People are getting fed up with AI, even as we continue to use it. Just this weekend, an article about a new Pew study claimed, “Americans Have Turned Against AI in Incredible Numbers.” But there’s a positive side to this hypocrisy.

I was at a dinner this week hosted by Jeremiah Owyang at Blitzscaling Ventures. It was a mix of a Jeffersonian dinner with Chatham House rules, which means I get to draw from the conversation themes without naming names or quoting anyone. It's also better than a Polkian dinner where the host goes around eating all your food, but that's enough 19th-century dad jokes for one newsletter. 

Jeremiah threw out this premise as the conversation topic: “What should the AI industry do to rebuild public trust?”

The lack of public trust is clear; I had no issue with that part of the premise. But I did have an issue that the AI industry should be doing something about this, beyond the self-interest we might have if we're running or working for a company whose entire business model revolves around AI.

In my remarks, I lauded the backlash. We need it. It's a sign that people are engaging in the most important skill right now: critical thinking.

We need to ask tough questions of any AI-powered tech or business we engage with. 

We need to ask AI to show its sources when it spits out information.

We need to scrutinize AI for its biases, especially if those biases reflect our own.

We need to move from asking, "What can AI do for me?" to, "Why should I use it?" and, "How is using AI here better than how I was doing things before?"

We need to ask, "What if AI runs rampant without guardrails?"

Many communities during this year's elections will also be asking tough questions like, "What will this data center do to my electricity bill?" and, "What happens to the aquifer levels once this is built, and when the center's usage is at its maximum capacity?" A data center controversy just took down a powerful Utah lawmaker, and he’ll be in good company this year.

Often, the answers to some of the questions above will lead us to find good reasons to adopt or increase usage of AI. Last year, I took on projects I could have only done with AI supporting me in ways like analyzing data. Readers of this missive know about my vibe-coding addiction, where I'm creating things I never would have attempted without it (like this week's SprayCannes.com). 

AI has helped give me straightforward answers to all kinds of day-to-day challenges, like how I might use a health savings account or replace a doorknob. I've recommended that clients use all kinds of AI technologies, from the major LLMs to practically unknown startups, when those products can help them achieve their goals. 

Not all generative AI is slop, but so much of it is egregious. If Generation Alpha kids like my 12-year-old want to insult you or anything else, especially when it seems fake or off-putting, they'll say, "That's AI." My daughter showed me the ads in a game she was playing on her iPad, and the AI slop in each one made me wonder if digital media's creative powers actually peaked in the days of Geocities. The ads were so bad that I paid for the app so she could skip them.

AI is bad marketing. AI is inauthenticity. AI is a shortcut that shouldn’t have been taken. AI is obfuscation. AI is so many of our worst instincts when we feel tired or lazy or just in desperate need of an answer, any answer, even if it isn’t the real one.

AI is us.

AI isn’t going to save us, and it isn’t going to wipe us out. We will fail or flourish (or, we will fail and flourish) of our own accord.

To see the mirror that is AI and bristle at the reflection is the epitome of us recognizing our own humanity.

— David Berkowitz, Chief Community Officer, Marketecture Media

Who: Agency Executives, Brand Marketers, Procurement Teams, CMOs

What: A study released in partnership with the 4As reveals that while nine out of 10 U.S. marketing agencies have adopted generative AI, the focus remains overwhelmingly tied to cost-cutting. The report highlights that agencies primarily leverage the tech for summarizing text, running competitive research, and building routine content assets. Analysts warn that this deep operational focus on productivity and immediate efficiency risks eroding long-term brand differentiation and effectiveness.

Why it matters: Lean into AI for operational efficiency, but ensure your cost savings are actively reinvested into unique creative talent and non-generic customer experiences.

(Forrester)

Who: PR Directors, Communications Managers, SEO Specialists

What: Industry panels at Cannes Lions highlighted a major strategic shift for public relations and corporate communications teams navigating the decline of traditional search engines. Because conversational AI models rely heavily on credible, deeply detailed trade publications and authoritative third-party media to formulate answers, media relations is finding renewed prominence. Marketers are establishing baselines of what conversational tools say about their executives and products to ensure accurate inclusion in AI responses.

Why it matters: Generative Engine Optimization requires a strong foundation of traditional earned media because authoritative, long-form journalism is what trains and feeds AI recommendation layers.

(PRovoke Media)

Who: Marketing Analytics Leads, Brand Strategists, CFOs, CMOs

What: Discussions at the Yale InsightsOn conference emphasized that the primary goal of marketing AI must shift from simple automation to augmented human judgment. Industry panels focused on the dangerous accountability gaps where fragmented analytics, siloed budgets, and over-automated reporting hide true business impact. Industry leaders argued that while AI can instantly streamline routine content analysis and asset generation, human taste, context, and strategic choice remain irreplaceable for true brand equity.

Why it matters: Efficiency metrics are vanity metrics if they do not tie directly to revenue, and AI tools are only as good as the human strategic guardrails guiding them.

(Yale School of Management)

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