Apple Flubbed the Vision Pro Launch

Overheard at ON_Discourse

Lost opportunity

The launch of the Vision Pro made me miss Steve Jobs

From the editor: The initial skepticism of the Vision Pro prompted many of our members to question Apple’s marketing strategy. Here is a collection of takes from a member at a recent virtual event who scrutinized the potential of this contentious product. We follow Chatham House rules, so we do not attribute perspectives without authorization.

Something struck me about the launch of the Apple Vision Pro. The whole process felt flat as if Apple was releasing a minor upgrade to an existing unit and not a revolutionary new piece of hardware. This was released more like the original Apple Watch, as if it were a fashion accessory that augmented the iPhone. It made me realize that this is the first major hardware release in the post-Jobs era. Does this explain the flat release? Is Apple any good at launching revolutionary products anymore? Does it matter?

Steve Jobs always marketed around clear and accessible customer use cases. When I saw “1000 songs in your pocket”, I immediately got the iPod (conceptually and commercially). The same can be said about the iPhone; this single device combined the iPod, phone, and mobile web. Additionally, the deliberately designed white phone contrasted mightily against the all-black devices that dominated the sector. Early adopters signaled their association with the Apple brand just by walking around. The little white brick made them look cool, which made other people want to buy one. The Vision Pro does not offer any of those benefits.

I’ve noticed that Apple has in-housed the marketing for the Vision Pro. This has resulted in unflattering 3D renders of the device with ineffective demonstrations of use cases. As a result, they haven’t made me want to buy one and I spend a lot of money on random shit I don’t need. 

The marketing was a flub, but this is still Apple and I fully expect future releases of the Vision Pro to go mainstream. Nevertheless, we are witnessing a fascinating new kind of computing experience get released without any imagination or spark. It’s disappointing and will result in a longer arc on the inevitable adoption curve.

XR will now forever be known as Spatial

This was no flub. Apple’s launch defined a new product category from scratch.

From the editor: We shared the critiques of Apple’s marketing with another member who has spent decades marketing with Apple. It turns out there are alternative ways to interpret Apple’s marketing strategy. We follow Chatham House rules, so we do not attribute perspectives without authorization.

Apple crushed the Vision Pro launch and I can prove it. The fact that we’re all using the word Spatial is the only evidence I need to prove that Apple is, once again, leading the conversation about new technology. No matter how big Apple gets and how premium its prices are, it will always be a challenger brand. In this case, Apple challenged and redefined the very nature of immersive video.

Apple deliberately avoided calling the Vision Pro an XR device, and as expected, the world followed. To call this device XR would follow the conventions set by the Meta Quest. Look at its marketing page: this device is built for video games. It is a toy. Apple had bigger intentions.

Apple positioned the Vision Pro around spatial experiences. This is a new concept that has yet to define a specific use case. Spatial tech can facilitate premium remote work experiences. It can catalyze exclusive new immersive video formats. It can also power a new kind of emotional content format: a sort of living memory. In its product launch, we saw Apple create an opportunity rather than box itself in as a video game player.

The idea that Apple hasn’t specified a use case is not the flaw you think it is; it is more of a flex. Apple has the resources, capital, and capability to launch this product and then figure it out. In your argument, you referred to the Apple Watch and how it was originally marketed as a fashion accessory. That is a fair point, but it is deliberately missing the coda. The initial product launch focused on fashion until health tech took over. Once that use case became clear to Apple, they marketed heavily around that. As a result, this Apple Watch is now the biggest-selling watch on the planet. To put it another way: Apple always figures it out.

In the end, Apple always wins.

Four Things Spatial Needs to Become Legitimate

Overheard at ON_Discourse

Free advice

The potential of spatial video is meaningless without scale

From the editor: Many of our members are excited by the Vision Pro. They are not deterred by the flawed form factor at all, and are instead focusing on the use-cases. One of our members recently laid out a roadmap for growth that has nothing to do with hardware fixes. This is a Chatham House recreation of a member’s perspective.

This post was written by a human and narrated by an AI-generated voice. (powered by Wondercraft.ai).

0:00 / 0:00

The Vision pro is ugly and expensive and buggy and it is going to make the internet way more interesting. The biggest challenge that this product faces is not the shitty keyboard experience or the weight on your face, nor is it the weird battery pack; it is the lack of scale. The Vision Pro needs scale to meet its destiny. Here are four steps that can catapult this product into the mainstream.

1

Subsidize Cost / Reinforce Use-Case

Find a partner that can subsidize the ridiculous retail price. Apple already gets credit for pioneering this strategy to make the iPhone more accessible to customers. The Vision Pro can partner with entertainment providers (Netflix?) or remote work platforms (Zoom?) to make it easier to access this device. The right partner not only reduces the price but it also reinforces the use-cases for this device. Netflix as a partner could pair this device with a new premium spatial video offering that includes exclusive access to this new content. Additionally, if Zoom were a partner, you can imagine remote work getting a significant boost.

2

Elevate Remote Work into a Premium Experience

Speaking of remote work: the Meta Quest made a half-hearted attempt to capture remote work demand but failed. It is inconceivable that professional employees would want to work in a cartoonishly designed metaverse. 


Meta’s failure leaves an untapped white-space in the world of remote work. Zoom interfaces and Slack channels have not noticeably improved since the pandemic. As a result we are seeing more companies try to force employees back into the office. Despite all of this, remote work is not going away. The Vision Pro has the opportunity to enable premium collaborative experiences by converting a pen on a desk into a virtual object that can legibly draw on a digital whiteboard. Eventually the economics of this experience are going to drive mass adoption. As AI continues to rapidly diminish headcounts and management structure, employers will start to consider how much money an office, a desk, a chair costs compared to this device.

3

Leverage Mass Cultural Phenomena

The Vision Pro is driving a new kind of AV format that is undeniably riveting. Spatial video is not just a screen on your face; it is an emotional experience. The original Vision Pro includes a spatial video of Alicia Keys in the studio and it is an absolutely mesmerizing experience. The viewer is no longer a viewer, but a participant in an intimate setting with the musician. You are next to her at the piano, feeling her presence as you are hearing her perform. Alicia Keys is a magnificent star, but imagine this experience at a higher scale. If Alicia Keys has the star power of the sun, Taylor Swift is a galaxy. Her Eras Tour film already broke records in conventional theaters. What will her fans do if they can experience her presence with a fully immersive and personal movie theater experience? What if this experience is offered to die-hard football fans or NBA fans? How much would they pay for premium access to courtside seats from their own couch?

4

Tap into the Allure of Adult Content

This point should not be taken as an endorsement of porn, just an acknowledgement of its power to persuade the population to upgrade their personal tech. The emotional, sensory experience of spatial video is going to be irresistible to many consumers with expendable income. The moments in between intimate viewing are going to drive these users to get more value out of their device than their late-night ribaldry.

For the Vision Pro, scale is not necessarily focused on revenue alone; it’s about culture. Scale converts our collective creativity into new ways to use technology to shape culture. The iPhone is an example of this: there are over 2 million apps in the app store, yet the average iPhone owner frequently uses only 9 apps. You need scale to test out and identify what those final 9 apps could be. The iPhone, after all, is the standard bearer for the modern mobile experience. The Vision Pro has the potential to define the same thing for XR.

This product is going to change the way people consume media which will influence the way media is created. We should all be excited about this future. I have seen what the first Vision Pro can do – bugs and all – and I am still so fucking excited.

Do you

see

what I
see?

Dan Gardner

Dan Gardner

Founder & Exec Chair of Code
and Theory & Founder,
ON_Discourse

Believe the hype

I can’t stop thinking about spatial video and neither should you.

From the editor: Our co-founder was having a creative anxiety attack after unboxing the Apple Vision Pro. It has been a long time since we’ve seen this digital tech executive so excited by new technology and wanted to give him a chance to explain his enthusiasm

This post was written by Dan Gardner and narrated by an AI-generated Dan Gardner. (powered by Wondercraft.ai).

0:00 / 0:00

I just got the Vision Pro and now I have seen the light. This product is not a fad. The goggles are ugly and expensive and it does not matter. Spatial computing is going to unlock new audiences for new behaviors and ultimately shape a new kind of internet. If you are an executive in digital media and are not excited by this product, then, please pardon my pun, you simply have no vision.

Let me explain myself: I was blown away by the experience of spatial video. It made me feel things. There is an ethereal quality when 3-D spatial video combines with spatial audio. For example, the Apple Vision Pro contains a spatial video with Alicia Keys in the studio that feels like you are next to her in that room. I need to reinforce this point: it’s not just being next to her; the experience feels like I am simultaneously forming and experiencing a new lifetime memory in real time. The jump cuts in the editing, so common in standard video formats, break the spell of the experience. For a moment, I was next to her at the piano, feeling like I am there, and suddenly now I am somewhere else because of that cut. My mind is literally vibrating with ideas about how this experience can unlock new opportunities for brands and end-users. Imagine Taylor Swift recording in spatial. Imagine a NBA or NFL game in spatial. Do you see what I see?

Do not underestimate the power of feelings. I don’t know that I’ve seen technology evoke a sensation as strongly as the Vision Pro.

Do not underestimate the power of feelings. I don’t know that I’ve seen technology evoke a sensation as strongly as the Vision Pro. It’s not just naturally visual, it’s naturally emotional. A simple spatial video of my kids left my wife in tears. The dimensionality of the experience resonated with her in a way that overcame her typical techno-skepticism. The implications of this technology cannot be overstated – imagine this technology powering the next generation of user-generated social media. Do you hear what I hear?

My enthusiasm comes in spite of the fact that the Apple Vision pro is the ugliest piece of hardware ever to come from Apple. That is saying something. It also acknowledges the insanely high price point that will restrict access to early adopters. This technology is only beginning.

We are at the precipice of an epic technological revolution. The power of AI, Web3, and spatial computing are coalescing and redefining the experiences that have defined the first generation internet. We are now entering into a new phase. And that is a gigantic white-space that is ready for new ideas, development, and investment.

"Sorry Dan, I disagree. All I see is a niche product.

This isn't as groundbreaking as it seems and I don't think it will scale."

Overheard at ON_Discourse

During a recent debate, one of our members made a strong counter-argument to against Dan’s fanboying enthusiasm. Given our observance of Chatham House Rules, their name has been redacted.

This post was written by a human and narrated by an AI-generated voice. (powered by Wondercraft.ai).

0:00 / 0:00

Here’s my thing. We’ve seen this movie before, right? The early adopters got the Google Glass in 2013. Modern users can get the Ray Ban glasses from Meta. Is the market penetration on either of these devices massive? No, and they are not even close to as expensive as the Vision Pro.

I’ve thought about these technologies and this hardware for a long time. I just don’t see a world where a ton of consumers are wearing these headsets and having meaningful experiences.

There are a lot of headwinds consumers face even if they want this. Price is the most obvious one. The second is access to experience. There are still limited options for a consumer to truly experience the amazing spatial video the Vision Pro offers. The third issue is more important: this is a fundamentally isolating and solo experience. People want to watch the big game together. They want to watch a movie together. This does not allow that. It erases community from the experience. No matter how cool the hardware is (and goggles aren’t cool and will never be cool), people want to be with other people.

Sorry but this isn’t it.

Different

Perspectives,

Together.

ON_Discourse is a private membership community for business leaders to participate in the Discipline of Discourse, cultivating perspectives, decision-making, and meaningful relationships.

Learn More

Issue #004

“Influencers are the modern athletes.”

“Fans are the new Free Agents.”

“Insurgent Sports Innovate.”

“Thrive To Survive”

Fans are the new free agents

ON_Sport dives into the last stronghold of the rapidly changing world of professional sports — the fan experience. Unlike other media verticals, the fan experience has been largely insulated against disruption; live sports have been one of the last bastions of linear broadcast media, a vast and mature market where regional relationships drive market activity and predictable consumer behaviors.

This stability is facing a triple threat of unstoppable disruption: the unbundling of ESPN, the rise of online gambling/fantasy, and the memification of highlights. These forces are resetting fan expectations for how they consume the game, what matters most to their experience, and where business opportunities lie in an uncertain future. 

The intergenerational transfer of fanatical devotion of a local team is going to fundamentally change in a new media and digital landscape, but the love of the game will remain. How will that love be witnessed, monetized, and mediated in an uncertain future?

Explore our initial questions and perspective

Discover More ON_Sport

The
secondary
market

issue #003

HAS OWNERSHIP

FALLEN OUT

OF FASHION?

Exploring the relationship
between fashion and
technology and the evolving

landscape that is the
secondary market.

The fashion industry has a strange relationship with technology.

Why does the Fashion Industry treat tech like a seasonal trend?

The secondary market is creeping up on the luxury market.

How might AI-driven entertainment redefine our relationship with anticipatory content?

AI Forecasting in Fashion has a Big Sustainability Problem.

AI forecasting is a noisy guess masquerading as an objective analysis — and manufacturers know it.

Discover More ON_Fashion

On_Entertainment

ISSUE #002

GOOD
ARTISTS
COPY,
GREAT
AIs
STEAL

Issue #002 examined how creativity, ownership, and distribution are
being impacted by the growth and mass adoption of AI and its impact
on the business of entertainment.

DO CREATIVES
KNOW WHAT CREATIVITY IS?

Our event set the stage for a lively, engaging debate over a private dinner and drinks in the Hamptons with ON_Members and specially invited guests in the entertainment, media, and tech industries.

We Are Algorithim-ing Ourselves Into a Monoculture

Content has become mundane and unexceptional as a result of personalized recommendations.

The Copyright Fight for Digital Creativity

The US copyright regime has become an obstacle to this new era of innovation–and not because of what the law actually says.

Would you let Netflix read your mind?

How might AI-driven entertainment redefine our relationship with anticipatory content?

How Artists Turn AI Into Gold

AI has the potential to be an industry-disrupting tool for streamlining creative processes and getting projects out the door faster than ever previously possible.

Discover More ON_Entertainment

AI

is

not

a

new

revolution

Food for thought

It is tempting to think of AI as novel technology that emerged very recently

Overheard at ON_Discourse

From the editor: One of our most credentialed AI experts shared some essential perspectives for companies betting on AI. This speaker has a PhD in Brain and Cognitive Sciences, and has been working on machine learning models for over 15 years. As always, ON_Discourse operates under the Chatham House Rule—no attribution of perspectives without explicit consent.

AI is not magical. It is not new. And the recent surge in attention is not the result of an unexpected advancement in generative software.

The dominant media story about AI is that OpenAI achieved a major technological breakthrough sometime in 2022. This breakthrough unlocked new ways consumers can prompt with models to receive shockingly relevant generative output. In other words, before 2022, the generative systems were still largely theoretical. Nope.

The ability to prompt with generative models has been around for more than a decade. Prior to 2022, researchers in cognitive and brain sciences (not computer science, by the way) were interacting with models as seen on ChatGPT. They did not call this functionality artificial intelligence – it had always been called machine learning, a more accurate representation of the underlying tech.

So what happened? If the software didn’t change, why are we treating AI as a groundbreaking technological revolution? The short answers are that the hardware (the GPU chips) got faster and OpenAI put it all online. In other words: the hardware got faster and the UI made it accessible. 

Everything else that happened is hype.

AI researchers are constantly building models, trying something new, and incrementing the version number. Nevertheless, we have to put things into perspective before the hype takes over. This is the reality: no AI model can suddenly build a rocket from scratch or do anything it couldn’t do before. The headlines brag about it getting a 95 on one benchmark, and ignore the fact that the previous model got a 92. It is all a progression.

The headlines brag about it getting a 95 on one benchmark, and ignore the fact that the previous model got a 92.

The technology is undeniably amazing but the amount of hype around their improvements hasn’t been proportional. The only major innovation is how they made their AI models available to the masses. The technology that’s under the hood remains the same.
  
Companies looking to innovate shouldn’t bother with generative AI models. Innovation in areas like quantum computing, neuromorphic computing, and low-temperature semiconductors is much more likely to bring about the next wave of AI than hiring a bunch of Stanford Computer Science PhDs.

This article is part of The Intelligently Artificial Issue, which combines two big stories in consumer tech: AI and CES.

Read more from the issue:

USER EXPERIENCE

Augmented Intelligence: from UX to HX

Will prompting replace browsing?

The car is the gateway drug to a voice-first acceleration

The prompt interface needs a redesign

RE-ORG

AI will brainstorm your next reorg

Expect fewer managers and direct-reports

AI is too immature for your business

AI is not a new revolution

BRAND

Should we ignore the hardware?

Can AI help consumers love your brand?

Your brand doesn't have enough data for AI

Can LLMs be optimized like search results?

Good brands will integrate more friction into their CX

Overheard at ON_Discourse
search icon

Can LLMs be optimized like search results?

From the editor: Marketers are starting to test different LLMs with branded prompts, reminding us of the early days of SEO. We convened two experts in brands and AI to sort through their conflicting perspectives on this analogy. As always, ON_Discourse operates under the Chatham House rule—no attribution of perspectives without explicit consent.

search icon

Can LLMs be optimized like search results?

From the editor: Marketers are starting to test different LLMs with branded prompts, reminding us of the early days of SEO. We convened two experts in brands and AI to sort through their conflicting perspectives on this analogy. As always, ON_Discourse operates under the Chatham House rule—no attribution of perspectives without explicit consent.

search icon

Can LLMs be optimized like search results?

From the editor: Marketers are starting to test different LLMs with branded prompts, reminding us of the early days of SEO. We convened two experts in brands and AI to sort through their conflicting perspectives on this analogy. As always, ON_Discourse operates under the Chatham House rule—no attribution of perspectives without explicit consent.

Kind of, yes

Kind of, yes

Sometimes, language models act like certain brands always lead in their industries.

“One of the things that people ask me a bunch is whether there are specific ways they should be thinking about optimizing what they do as marketers so that the LLMs have a better sense of their brand or they become the default brand when the LLM or diffusion model imagines a car or a beer … And my answer is that I don’t think it’s anything fundamentally different.

I think basically what you do when you’re doing brand building—building distinct brand assets over time—is probably the best thing that you can do to build up the LLMs’ understanding of the brand."

Sometimes, language models act like certain brands always lead in their industries.

“One of the things that people ask me a bunch is whether there are specific ways they should be thinking about optimizing what they do as marketers so that the LLMs have a better sense of their brand or they become the default brand when the LLM or diffusion model imagines a car or a beer … And my answer is that I don’t think it’s anything fundamentally different.

I think basically what you do when you’re doing brand building—building distinct brand assets over time—is probably the best thing that you can do to build up the LLMs’ understanding of the brand."

No
way

No
way

But...

We should not be confusing LLM and SEO. They are different topics and functions.

“I think if you are trying to make your brand what an LLM responds with when asked for a default beer, then you’re fundamentally misunderstanding what this technology is, and how to leverage it – it’s likely your reference point is 'how do I get the top result in search'.”

Firstly, the LLM is not imagining a car or beer can like we might. It’s developing something based on the prompt that is entered by a user. This matters a lot. It’s then going to modify that depending on what extra knowledge it receives in further commands.

But...

We should not be confusing LLM and SEO. They are different topics and functions.

“I think if you are trying to make your brand what an LLM responds with when asked for a default beer, then you’re fundamentally misunderstanding what this technology is, and how to leverage it – it’s likely your reference point is 'how do I get the top result in search'.”

Firstly, the LLM is not imagining a car or beer can like we might. It’s developing something based on the prompt that is entered by a user. This matters a lot. It’s then going to modify that depending on what extra knowledge it receives in further commands.

Yeah, but…

Sustained marketing strategy can determine what the LLM does and that is important.

“I mostly agree, but on the flip side, there are some brands for whom this is true (they’re the default brand that the LLM 'thinks' of), and the real point is that those brands that have achieved that status did so through many years of good marketing and branding practices. These are the same brands we think of when we think of sneakers and soda: the LLM is just reflecting back this perceptual reality."

Yeah, but…

Sustained marketing strategy can determine what the LLM does and that is important.

“I mostly agree, but on the flip side, there are some brands for whom this is true (they’re the default brand that the LLM 'thinks' of), and the real point is that those brands that have achieved that status did so through many years of good marketing and branding practices. These are the same brands we think of when we think of sneakers and soda: the LLM is just reflecting back this perceptual reality."

I still don’t agree…

This is not the time to be thinking about what an LLM outputs. There are higher priority issues for marketers.

Honestly, this kind of thing should not even be on the radar of a marketer right now – they should be focused on understanding how LLMs can be used as reasoning engines, how knowledge can be leveraged and stacked, how their workflows and lives can be made easier, and marketing made more effective.”

A brand shouldn’t be worrying about being the car that the LLM 'imagines' because it’s essentially creating a mishmash of a combination of everything it has learned about what a car is when it returns the output. It’s the detailed input that goes into prompts that creates the direction – e.g. futuristic car, Ford car, etc. If a brand wants to be mentioned by an LLM, then it needs to be worried about what is inputted to drive the output.

I still don’t agree…

This is not the time to be thinking about what an LLM outputs. There are higher priority issues for marketers.

Honestly, this kind of thing should not even be on the radar of a marketer right now – they should be focused on understanding how LLMs can be used as reasoning engines, how knowledge can be leveraged and stacked, how their workflows and lives can be made easier, and marketing made more effective.”

A brand shouldn’t be worrying about being the car that the LLM 'imagines' because it’s essentially creating a mishmash of a combination of everything it has learned about what a car is when it returns the output. It’s the detailed input that goes into prompts that creates the direction – e.g. futuristic car, Ford car, etc. If a brand wants to be mentioned by an LLM, then it needs to be worried about what is inputted to drive the output.

So in conclusion...

Google has profited immensely from the marketing world’s obsession with its black-box search algorithm. This obsession unlocked a deeper technical understanding of how online search works so brands can carve out opportunities to differentiate. It is therefore logical that markers begin to explore how LLMs respond to prompts. There is an undeniable symmetry in these two technical processes.

One of the interesting takeaways from this discussion is the inherent strength legacy brands will have in this upcoming AI era. They already possess the collateral that initially fed the data set behind the model. It makes us wonder how new brands should think about this upcoming era. Is there anything they can do?

This article is part of The Intelligently Artificial Issue, which combines two big stories in consumer tech: AI and CES.

Read more from the issue:

USER EXPERIENCE

Augmented Intelligence: from UX to HX

Will prompting replace browsing?

The car is the gateway drug to a voice-first acceleration

The prompt interface needs a redesign

RE-ORG

AI will brainstorm your next reorg

Expect fewer managers and direct-reports

AI is too immature for your business

AI is not a new revolution

BRAND

Should we ignore the hardware?

Can AI help consumers love your brand?

Your brand doesn't have enough data for AI

Can LLMs be optimized like search results?

Good brands will integrate more friction into their CX

Good brands

will integrate

more friction

into their CX

Hear me out

Let’s get a little inefficient

in the AI era

Dan Gardner

Dan Gardner

Co-Founder & Exec
Chair of Code and Theory
Co-Founder,
ON_Discourse

This article is part of The Intelligently Artificial Issue, which combines two big stories in consumer tech: AI and CES.

Read more from the issue:

USER EXPERIENCE

Augmented Intelligence: from UX to HX

Will prompting replace browsing?

The car is the gateway drug to a voice-first acceleration

The prompt interface needs a redesign

RE-ORG

AI will brainstorm your next reorg

Expect fewer managers and direct-reports

AI is too immature for your business

AI is not a new revolution

BRAND

Should we ignore the hardware?

Can AI help consumers love your brand?

Your brand doesn't have enough data for AI

Can LLMs be optimized like search results?

Good brands will integrate more friction into their CX

From the editor: Our co-founder spent the past 20 years designing to remove friction, only to see how AI stands to push it too far. Do you think he has a point?

Technology, if you really think about it, is an evolution of removing friction from everything that we do. Successful brands offer their customers value and build their staying power by leveraging technology to remove friction.

AI is just another piece of technology with the potential to remove even more friction. Taken to an extreme, it’s easy to imagine the perfect AI-driven experience: no friction. Whatever you want or need is available exactly when you want or need it. A perfectly frictionless experience.

Friction points let customers
recalibrate ahead and realign
with the brand in a more direct
and human way.

Think about the Humane Ai Pin launch video. There is a moment when a book is offered in front of the Pin with a directive to buy it. Which store? At what price? Is there a membership plan associated with the retailer? The assumption in that video is that the consumer is in some kind of a rush to buy.

We’re not there yet, but we’re getting close. 

When you’ve removed all friction, there’s no moment left for decision making. Brands could no longer need, or even allow the customer to make decisions anymore.

If we were to reach such a point, brands would need to learn where and when to add friction back in. In a world of no friction, the trend of removing friction would have to reverse. This is where good brands will distinguish themselves.

Good brands will define ideal friction points for their customers. Friction points let customers recalibrate ahead and realign with the brand in a more direct and human way.

AI is too

immature

for your
business

From the editor: One of our most credentialed AI experts shared some essential perspectives for companies betting on AI. This speaker has a PhD in Brain and Cognitive Sciences, and has been working on machine learning models for over 15 years. As always, ON_Discourse operates under the Chatham House Rule—no attribution of perspectives without explicit consent.

AI is an

adolescent

This tech revolution is built on bad behavior.

AI behaves like a teenager. It is moody, unreliable, and unpredictable. It needs constant supervision.

Are you sure you want this kind of technology driving business decisions?

Without any guardrails in place, AI models trained on text scraped from the internet swear at you, call you names, go off on sexist and racist rants, and so on. These are very teenager things to do: saying something just to say something, without realizing what it actually means, how bad it is, or what the repercussions in society might be.

Companies form so-called red teams to perform adversarial testing on their AI systems. These tests try to make an AI model do all the worst stuff possible, so that the companies can then prevent it from doing that stuff when it’s talking to their users.

Many people don’t realize that a lot of the work around AI currently involves babysitting models so that the end user doesn’t realize that the tech needs to be babysat. In short, companies are hiding how incredibly immature AI still is.

Keep this in mind before, during, and after you deploy any sort of AI tech across your organization.

This article is part of The Intelligently Artificial Issue, which combines two big stories in consumer tech: AI and CES.

Read more from the issue:

USER EXPERIENCE

Augmented Intelligence: from UX to HX

Will prompting replace browsing?

The car is the gateway drug to a voice-first acceleration

The prompt interface needs a redesign

RE-ORG

AI will brainstorm your next reorg

Expect fewer managers and direct-reports

AI is too immature for your business

AI is not a new revolution

BRAND

Should we ignore the hardware?

Can AI help consumers love your brand?

Your brand doesn't have enough data for AI

Can LLMs be optimized like search results?

Good brands will integrate more friction into their CX

Expect

fewer

managers

and

‏‏‎ ‎direct‏‏‎
‏‏ reports‏‏‎ ‎‎

From the editor: This overheard passage comes from a virtual event that featured a productive disagreement between members. In this piece you’ll see two opposing perspectives about the well-worn assumption that AI will replace labor. As always, ON_Discourse operates under the Chatham House rule—no attribution of perspectives without explicit consent.

‏‏‎ ‎Yes,‏‏‎ and here's why

AI could accelerate the flattening of organizations

MBA programs didn’t prepare anyone for this. The accelerating adoption of AI tools could completely redefine how businesses organize. The first dominos to fall will be the HR and management layers. At first glance this seems like a bad thing, but it’s not…

Growing
without
headcount

Today’s model is fundamentally stupid—I don’t mean that pejoratively. Managers are incentivized to grow their teams regardless of need. Why? Having more direct reports leads to more promotions and more raises for managers. This sustains a conventional growth model that leads to overhiring and layoffs.

AI tools will disrupt the need for companies to grow their workforces by injecting intelligence and data into this dumb growth model. The knee-jerk reaction to such a shift typically sounds like, “If we don’t grow our teams, how are we ever going to get promoted and have a career path?”

This thinking is rooted in the assumption that a hierarchy and a climbing mentality are required for growth. AI tools will reveal that this is not the case, and adding people will not be seen as a requirement for revenue growth.

Instead, revenue growth could be achieved while keeping headcount flat, or even through reductions. Many non-revenue-generating roles, like in HR and middle management, will start to disappear. Active executors that have a more direct relationship with the bottom line of the organization will replace them.

Focusing
on what
matters

People managers who remain will have more time to focus on their hands-on efforts. These individuals were good enough at doing something to get promoted. Their employers will develop metrics and goals around those skills, unlocking an entrepreneurial spirit.

Instead of adding more people to manage, people managers will become more focused on outcomes. AI tools could help incentivize individual contributors based on what uniquely motivates them and the impact they can make.

On the HR side, plenty of functions could be handled by AI, possibly with less bias, more clarity, and more transparency. The processes could be opened up and deployed more equally across teams.

More layers and hierarchy only distract from revenue-generating functions and complicate decision-making.

Better
outcomes

This has important knock-on effects. Non-revenue-generating roles pull businesses further away from their customers and the outcomes they want. More layers and hierarchy only distract from revenue-generating functions and complicate decision-making, whereas fewer non-essential roles could mean more focus on translating user needs to products and services.

Some argue that AI can just help bring all the data needed for decisions to the top of the organization, but that’s backward. Why bother having such a structure? Instead, flatten your organization and empower more people to make decisions closer to the customer.

AI tools will disrupt the need for companies to grow their workforces by injecting intelligence and data into this dumb growth model. The knee-jerk reaction to such a shift typically sounds like, “If we don’t grow our teams, how are we ever going to get promoted and have a career path?”

This article is part of The Intelligently Artificial Issue, which combines two big stories in consumer tech: AI and CES.

Read more from the issue:

USER EXPERIENCE

Augmented Intelligence: from UX to HX

Will prompting replace browsing?

The car is the gateway drug to a voice-first acceleration

The prompt interface needs a redesign

RE-ORG

AI will brainstorm your next reorg

Expect fewer managers and direct-reports

AI is too immature for your business

AI is not a new revolution

BRAND

Should we ignore the hardware?

Can AI help consumers love your brand?

Your brand doesn't have enough data for AI

Can LLMs be optimized like search results?

Good brands will integrate more friction into their CX

I totally ‏‏‎ ‎disagree‏‏‎

AI will need many more managers

I agree with
you on two
important
points

I agree with you on
two important points

  1. No conventional MBA graduates in management are prepared for the AI era.
  2. The proliferation of AI products and services will change management structures.

The rest, you have backwards. The number of managers is going to grow significantly in the near future. We are going to need more people to manage the adolescent that is AI.

Adding AI products and services to the toolbox creates a new output signal that businesses need to wrangle. This in turn calls for another human layer to figure out how the AI tools are performing and how they are changing the way we ingest new information.

We are going to need more people to manage the adolescent that is AI.

AI tools could create
a lot more noise
for decision makers

Because we have more signals coming in, we will ultimately make better decisions. Those additional signals, however, require more data science teams, more linguists, more operational people, more people managing how the models are performing, more people monitoring any human bias that is going into those models, and so on.

Industry expertise will remain vital. Companies will demand subject matter experts who decipher the truth within AI-generated content.

There are limitations to what AI can produce. Only humans can figure out that last critical bit. Non-technical roles, filled by creative and culturally-aware individuals who bridge technical jargon and diverse global perspectives, will grow in importance.

In fact, we might see high demand for managers who can attract the right mix of these unique, multidisciplinary groups of people, and know how to get them to work together productively and efficiently. AI simply doesn’t have the people skills to manage divergent perspectives and disciplines into a cohesive group.

More technology will once again require more humans to manage it.

Your brand does
not have enough
data for AI

This article is part of The Intelligently Artificial Issue, which combines two big stories in consumer tech: AI and CES.

Read more from the issue:

USER EXPERIENCE

Augmented Intelligence: from UX to HX

Will prompting replace browsing?

The car is the gateway drug to a voice-first acceleration

The prompt interface needs a redesign

RE-ORG

AI will brainstorm your next reorg

Expect fewer managers and direct-reports

AI is too immature for your business

AI is not a new revolution

BRAND

Should we ignore the hardware?

Can AI help consumers love your brand?

Your brand doesn't have enough data for AI

Can LLMs be optimized like search results?

Good brands will integrate more friction into their CX

From the editor: One of our most credentialed AI experts shared some essential perspectives for companies betting on AI. This speaker has a PhD in Brain and Cognitive Sciences, and has been working on machine learning models for over 15 years. As always, ON_Discourse operates under the Chatham House Rule—no attribution of perspectives without explicit consent.

You need an
enormous amount

This is one of the AI era’s most
under-appreciated assumptions.

In the AI era, everyone seems to have convinced themselves that their company has the best data. You likely believe that not only is your data just the best, but it also happens to be just so unique that the resulting AI model is going to supercharge your whole business.

This is wrong, for two reasons:

  1. You have too little data. You need billions or even trillions of heterogeneous observations to be able to do anything interesting with AI. There are only a handful of companies today that possess that quantity.
  2. Your data is of poor quality. Even most large enterprises do not have a dataset rich enough to make a meaningful AI play. They rely on buying data from multiple sources or stealing it from internet users under the guise of fair use.

Many companies are opting for a shortcut into AI. Any company today can implement base GPT models. That works for experimentation, but it won’t drive revenue or improve efficiency. Why? AI is not trustworthy. You need to hire experienced teams to manage its bad behaviors.

For almost every single company, trying to build something bespoke that will move the needle is simply not worth the investment.

Your brand does
not have enough
data for AI

This article is part of The Intelligently Artificial Issue, which combines two big stories in consumer tech: AI and CES.

Read more from the issue:

USER EXPERIENCE

Augmented Intelligence: from UX to HX

Will prompting replace browsing?

The car is the gateway drug to a voice-first acceleration

The prompt interface needs a redesign

RE-ORG

AI will brainstorm your next reorg

Expect fewer managers and direct-reports

AI is too immature for your business

AI is not a new revolution

BRAND

Should we ignore the hardware?

Can AI help consumers love your brand?

Your brand doesn't have enough data for AI

Can LLMs be optimized like search results?

Good brands will integrate more friction into their CX

From the editor: One of our most credentialed AI experts shared some essential perspectives for companies betting on AI. This speaker has a PhD in Brain and Cognitive Sciences, and has been working on machine learning models for over 15 years. As always, ON_Discourse operates under the Chatham House Rule—no attribution of perspectives without explicit consent.

You need an
enormous amount

This is one of the AI era’s most
under-appreciated assumptions.

In the AI era, everyone seems to have convinced themselves that their company has the best data. You likely believe that not only is your data just the best, but it also happens to be just so unique that the resulting AI model is going to supercharge your whole business.

This is wrong, for two reasons:

  1. You have too little data. You need billions or even trillions of heterogeneous observations to be able to do anything interesting with AI. There are only a handful of companies today that possess that quantity.
  2. Your data is of poor quality. Even most large enterprises do not have a dataset rich enough to make a meaningful AI play. They rely on buying data from multiple sources or stealing it from internet users under the guise of fair use.

Many companies are opting for a shortcut into AI. Any company today can implement base GPT models. That works for experimentation, but it won’t drive revenue or improve efficiency. Why? AI is not trustworthy. You need to hire experienced teams to manage its bad behaviors.

For almost every single company, trying to build something bespoke that will move the needle is simply not worth the investment.