Who Wins When AI Does the Work?

As AI multiplies productivity, it's reshaping how—and when—we work, opening the door to a more flexible mix of mental, physical, and personal pursuits.

In his book Deep Work, Cal Newport argues that many of history's most notable achievements — from mathematical breakthroughs to literary classics — were produced in just a few hours of focused, high-value effort each day (and certainly not in 8-hour, office-bound chunks filled with status updates and activity reports).

By now, we know that AI isn't a productivity tool; it's a productivity multiplier — and an inverse multiplier of knowledge work and the traditional 9-to-5 workday.

That means it's coming for almost every part of our work. The right question isn't, "What part of my job can AI do better?" It's, "What part can't it?"

The honest answer for most of us? Very little. Fundraising, research, strategy, budgeting, analysis, and reporting can now be automated or scaled far faster — and often more accurately — than any human team. The only work worth defending is what still requires uniquely human judgment, emotional intelligence, or contextual nuance.

The good news? AI might finally let us achieve the kind of work Newport idealizes: a few hours of deep, meaningful concentration each day, with the rest of our time reclaimed for other activities (or income-earning endeavors) — whether trade or gig work, hobbies, social connection, or family.

Predicted Outcome 1: The Rise of the Contractor and a Renaissance for Trades

Most companies don't need full-time knowledge workers in the traditional sense. Ever-busy full-time employees point to our meetings, report-outs, and "check‑ins" as evidence of the value we add. Contractors, who ebb and flow with demand for work, deliver a clearer exchange of fees for outcomes.

With AI displacement, many of us will diversify our time — using part of the day for focused, high-value knowledge work and the rest for pursuits that add incremental value to our lives, whether for supplemental income or simply for physical or intellectual stimulation.

Whether that looks like launching a startup, starting a local plumbing business, or spending afternoons gardening will depend on our priorities — and whether AI-created value is redistributed to free us to pursue passion projects, or requires us to monetize our extra hours.

Predicted Outcome 2: The Collapse of Traditional Media Economics

Information economics have been shifting since the demise of the legacy network-TV triopoly, but today the pace of change has accelerated exponentially. Traditional media is being scraped and summarized by AI. At the same time, entrepreneurial creators reach audiences at a fraction of the cost (albeit often at the expense of in-depth reporting, journalistic rigor, and fact-checking).

And it's not just hard news. As Kara Swisher and Scott Galloway noted on Pivot last week, their podcast generates $20‑25M annually (growing 20% year-over-year) with just 15 staff, while the recently canceled Late Show with Stephen Colbert generated $60M with 200 employees — and still lost ~$40M annually.

The economics are unsustainable, particularly as the long-standing marriage between capitalism and the First Amendment becomes increasingly tenuous.

Predicted Outcome 3: Brands Will Become Their Own Best Sources

The consolidation of credible journalists, influencers, and podcasters into a small, hard-to-reach group (think Kara and Scott) will make traditional media relations less effective.

Brands can't rely solely on traditional PR alone. They'll need to publish a higher volume of AI-discoverable, subject-authored content — not just for SEO, but to ensure their perspectives train the very systems people use to learn about them.

In this future, brands will be recognized as the most credible voice on their own business, which will matter far more than any earned media hit.

The Takeaway

With the obsolescence of the 40-hour knowledge work week, AI may finally allow us to structure our lives more intentionally each day: a few hours of focused "deep work," supplemented by trade or gig work, plus some physical labor or hobbying, and more time for family and community.

The winners won't just be those who keep up with AI — they'll be the ones who use it to buy back their time and design a life of their own making.

Stop asking if AI wrote it. Start asking: Will AI read it?

Much has been written about the proliferation of AI-generated content across college campuses, newsrooms, and corporate offices. Understandably. We have an almost religious reverence for the written word. By treating prose as a sacred art and a miracle of human creativity, the idea of it being generated by a machine feels fraudulent. Even if the substance of the ideas within are profound, we dismiss it as a fabrication.

As communicators, what if we're approaching this all wrong? What if instead of treating writing like art — something that flows from our creative right brain — we looked at it like math, a left-brain exercise focused on function over form?

