when I was also heavily using AI), but nothing like the massive bump from my pre-AI time. As imperfect as my changelist stats are (version control is easily distorted by site migrations or new API docs), it’s pretty clear that the productivity bump occurred over the *last* two years (when AI hit the scene), and now things are leveling out. It’s not an unlimited growth curve, as the validation bottlenecks and other manual process overhead limit velocity. Many tech writers are just getting started on their AI journeys. As they gain familiarity with AI tools (like [Antigravity](https://antigravity.google/), [Gemini 3](https://gemini.google/), or [Claude Code](https://claude.ai/)), they’ll discover this initial boost. Reports like from index.dev provide some quantitative data around the productivity boost, noting that “developers report that AI tools raise productivity by 10 to 30% on average” ([Developer Productivity Statistics with AI Tools 2025](https://www.index.dev/blog/developer-productivity-statistics-with-ai-tools).) This aligns (at least conservatively) with my own qualitative experience, though it seems low. The report adds an interesting nuance to this picture, noting that “When tested, the same developers actually took 19% longer to finish their tasks with AI,” even though “developers still believed they worked 20% faster with AI.” Furthermore, “46% of developers say they don’t fully trust AI outputs.” This paradox suggests that while the *perception* of velocity is high, the actual output may lag due to the overhead of reviewing and fixing AI generated content. Because of the distrust of AI outputs, I see more emphasis on review and validation tools, since this is where the bottleneck is. Writers need more confidence that AI outputs are correct, and tools/techniques that can help with this will be in high demand. ## 2. The virtuous cycle starts to become apparent **In 2026, we’ll start to see the effects of the virtuous cycle of AI adoption.** Higher quality docs lead to better code, which leads to more robust tools, which in turn leads to better products. This cycle is powered by usage data: as people use AI-infused products, that data feeds back into the models to improve them, which drives further usage. As Erik Trautman notes that this “ever-growing data set” allows the product to pull ahead at an increasing rate ([The Virtuous Cycle of AI Products](https://eriktrautman.com/posts/the-virtuous-cycle-of-ai-products)). Those companies embracing AI will move faster and do more than those that don’t. It won’t be a rapid trajectory, just a gradual rising of the company’s overall economic ocean and flourishing in slow, steady, impossible-to-dismiss ways. But AI-based companies will start to move faster in a noticeable way. I’m inclined to believe in the virtuous cycle because I see its impact on my docs. The more accurate my docs are, the easier it is to add new docs and make other updates. Using AI, I’ve made comprehensive API diagrams and other attribute tables that make it easier to understand and review each additional update. ## 3. Hiring will shift from headcount to high-value skills **In 2026, hiring numbers will likely remain flat for generalist roles, and many tech writers who leave a team might not have their positions backfilled.** The market for technical communication will continue to be challenging for those relying solely on traditional writing skills. Companies are under increased pressure to fund the “AI arms race”—buying expensive compute and infrastructure—and to offset those costs, they’re becoming far more selective with headcount. This trend not only aligns with what I’ve seen in my own team’s dynamic (it’s been years since we expanded our team with an additional person), but also with the “Hiring less, expecting more” trend identified in [PwC’s 2025 AI Jobs Barometer](https://www.pwc.com/gx/en/services/ai/ai-jobs-barometer.html). PwC found that while the number of people working in the Information, Communication, and Technology (ICT) sector has nearly doubled since 2012, the share of job postings for these roles has dropped by nearly half. This signals a major shift: companies aren’t flooding job boards to fill seats; they’re hunting for a smaller number of specialized experts. Data from the World Bank’s [Digital Progress and Trends Report 2025](https://openknowledge.worldbank.org/server/api/core/bitstreams/f2509a0f-7153-4f32-b180-bc11e90c4940/content) confirms this decoupling. While the broader tech hiring market has softened, demand for specific AI skills has gone up. The report notes that online vacancies requiring Generative AI skills rose ninefold between 2021 and 2024. Further, more than 70% of these high-value AI job postings are located in high-income countries; this signals a consolidation of talent rather than a broad, global expansion. The takeaway for technical writers is that job security might now hinge on specialization. Generalist roles are fading, but specialized, AI-literate roles are commanding a premium. The market isn’t hiring for more people; it’s hiring for more AI specialists. If you’re looking for a job as a technical writer, specialize in AI and doors will open. ## 4. More tech products everywhere **In 2026, we’ll see significantly more technology products released.** The fundamental nature of technology is that tech begets tech. What are most people doing with their AI tools? They’re writing more code, launching more tools and scripts and apps and frameworks. AI leads to more tech tools, which means more engineers building more tech-based products faster and more prolifically. The pace of change will continue to accelerate, with technology products saturating the economy. I’ve seen this trend in the precambrian-like prolification of tools in my workplace. There’s a palpable fatigue whenever someone announces yet another tool. Recently I was in an AI-focused tech writer meeting where someone was heralding a new AI tool, and a person raised their hand and said (more or less), “Is this *yet another tool* to learn?” This technology saturation isn’t just about more apps; it’s about AI becoming invisible infrastructure at every point in the code/content development journey. As Help Net Security says in a report titled [Five identity-driven shifts reshaping enterprise security in 2026](https://www.helpnetsecurity.com/2025/12/24/five-identity-driven-shifts-reshaping-enterprise-security-in-2026/), “AI is now embedded at every layer of the organization, from workflows and applications to customer experience, DevOps, IT automation, and strategic decision making.” I see this daily: when I read a bug, AI is there to summarize it. When I create a new CL, AI is there to read my changes and type a description. When I review code, I can prompt AI to look for errors in the changed files. When I browse the code base, AI is there to interpret it. When I write my weekly report, AI is there to help collect all my week’s highlights. When I go bed at night, AI is there to tuck me in. The AI infrastructure isn’t consolidated in a few apps; it’s spread across the entire codebase, creating a dense, interconnected web of automated agents and tools ready to assist us seemingly everywhere.