Let’s be honest from the start: The journalism and media business is one of the most obvious low-hanging fruit for AI disruption. Excuse me for a bit of navel-gazing here — but this hits particularly close to home for me, both personally and professionally, in my role at Techstrong. Transparency matters: So let me lay out a simple truth — every media outlet is using AI today. If they aren’t admitting it, they are lying.
Here at Techstrong, we live by one simple principle: Human-in-the-loop. We have a layered editorial process: Articles authored by our in-house editorial team (like this one), content created by contracted writers, pieces submitted by contributors from around the world (we review these closely to ensure they aren’t just “AI slop”), and syndicated RSS-feed content from networks like the Security Creators Network over at Security Boulevard, where our control is lighter. We aim to be open about how we operate.
When I started looking at AI, I was skeptical. AI? A tool, for sure — but an author? Far from it. I firmly believed that the human writer, the storyteller, the journalist with the beat and the insight, remained irreplaceable. Over time, as I saw AI’s utility up close, saw it improving day by day, week by week, release by release, that skepticism softened — yes, it is a tool, a powerful one, growing more powerful every day — but it is still not the author. And I still believe that with conviction. To paraphrase Billy Joel, “AI can’t start the fire,” only the human has the spark.
What started this navel-gazing exercise was a recent article in The New York Times (Nov. 7, 2025) that makes this very point: Media organizations are using AI for a wide variety of jobs: Background research, idea generation, drafting help, headline creation, editing, summarization, and, in some case,s more. But what they are not at least publicly doing (yet) is full autopilot: “Tell AI the subject, it writes the article, hits publish, done.” At least not in the mainstream. The article describes outlets using AI in varying degrees — but always with humans involved.
Why does this matter? Because journalism is fundamentally human. It’s curiosity. It’s asking questions. It’s context, nuance, empathy, even moral tension. A machine can process data, detect patterns, summarize large volumes of text — but it doesn’t live the beat. It doesn’t call the source in the middle of the night. It doesn’t feel the hesitation in a quote. It doesn’t reflect its own biases. It doesn’t start the fire as I said earlier; only the human has the spark.
The Times article shows several examples of AI use in journalism: There are newsrooms using AI to analyse large datasets (financial filings, regulatory transcripts) and suggest story angles. Others use AI to draft bullet points for articles, generate social-media summaries, or even create first-draft headlines that a human then refines. Some are piloting the use of AI to transcribe and summarise interviews, freeing reporters from manual tasks. But across the board, the human remains the author, the gatekeeper, the voice. AI helps — but it doesn’t replace.
At Techstrong, I personally incorporate AI into my writing process. Here’s how:
- I draft an article as a prompt: I write an outline, narrative, key argument(s), voice cues — essentially what I want to say.
- I feed that into an AI model and ask it to improve or flesh out the draft.
- I review the output carefully — I refine, I add voice, I cut, I reshape.
- I submit the refined article to our human editorial team for one more set of eyes before publication.
So yes, I use AI. But the end product is still my thoughts, my voice. The human author still stands front and centre. This is my content, under my byline.
Here’s the key point: Tool versus author. And I believe maintaining that delineation is essential — not just for our process, but for credibility, trust and brand. If a reader knows that a piece was written by a human but assisted by AI, that is far different than one produced by AI and published without human intervention. Disclosure, transparency and clarity matter.
So how disruptive is AI? I’d argue: It’s already very disruptive, but we’re still in the first innings. The disruption is visible in three major ways:
- Workflow re-engineering: AI is accelerating many of the behind-the-scenes tasks — idea generation, research, summarisation, first drafts. Reporters who once spent hours parsing dense filings can use AI to extract key points in minutes.
- Economic model pressure: If AI can produce or help produce more content at lower marginal cost, media outlets face decisions about scale, quality, staffing, value. This creates tension with legacy models built on human effort and expertise.
- Trust & authenticity challenge: If audiences sense content is wholly machine-generated or human oversight is minimal, credibility suffers. Readers may ask: “Is this someone’s voice or a machine’s output?” If the answer is fuzzy, we risk erosion of trust.
The Times article underscores this. It quotes newsroom leaders who say: “We are piloting AI for concept generation/background research/draft summarisation.” They note potential cost savings, but also emphasise editorial guidelines, human sign-off and ethical guardrails. They warn: Full robotic automation of news writing would invite existential questions about what journalism is, and what audiences expect. I couldn’t agree more.
At Techstrong, we designed our process with that guardrail in mind. Human oversight, voice authenticity, quality control and transparency. We believe that AI is a force multiplier, not a replacement. When we syndicate RSS feeds where our control is less, we observe outcomes and flag “AI slop” — low-quality, thin content that feels machine-driven, lacking depth, lacking human insight. The term “AI slop,” for lack of a better label, describes content that may be technically valid but lacks the soul, the nuance, the “why it matters” — and ultimately fails to engage.
Shimmy’s Take
Look—I’m not claiming I’m better or smarter than any other journalist or author. Far from it. We are all experimenting in this brave new world we find ourselves in. The tool (AI) has dropped into our laps and we’re still figuring out how to wield it wisely. The best path forward in my view: Transparency + human judgement + process design. I haven’t even mentioned how I trained the AI I use on my specific style and voice preferences (that’s another post). But I’m engaged, I’m learning, and I’m adapting.
And make no mistake — the disruption has only just begun. Beyond the written word, the audio and video arms of the media business are ripe for transformation. Podcasts, video production, real-time news aggregation, automated clipping, metadata tagging — these areas are already seeing AI runway. Imagine agentic AI workflows in video news: automated sourcing, scripting, b-roll selection, voice synthesis, editing, publishing. The possibility is near. And yet — for now — we still need humans.
Why does this matter? Because we founded Techstrong.ai to document disruptions as they occur: Across DevOps, cybersecurity, cloud, AI, other disciplines as well — and yes, even media. If we want to cover transformational change credibly, we must admit how the disruption is affecting us. How it’s reshaping our workflows, how it challenges our assumptions, how it forces us to ask: “What remains human, and what becomes machine?” That honesty isn’t a weakness — it’s the foundation of trust in this era of transformation.
If media outlets are scrutinising how AI is disrupting content creation and consumption, readers are asking the same questions: “Who wrote this? How was it produced? What role did AI play?” When you answer honestly, you build credibility. When you obfuscate, you risk being found out — and trust is the one asset no media brand can take for granted.
In short: Yes, AI is disruptive in news and media — and the disruption is real, measurable, ongoing. But the disruption is not just external (to your newsroom, your competition, your market). It is internal — to your mindset, your process, your identity as a journalist or publisher. Embrace the disruption, but don’t surrender your humanity. Use AI to amplify, not replace. Keep the human in the loop. Write with voice.
Publish with authenticity. Because at the end of the day, people still connect to people — not just machines.