When solving an equation, do we care whether a calculator was involved, or are we more interested in whether the answer is correct? There are certainly forms of literature that represent true artistry — works that will endure for their delicately nuanced prose and ability to evoke a deep emotional, philosophical, or intellectual response. But let's be honest: most corporate writing isn't that. Most brand communications, executive letters, and company content serves a fundamentally utilitarian purpose.

We in communications should spend less time debating whether AI should write our content and more time considering whether AI will bother to read it.

In other words, it's more valuable to think of AI as your audience rather than wrestling with its role in authorship.

The organic human audience for long-form corporate communications has always been elusive and is shrinking fast. Sustainability reports, shareholder letters, annual reports, and company blog posts reach increasingly narrow audiences as attention spans contract. But this doesn't make the content worthless — quite the opposite.

It's now more critical than ever to publish owned media that can serve as reliable training data for large language models. Content that comes directly from the source carries inherent credibility. When it's well-written, seemingly objective rather than promotional, and thoroughly cited, it's far more likely to be crawled by AI systems and incorporated into their outputs.

Traditional SEO tactics also help optimize for AI — proper HTML structure, descriptive headings, alt text for images, meta descriptions, and clear semantic markup. If and when training data for LLMs becomes more transparent, optimization tactics will grow more sophisticated.

The future of content strategy isn't about protecting human creativity from AI — it's about ensuring human ideas can be effectively transmitted through AI. The companies that recognize this first will find their messages amplified in ways they never could have achieved directly.

This shift in thinking led me to build a simple beta app that analyzes content for AI discoverability, rating how well a given webpage is structured for AI consumption and offering recommendations to improve crawlability and make its messaging more "algorithm-friendly." You can try it here and share your feedback.

The broader principle is clear: as AI systems become primary information intermediaries, the questions that matter aren't about authorship but about accessibility. Is your content structured in ways that AI can parse, understand, and accurately represent? Are you optimizing for algorithmic comprehension alongside human readability?

It's time to stop worrying about AI writing and start thinking about AI reading.

The PR Agency Model is Broken

Yesterday, Nividia's CEO disagreed with Anthropic's over whether 50% of entry-level jobs could become obsolete with AI. While that claim can be debated for the economy at large, for public relations professionals, the percentage is likely much higher. That's because our $60 billion global industry operates on an antiquated "thinker" versus "doer" dichotomy.

The "doers" are account executives who spend their days developing media monitoring reports, building PowerPoint decks, compiling media lists, and crafting press materials. Their billable hours, marked up in multiples, form the profit-making center of most agencies. The "thinkers" are seasoned professionals who look the part and whose bios appear prominently in pitch decks. They present the work to clients (and often disappear once the business is won).

But in the age of AI, both "thinking" and "doing" can now be handled by artificial agents, not press agents. The only human role that remains essential is that of the "operator" — someone who interprets client needs through human experience, provides necessary data sources, and engineers prompts to derive deliverables that must then be reviewed and refined to ensure they connect authentically with audiences.

Consider what comprises the bulk of junior PR work: writing clearly and succinctly, distilling complex information into pithy soundbites, compiling media contacts, collating press clips, and measuring coverage through online tools. AI can already perform all of these tasks more efficiently and often more accurately than humans. A sophisticated language model can analyze thousands of media outlets simultaneously, craft personalized pitches at scale, and generate comprehensive reports in minutes rather than hours.

Most PR professionals have a conflicted relationship with this reality. Rather than searching for moats to protect and rationalize our roles, we should be embracing these tools — becoming technical experts, learning to (have AI) code, and developing AI applications built on our base of human communications and business experience.

Instead, we're throwing up our elbows to protect our turf, conceding AI's usefulness in summarization or research while insisting that "bread and butter" communications require a human touch that can’t be replicated by robotic prose. We’re in denial.

The PR agency rate card, traditionally overflowing with an endless hierarchy of titles and hourly fees, can be replaced by one line item: the operator. Six-figure monthly retainers suddenly have fewer zeroes. "Doing more with less" becomes more than a trite workplace expression. Without the coordination tax of managing armies of junior staff, agencies (and clients) can actually accomplish more work faster and with dramatically fewer resources.

The agencies that survive the next five years will be those that embrace this transition now. They'll invest in training their teams to become AI operators rather than traditional account managers. They'll restructure their pricing models around value and outcomes rather than billable hours. Most importantly, they'll recognize that the future of PR isn't about protecting the old model — it's about building a better one.