If there's no company brand to speak of, how can we trust AI?

If you’re still getting your arms around the vibe-coding wave, start with Edition #40 and this LinkedIn post where I share a few of my own experiments (and bruises).

My advice: ride the wave—fast. Build a portfolio of MVP solutions rooted in your subject-matter expertise. Don’t wait for permission.

The flood of product updates also raises a more interesting question than “what’s new?” How do you choose what to trust? Because when the output quality is often good enough across tools, the deciding factors start to look like this:

• Data: what am I giving up to get the “best” answer?

• Ecosystem: is 90% inside one suite better than stitching together five best-of-breed tools?

• Experience: will it work the same on my devices and workflows?

• Values & accountability: do I believe the company’s incentives—and the language of its leaders?

Run that test and the choices get real, quickly: Gemini’s integration is powerful, but what’s the trade-off? ChatGPT can be blisteringly good, but do you trust the direction of Open AI? Anthropic’s safety posture is admirable, but does it constrain what you can do (as people often say Copilot does)? Claude Code is having a moment, but does that capability travel beyond code?

These aren’t just product questions anymore. For some organizations, they’re strategic—and borderline existential.

And that’s the opening for communicators: as capabilities converge, brand, mission, trust, and executive narrative become the differentiators. Right now, that story is underbuilt in most places.

Comms folks: time to step up.

In other news...

Agentic AI will reshape marketing from “messages” to real-time, 1:1 experiences Gartner prediction, Jan 15 | Source

• What: Gartner predicts agentic AI will increasingly handle customer-facing marketing work—shifting content from planned campaigns to adaptive, always-on interactions.

• Why it matters: If the prediction holds, marketing teams built around quarterly campaign calendars and batch-and-blast content creation will find themselves structurally misaligned with how customers actually experience the brand. The shift isn’t just operational—it’s about whether your content infrastructure can support real-time personalization at scale, and whether your approval processes can keep pace when “publish” happens thousands of times per second rather than dozens per month.

• The number: Agentic AI will account for the majority of customer interactions used for marketing by 2027.

AI in game creation will win if it augments craft—not “generative slop” Razer CEO interview, Jan 19 | Source

• What: Razer is betting AI will become a standard layer in creation workflows, especially for QA and assistance, while designing hardware to make AI feel unobtrusive.

• Why it matters: The “generative slop” framing from a major hardware CEO signals where the content creation market is heading—toward tools that enhance human craft rather than replace it. For content teams, this validates investment in AI that speeds up tedious work (QA, formatting, optimization) over AI that tries to do the creative thinking. It’s also a reminder that how AI feels in the workflow matters as much as what it can technically do.

• They say: “We’re going from touchscreens or mice to voice and vision.” — Min-Liang Tan, CEO, Razer

• The number: Razer took $20 reservations for its “Project Ava” concept while gathering feedback.

YouTube will let creators make Shorts using AI versions of themselves YouTube announcement, Jan 21 | Source

• What: YouTube says it will let creators generate Shorts using their own AI likeness—part of a push to ship creator-facing AI tools while tightening enforcement against spammy content.

• Why it matters: This is the platform playbook emerging in real time: give verified creators AI superpowers while cracking down on anonymous AI spam. For brands and communicators working with influencers, it means the creator economy is splitting into those who control their AI likeness and those who get drowned out by synthetic noise. It also raises new IP and authenticity questions—when a creator’s AI twin posts a Short, who’s responsible for what it says?

• They say: “We’ll have more to share soon, including the launch date and how the feature will work.” — Boot Bullwinkle, spokesperson, YouTube

• The number: YouTube Shorts averages ~200 billion daily views.

PR provocateur as creator: Ed Zitron’s AI backlash narrative goes mainstream The Guardian profile, Jan 19 | Source

• What: The Guardian profiles how Ed Zitron—originally from the PR world—has become a prominent creator shaping skepticism about generative AI’s economics and social impact.

• Why it matters: Zitron’s rise shows how the “AI skeptic” narrative has moved from tech Twitter fringe to mainstream media validation. For communicators, this matters because he’s giving audiences permission to doubt AI hype—and he’s doing it with PR expertise, which means he knows how to frame, package, and distribute a counter-narrative effectively. When your skeptic is a former PR pro with a media platform, you’re not fighting random trolls—you’re up against someone who understands your playbook.

• They say: “AI has taught us that people are excited to replace human beings.” — Ed Zitron, tech PR professional / media creator

• The number: Zitron’s newsletter has 50,000+ subscribers.

GenAI is mainstream in PR—but “high integration” is still rare Meltwater / WE report, Jan 14 | Source

• What: A new State of PR report says most PR teams now use generative AI for core workflow tasks, but relatively few say it’s deeply embedded in operations.

• Why it matters: The gap between “we use it” and “it’s built into how we work” is where most PR teams are stuck—and it’s creating a false sense of progress. Experimentation without integration keeps AI in the “nice to have” category rather than making it a competitive differentiator. For communicators, this is a wake-up call: if 90%+ are dabbling but only 13% have deep integration, the real opportunity is in moving from pilots to process change before competitors do.

• The number: Report surveyed 1,100+ PR/comms professionals worldwide; 90%+ have integrated genAI into workflows, but only 13% call it “highly integrated.”

PR’s AI usage levels off—but governance and paid tools surge Muck Rack report, Jan 21 | Source

• What: Muck Rack says PR is entering a “mature” phase where adoption isn’t growing as quickly, but policies, training, and paid-tool usage are rising sharply.

• Why it matters: The data reveals a divide forming between teams that experimented and teams that operationalized. Organizations now investing in governance frameworks and paid tooling are signaling they see AI as infrastructure, not novelty—which means competitive advantage is shifting from “do you use AI?” to “have you built the guardrails and capabilities to use it consistently and well?” Teams still in the curiosity phase are falling behind.

• They say: “Success now depends on whether teams are given the tools, training and permissions to use it effectively.” — Greg Galant, Cofounder & CEO, Muck Rack

• The number: 76% of PR pros use genAI; 51% have an AI use-case policy (up from 21% in 2024); 75% use at least one paid AI tool (up from 57%).

The AI future should be “human in the lead” Accenture CEO interview, Jan 21 | Source

• What: Julie Sweet frames the comms challenge for leaders as narrative, not novelty—positioning AI as a growth lever while directly addressing employee anxiety and the “human in the loop” framing that can feel demotivating.

• Why it matters: Sweet is giving executive communicators a blueprint for the AI narrative that might actually land with skeptical employees. “Human in the loop” sounds like “you’re QA for the robot”; “human in the lead” sounds like “you’re the strategist with a powerful tool.” For leaders trying to message AI transformation, the lesson is that how you frame human agency determines whether people hear empowerment or replacement. This is the language test for whether your AI rollout creates energy or anxiety.

• They say: “Companies are led by humans, and they will win by tapping into human creativity.” — Julie Sweet, Chair & CEO, Accenture

• The number: Accenture’s Pulse of Change survey (7,000 workers) found >75% of leaders see AI’s bigger promise as revenue growth; only 20% of non-C-suite feel like “active co-creators” shaping AI at work.

“Trust in AI Alliance” targets standards for agentic AI Thomson Reuters announcement, Jan 14 | Source

• What: Thomson Reuters is convening AI leaders to define practical principles for trustworthy agentic systems—especially in high-stakes information environments where credibility is the product.

• Why it matters: When a legacy information business convenes OpenAI, Anthropic, and cloud giants to define trust standards, it’s a signal that “move fast and break things” is over in sectors where accuracy isn’t negotiable. For executive communicators, this is about positioning: leaders who can speak fluently about trust frameworks, transparency mechanisms, and accountability in AI will sound serious; those who can’t will sound reckless. The gap between “we use AI” and “we’ve defined how we ensure AI is trustworthy” is becoming a reputational divide.

• They say: “As AI systems become more agentic… building trust… is essential.” — Joel Hron, Chief Technology Officer, Thomson Reuters

• The number: The alliance identified 3 foundational challenges: context integrity, immutable provenance, and security against adversarial prompts.

Slackbot gets “agentic” upgrades—turning chat into a workflow front door Slack product update, Jan 14 | Source

• What: Slack’s direction is clear: internal comms channels become execution surfaces, with bots that can take actions across apps—raising the bar for governance, permissions, and employee trust.

• Why it matters: This shifts internal comms from “where information lives” to “where work gets done”—which means every bot interaction becomes a trust test. If employees don’t understand what the bot can access, what actions it can take, and when it’s escalating to a human, you’ll get resistance disguised as “technical issues.” For IC teams, this means your job now includes explaining and governing agentic workflows, not just broadcasting messages. The new risk isn’t “did people read the email?”—it’s “do people trust what the bot just did on their behalf?”

• The number: Slackbot is the most quickly adopted feature in Salesforce’s 27-year history.

Employee confidence is high—but co-creation is low Accenture survey, Jan 21 | Source

• What: Accenture’s survey of 7,000 workers found employees largely tolerate AI investment, but most don’t feel involved in shaping how AI changes their work.

• Why it matters: For internal communicators, this is an early warning signal of resistance and rumors. When only 20% of non-executives feel like “active co-creators” of AI at work, you’ve got a legitimacy problem that no amount of town halls or FAQs will fix. Employees who feel AI is being done to them rather than with them are the ones most likely to distrust leadership messaging, circulate worst-case scenarios, and quietly disengage. The gap between “we’re investing” and “you helped decide how” is where culture breaks down.

• They say: “We do think there is still a lot of anxiety…” — Julie Sweet, Chair & CEO, Accenture

• The number: Only 17% of employees say they enjoy using AI and actively seek new ways to apply it; 83% believe their org would keep investing even if there’s an AI bubble burst.

Investors are asking whether the “AI bubble” has popped—IR is getting harder CFO Brew analysis, Jan 21 | Source

• What: The piece frames a new IR reality: executives must explain AI strategy with credible economics (capex, margins, timelines), not just capability demos.

