Bill Gross has been here before.
Back when the Internet was young, when the dot-com wave broke across the monied shoals of Wall Street opportunism, Gross built a world-changing company, took it public, then sold it for billions.
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BULLSHIT!
That’s what I found myself yelling at a recent board meeting, unimpeded by my usual filters of propriety or self-restraint. But I couldn’t help myself. The board was debating whether AI was going to come for all of our jobs, and someone had just referenced an article which said it wouldn’t be long before AI was doing the work of most doctors, lawyers, and – this is where I broke – writers.
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According to scholar Carlota Perez, one of tech’s most revered theorists, society regularly goes through technology-driven “revolutions.” These structural cycles can take fifty years or more, and are defined by core technologies which shape life as we know it. Her list of previous cycles include the Industrial Revolution; The Age of Steam and Railways; The Age of Steel, Electricity and Heavy Engineering; and The Age of Oil, the Automobile, and Mass Production.*
Back in the early 2000s, Perez has identified the Internet (more formally, ICT, or “information communications technologies”) as the dominant technological force driving our current age. Perez’s framing has been a favorite of pundits ever since – and has played a central role in the debate as to whether a much-hyped “Next Big Thing” – crypto, the metaverse, quantum computing – is merely a feature of an ongoing revolution, or the starting gun to an entirely new age.
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[Second in a series, first post here]
This past week, Wall Street caught up with the rest of us and realized that Google has lost its monopoly grip on search. The trigger wasn’t Google losing an anti-trust case – that happened last summer. Nor was it the first ten days of Google’s ongoing search remedies trial. Instead, it was a statement just two days ago by an Apple executive, Eddie Cue, which led to an almost instantaneous panic amongst investors.
Cue told the court that consumers’ preference for using AI agents had led to a decline in search traffic inside Apple’s Safari browser (Google pays Apple more than $20 billion a year to secure that traffic – a major focal point of the government’s case).
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Over the past 25 or so years, I’ve argued that Google has built a massive database of intentions – the aggregate result of every search ever entered, every page of results ever tendered, and every path taken (there’s a lot more to it, but that’s the key stuff). I’ve tracked this extraordinary artifact since 2003, and have come to believe that Google’s control over it has become a inhibitor to innovation and flourishing in our society.
The US government – yes, even this one – agrees with me. In the nearly three decades since Google first launched, the company has gone from champion of the open Internet to established monopolist whose principle business is protecting its profits. With the advent of consumer AI, that principle business is imperiled. Google is protecting a revenue stream that it must understand is no longer defensible, either by law or by practice.
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I’ve been traveling for the past week, and ignoring the news as best as one can while on the road. But when The Information posted this doozy of a story – OpenAI Forecasts Revenue Topping $125 Billion in 2029 as Agents, New Products Gain – I made a note to myself: Grok those numbers, and see what on earth is going on.
By the time I got home, Ed Zitron, currently the tech world’s most fervid antagonist – had beat me to it. Zitron dissembled The Information’s reporting, noting that the piece takes “great pains to accept literally everything that OpenAI says as perfectly reasonable, if not gospel, even if said things make absolutely no sense.”
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After I write my annual predictions, I keep a little file of stories that relate to my prognostications. The most active one so far – if you tune out my opening line that “this is not going to be a normal year” – is #3: “2025 will not be the year AI agents take off.” It may be hard to recall, but by the end of last year, AI agents and “the agentic web” were all the rage, pushed as the Next Big Thing by just about everyone who had a stake in tech’s Numbers Go Up economy.
But it struck me that there was a lot of wood to chop between the hand waving of tech optimists and the reality of how complex systems actually work. I noted that the most significant structural impediment was Big Tech’s business model, which is reliant on consumer advertising and enterprise subscriptions and sales. Agents, as I pointed out in Where’s The Business Model in Chat-Based Search?, will likely undermine traditional consumer advertising models employed by Google and Meta. As for the enterprise, well, inter-operability been the bugaboo and the holy grail of enterprise software for as long as enterprise software has existed. Without protocols that allow developers to integrate across diverse systems, agents are never going to take off.
It takes years, not weeks, for such protocols to emerge and gain widespread support. Earlier this year I wrote about Anthropic’s MCP, which addresses a core issue: data connectivity (OpenAI recently announced support for MCP.) But MCP doesn’t address a host of other integration issues, including user interface, directory services, communication handling, and many other dull-but-important tasks. Aware of this problem, Google this week announced another protocol: A2A.
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There’s an old maxim in the news business: Stories in which a dog bites a man are uninteresting. But a man biting a dog? Now that’s worth writing up!
Last week Google released a report on the value of news to its business. Its conclusions minced no words. Here’s the money quote: “…news content in Search has no measurable impact on ad revenue for Google.”
On first glance, Google’s experiment feels like a Dog Bites Man story – everyone knows news doesn’t drive advertising revenue – hell, I lived that truth most of my career, most recently with The Recount, which attempted to convince advertisers to support high-quality news coverage across video and social media (we couldn’t). But look a bit closer, and you might just see a Man Bites Dog story after all.
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Two years ago I wrote a series of posts exploring the business model and interface implications of generative AI-based search. At the time, it was not clear how Google would respond to the existential threat that ChatGPT and its peers seemed to present. If it took root, a chat-like interface to search would fundamentally disrupt Google’s core revenue model. What was the company going to do about that?
I noted that six months into the GPT revolution, Google’s response seemed to be overly cautious. I encouraged the famously slow-moving company to go on offense: “It’s time to push something out to market, it’s time to declare yourself the leader in this new market, and it’s time to lay out a vision for what the future of computing will look like,” I wrote. “Imagine if they had waited until they figured out how to make money before launching Google Search?”
Read MoreThe data comes from Adobe’s Analytics platform customers, and it paints a fascinating if incomplete portrait of how consumers conduct their online research. Yes, traffic from AI chatbots has risen more than 1000% since last summer, but….on what base? Take a look at this chart:
