How to Sell AI in the Kingdom of the Bored
Urban light is now so cheap and so abundant that many consider it to be a pollutant. The same could be said about AI.
Silicon Valley investors remain optimistic that artificial intelligence can deliver trillions of dollars in business value, even as they agree that the technology has continued to feed a now years-long hype cycle.
“We are definitely in a hype cycle, especially for generative AI,” said Konstantine Buhler, a partner at Sequoia Capital, speaking on a panel at The Wall Street Journal’s CIO Network Summit on Monday.
The questions remain: Will AI’s hype cycle turn into meaningful value for enterprises, and if so, when? In the timeline for generative AI’s value to be fully realized, “We are not even in the beginning,” Buhler said.
— Is AI Revolutionary or Hype? What If It Is Both?, Wall Street Journal, February 11
The Census Bureau finds that less than 4 percent of American businesses use AI and less than 7 percent have plans to adopt it in the near future. Many others find the tech either difficult to use or irrelevant to their line of business.
Some markets have lower levels of AI adoption than others.
For example, less than 2 percent of businesses in the "Accommodation and Food Services" industry use AI. On the other hand, and this should come as no surprise, the tech services industry is all in, betting the farm on the transformative potential of technology to transform humanity through the potential of digital transformation.
The Sound of One Hand Clapping
For technology companies that can either integrate generative AI into their products and services or offer stand-alone AI products, the trajectory seems simple. “Because we all sell software with AI in it, by definition [AI] is driving revenue,” said Aaron Levie, chief executive of cloud company Box.
Generating returns from new technology investments is a high-pressure task for chief information officers — in addition to dealing with everything else that comes with the technology.
More often than not, it's easy to get distracted by all the humanity-saving potential.
“With CIOs dealing with interoperability, data privacy, vendor management, vendor relationships, security, risk, legacy versus new, AI-native versus non-AI native, there are infinite complexities in decision-making,” said Tali Bray, investor and adviser for software developer Graphio.AI, an attendee at the Wall Street Journal summit on Monday. [These CIO problems are, I would suggest, relatively small, technical problems that can be simply solved through procurement innovation.]
Writing on a century of American innovation and technological enthusiasm, Thomas P. Hughes (American Genesis: A Century of Invention and Technological Enthusiasm) described real invention as the process of weaving scientific and technological advancement into a larger frame. It’s more sociological than technical. Radical success happens at a different level, from sparking or striking breakthroughs in nascent economic systems, rather than from the incremental improvements in well-established technological ones.
“In general, today’s accounts of the information revolution focus upon artifacts, such as computers and the Internet. This approach is myopic. We should broaden our concept of the information revolution. The other industrial revolutions involved far more than hardware. Besides technical artifacts, these earlier revolutions involved political, economic, social, organizational and cultural changes….”
If not completely irrelevant, the word "digital" is incidental as a bullet in the PowerPoint.
"Disruption" as a war cry hasn't delivered economic growth at scale. The mind-numbing flow of headlines from the media on what technology "can" do have all failed to spark the kind of systemic change in direction needed to sweep aside the status quo. The thing this moment needs is a different framework.
And while "deleting entire agencies" may not be the right approach, if you understand feedback loops and how systems work, you'll know why Chopping the Knot will get you running different faster than trying to "fix" an embedded economic system. [The Wall Street Journal this morning has an insightful read on the Trump Method to dealing with complexity: "Trump Writes a New Playbook for Quagmires in Gaza and Ukraine: President’s blueprints for the world’s intractable problems represent rejections of decades-old U.S. policy."]
Boldly Going Where Everyone Has Gone Before
Says pretty much every tech vendor selling the bull case on technology:
“As we look ahead in 2025, the shift toward cloud adoption by healthcare payers is becoming increasingly crucial. Although this transition requires substantial investment, it is essential for enabling seamless interoperability between providers and payers. Cloud adoption allows providers to make real-time, data-driven decisions, which payers can easily access to inform their care and claims decisions. If payers don’t invest in cloud adoption, they risk losing their competitive edge, as members and providers continue to demand better engagement experiences.
It is an exciting time to be part of the ongoing evolution of healthcare IT, and I look forward to supporting payers and providers as they boldly embark on their cloud transformation journeys.”
Here's what that story looks like strategically, which is to say competitively:
How to Position Different Strategy Stories
The shape and texture of transformational visions come from discovering new language — different strategy stories — to frame and sell (and implement) roadmaps that work horizontally across enterprise, market, industry, state and even national boundaries.
It can be exciting to be part of all the excitement. But technology isn’t strategy. Healthcare isn’t technology. And strategic problems don’t have technical solutions.
We're positioning the new operating model ahead of the new thinking model.
Let’s Save Humanity. Yay.
Abundance breeds boredom.
At a summit in Paris this month, big tech visionaries vied to issue the most grandiose claims about the humanity-saving potential of AI. “AI will be the most profound shift in our lifetimes,” is how Sundar Pichai, Google chief executive, put it. Dario Amodei, chief executive of Anthropic, said AI will lead to the “largest change to the global labor market in human history.” Sam Altman, not to be outdone, wrote in a blog post that "The economic growth in front of us looks astonishing, and we can now imagine a world where we cure all diseases, have much more time to enjoy with our families, and can fully realize our creative potential.”
When there’s no end of choices, each choice feels disappointing. Listening to or watching one thing means you’re not listening to or watching all the other things you might be listening to or watching, writes Nicholas Carr in a recent Substack. He quotes a telling line from Karla Starr’s 2008 article “When Every Song Ever Recorded Fits on Your MP3 Player, Will You Listen to Any of Them?” Confessed Starr: “I find myself getting bored even in the middle of songs simply because I can.”
And so, bored by the content, bored by the art, bored by the experience, we become obsessed with the interface. We seek to master the mechanism’s intricate, fascinating functions: downloading and uploading, archiving and cataloging, monitoring readouts and notifications, watching time counts, streaming and pausing and skipping, clicking buttons marked with hearts or uplifted thumbs. We become culture’s technicians. We become bureaucrats of experience.
It’s as though we find ourselves, suddenly, in a vast library, an infinite library, a library of Borgesian proportions, and we discover that what’s of most interest to us is not the books on the shelves but the intricacies of the Dewey Decimal System.
The poet Kenneth Goldsmith, in a Los Angeles Review of Books essay, writes of the day when he felt an urge to listen to some music by the American composer Morton Feldman:
I dug into my MP3 drive, found my Feldman folder and opened it up. Amongst the various folders in the directory was one labeled “The Complete Works of Morton Feldman.” I was surprised to see it there; I didn’t remember downloading it. Curious, I looked at its date — 2009 — and realized that I must’ve grabbed it during the heyday of MP3 sharity blogs. I opened it to find 79 albums as zipped files. I unzipped three of them, listened to part of one, and closed the folder. I haven’t opened it since.
The pleasure of listening to music was not as great as he anticipated. He found more pleasure in manipulating music files.
“Engaging with media in a traditional sense is often the last thing we do,” he observes, an insight with big implications for the wounded and limping market in digital transformation. “In the digital ecosystem, the apparatuses surrounding the artifact are more engaging than the artifact itself.” It was once assumed that digitization would liberate cultural artifacts from their physical containers. We’d be able to enjoy the wine without the bottles. What’s actually happened is different. We’ve come, as Goldsmith says, “to prefer the bottles to the wine.”
The Jevons paradox — the idea that efficiency leads to more use of a resource, not less — has in recent days provided comfort to Silicon Valley titans worked about the impact of DeepSeek, reports The Economist this morning (Tech Tycoons Have Got the Economics of AI Wrong). “Microsoft CEO Satya Nadella posted on X that “Jevons paradox strikes again! As AI gets more efficient and accessible, we will see its use skyrocket, turning it into a commodity we just can’t get enough off.”
Sort of like electricity.
Which, I think, only underscores the point I was making in Houston, We Need a New Narrative:
When everyone has access to the same amazing technologies, and everyone deploys the same amazing technologies the same amazing way, you get a sea of sameness at an amazing scale.
Technology breeds competitive convergence, not strategic differentiation.
The shape and texture of transformational visions come from discovering new language — different strategy stories — to frame and sell (and implement) roadmaps that work horizontally across enterprise, market, industry, state and even national boundaries. This is what an ecosystem-centered market strategy is really all about: building ‘lateral strength’ as a management innovation, developing the storytelling skills to align value that a set of markets can share.
Can AI Make Money for Business?
Corporate technology leaders across industries have been spending big on generative artificial intelligence over the past year, reported the Journal this past summer. Now, they’re looking for returns to go beyond efficiency gains to actual dollars and cents, even as many admit it isn’t clear if and when they’ll start seeing them.
CIOs have extolled AI’s efficiency savings, such as big boosts in productivity for software developers that use an AI coding tool. But as companies increasingly move from pilot to production with the pricey technology, they’re putting a bigger and bigger spotlight on where it will have a financial impact.
For technology companies that can either integrate generative AI into their products and services or offer stand-alone AI products, the trajectory is simpler. “Because we all sell software with AI in it, by definition [AI] is driving revenue,” said Aaron Levie, chief executive of cloud company Box.
It's the sound of one-hand clapping. Which helps explain the Census Bureau data.
New rule for technology sales teams:
When it comes to pitching the strategic value of technology, you’ll sell more technology by not talking about technology.
/ jgs
John G. Singer is Executive Director of Blue Spoon, the global leader in positioning strategy at a system level. To engage: john@bluespoonconsulting.com