• Why it matters: The market is increasingly allergic to vague “AI transformation” talk without proof points, which means IR teams now face a double bind—leadership wants to signal AI ambition, but investors want to see ROI discipline. For communicators, this changes how you prep executives for earnings calls and analyst meetings: demos and vision aren’t enough anymore. You need clean answers on where the spend is going, what the margin impact will be, and when shareholders should expect returns. The companies getting this right are winning credibility; those still waving hands are getting punished.

• The number: 60% of survey respondents in Motley Fool’s 2026 AI Investor Outlook Report believe AI-focused companies will deliver strong long-term results.

AI “themes” increasingly show up in forward guidance language InterDigital outlook, Jan 20 | Source

• What: Investor-facing releases are increasingly baking AI into positioning and guidance—making consistency across earnings scripts, analyst Q&A, and PR messaging a credibility test.

• Why it matters: When AI moves from “innovation update” slide to forward guidance language, it becomes a commitment the market will measure you against. For IR and corporate comms teams, this means every piece of AI messaging—press releases, earnings scripts, analyst briefings—now has to align on terminology, timelines, and expected outcomes. Inconsistency between what the CEO says on CNBC and what’s in the 10-Q is no longer just sloppy; it’s a red flag that you don’t have a coherent AI strategy. The narrative has to hold together across channels or you lose credibility fast.

• The number: InterDigital projects 2026 revenue of $675-$775 million, explicitly framing AI as a growth driver.

News Corp taps Symbolic.ai to boost newsroom “style” + speed TechCrunch report, Jan 15 | Source

• What: The story signals a pragmatic newsroom pattern: AI is being adopted less as “robot reporter” and more as an internal productivity layer—summarization, translation, structure, and consistency.

• Why it matters: This is the practical version of AI in journalism—not the “AI writes the story” panic scenario, but “AI handles the tedious formatting, translation, and structure work so journalists can focus on reporting and analysis.” For communicators watching how newsrooms adopt AI, the lesson is that credible publishers are treating it as workflow infrastructure, not replacement labor. It also means pitches and press materials that arrive pre-optimized for these AI productivity tools (clean structure, consistent metadata, translation-ready formats) may get processed faster than messy, unstructured content.

• The number: Dow Jones Newswires’ early use of Symbolic yielded productivity gains of up to 90% on complex research tasks.

UK regulator keeps probing deepfake safeguards—pressure rises on platforms Reuters report, Jan 15 | Source

• What: For journalism, the implication is verification load: regulators and platforms are still wrestling with deepfake abuse controls, which increases the operational importance of provenance, labeling, and rapid debunk workflows in newsrooms.

• Why it matters: Newsrooms are now stuck between two pressures—the speed of synthetic content creation and the slowness of verification infrastructure. When regulators are still figuring out deepfake controls and platforms are playing catch-up on labeling, journalists become the de facto frontline for spotting and debunking AI-generated misinformation. For communicators, this means any visual content you distribute needs bulletproof provenance metadata, because the trust cost of distributing something that turns out to be synthetic is climbing fast. Newsrooms burned by deepfakes will remember who sent them questionable material.

• The number: Ofcom could impose penalties of up to £18 million, or 10% of X’s global revenue, if X breaches safety laws.

Holocaust memorial condemns AI Auschwitz images spreading on TikTok Reuters report, Jan 16 | Source

• What: The story underscores a new disinformation challenge: synthetic “historical” imagery can travel as emotional truth, outpacing fact-checking and forcing institutions to respond quickly with clear, provenance-based rebuttals.

• Why it matters: AI-generated historical imagery is particularly dangerous because it exploits emotional resonance and people’s assumption that “if I can see it, it must have happened.” When fake documentary-style visuals spread faster than institutions can respond, the damage is done before the correction lands. For communicators, this is a warning about the new risk landscape—any organization with historical authority or educational mission now needs rapid-response protocols for synthetic content, because waiting 48 hours to issue a statement means millions have already internalized the fake as real.

• The number: The Auschwitz Museum receives 4-5,000 comments daily on its social media posts, creating significant challenges for synthetic content moderation.

California AG sends cease-and-desist to xAI over deepfake sexual images Reuters report, Jan 16 | Source

• What: This is the comms-risk playbook in real time: brand, legal, and platform comms collide when synthetic abuse content goes viral—triggering regulator pressure, policy changes, and reputational damage control.

• Why it matters: When state attorneys general start sending cease-and-desist letters over AI-generated content, the compliance and reputational stakes have escalated beyond “content moderation debate” into “legal liability and brand crisis” territory. For platform companies and AI providers, this signals that reactive content policies aren’t enough anymore—regulators want proactive safeguards built into the product, not just cleanup after harm spreads. For corporate communicators, this is a case study in how quickly “AI innovation” narratives can flip to “AI accountability” crises when synthetic abuse content enters the conversation.

• The number: More than half of the 20,000 images generated by Grok between Christmas and New Year’s depicted people in minimal clothing.

À bientôt!