Will

prompting

replace

browsing?

From the editor: The AI era has ushered in a new way of content interaction: prompting. This article explores two views on what will happen to another interaction model: browsing.

Anthony DeRosa
Head of Content and Product, ON_Discourse

No, it won't.

Generative AI is transforming content consumption, starting with just a prompt. This shift begs a critical question: Are we overestimating the desire to engage with content through AI prompts, and underestimating the timeless value of traditional browsing?

The enduring appeal of browsing


Browsing—the act of casually exploring content without a specific goal—has been an intrinsic part of human behavior long before the digital era. It caters to our innate curiosity and desire for serendipitous discovery. In contrast to AI-prompted interactions, where responses are generated based on specific user inputs, browsing allows users to stumble upon unexpected content, leading to new ideas and inspirations.

I spoke to Tyler Chance, a VP of Product at Hearst, who questions whether a prompt-first interface can lead to a better user experience.

“I don’t know what replaces the browse. If the entire Netflix homepage were to go away and just be an input prompt… because now, I’ve watched everything that I know I want. How do I get to the things that I don’t know I want?”

It is about the dopamine, the slow dopamine drip of a browse."

people browse in a mall set within a smart phone

The prompt paradigm

AI technologies have introduced a new way of interacting with content. AI systems like chatbots and recommendation engines provide users with content based on direct prompts or past behavior. This approach, while efficient, is rooted in the assumption that users always have a clear intent or preference when engaging with content, which is not always the case.

We must consider the balance between intent-based consumption and discovery through browsing. While AI excels in delivering content tailored to specific queries, it may not always capture the joy of spontaneous discovery that browsing offers. 

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

User preferences: new or familiar?

Do people currently spend more time seeking specific information or exploring content without a predetermined goal? This question extends to user interface preferences. Do people genuinely seek a new way of interacting with content, or is there comfort and satisfaction in traditional methods? While some may argue that current content consumption methods are outdated and inefficient, others find value in the familiar experience of browsing, suggesting resistance to completely adopting prompt-based interfaces.

Chance believes that it would be hard to break away from how attractive, addictive, and spontaneous the browsing experience is, as opposed to one where you’re expected to know the right way to prompt or always have a specific intent.

“Just think about the notion of UX over the last like, 10 years," Chance said. “It is about the dopamine, the slow dopamine drip of a browse. That is what the social feed is. That is what you know. That’s where we start. We start and then we hone and that is going to be a really hard nut to crack because it is the place to go when you have zero intent and you want to craft an intent.” 

The argument for AI-driven content discovery is flawed. The assumption that users always have a clear intent is overstated, while browsing without a specific goal can lead to discovering content that one might not have known existed. Additionally, AI systems, while advanced, don’t understand the nuances of human curiosity and the desire for serendipity.

Emil Protalinski
Managing Editor, ON_Discourse

Yes, it will (sorta).

Something was bothering me, and I couldn’t figure out what the query should be. All I could remember was that “an investor at some point in time spotted a trend wherein the first few days of January set the tone for the rest of the year.” This was not enough for a Google search, or at least not enough to avoid a lot of furious and frustrated clicking.
 
I turned to Perplexity AI. The chatbot’s quick responses, inaccurate or not, led me to remember the phrase “investor’s almanac,” which pointed me to the Stock Trader’s Almanac. Perplexity then informed me about “the first five trading days of January” and the “January Barometer.” I then confidently turned to Google, where I satisfied my knowledge gap by browsing and reading a variety of high-quality articles.

This anecdote cemented two realizations for me:
1. Prompting is not a temporary phenomenon.
2. Browsing is not going away.

In a world of just prompting, I would have been stuck wondering what responses were accurate and which were hallucinated. In a world of just searching, I would have spent too long trying to figure out the right query, if I had had the energy to search at all.

Sometimes, humans want to quickly prompt. Other times, we just want to browse.

Hey Siri,

You suck.

Love,

cars

Emil Protalinski
Managing Editor, ON_Discourse

From the editor: Voice tech on smartphones and smart speakers failed to hook users. LLMs could make the car the gateway drug into a voice-first world.

OpenAI released ChatGPT to the world in November 2022, and exactly a year later, in November 2023, rolled out ChatGPT with voice to all its free users. The rollout is part of a long list of voice-based tech launches that overpromise but underdeliver. We’re edging closer to a future where voice can be used as the primary input in increasingly more scenarios (beyond “Google, what’s the temperature outside?” or “Alexa, set a timer for 30 seconds”), but we’re still a long way from a voice-first world.

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

The car is the gateway drug to voice-first tech

Since at least March 2023, General Motors, which manufactures Chevrolet, Cadillac, Buick, and GMC cars and trucks, has reportedly been working on a Microsoft Azure-hosted virtual assistant that leverages the AI models behind ChatGPT. Such an AI assistant could go beyond the simple voice commands available in today’s cars by, for example, informing drivers how to change a flat tire (including by playing an instructional video on the car’s display) or by explaining to drivers the meaning of a diagnostic light on the car’s dashboard, telling them whether they should pull over and maybe even make them an appointment at a local repair shop.

We haven’t heard anything about GM’s project since.

In January 2024, Volkswagen unveiled its first vehicles that integrate ChatGPT into its in-car voice assistant, which will supposedly be able to control the infotainment, navigation, and air conditioning, as well as answer general knowledge questions. The company promises that “this can be helpful on many levels during a car journey: Enriching conversations, clearing up questions, interacting in intuitive language, receiving vehicle-specific information, and much more – purely hands-free." The feature is set to start rolling out “in many production vehicles” in Q2 2024, starting in Europe.

I doubt Volkswagen will issue an OTA update to cars already on the road, meaning that most car owners won’t get this functionality for years. Mercedes, BMW, and Hyundai have also promised to integrate large language models to bolster their in-car voice assistants, but not before 2025.

Carmakers moving slowly does not surprise me. Apple and Google, however, haven’t even bothered to talk about updating Carplay and Android Auto with LLMs.

As a result, people are getting into their cars, launching ChatGPT with voice on their phones, and just talking. They’re using the chatbot as a sounding board to brainstorm. They’re entertaining their kids by letting them ask endless questions. They’re accessing a large chunk of humanity’s knowledge by just talking while driving.

People are doing this behind the wheel because the car is the perfect location for voice input. Billions of car trips occur solo. In most parts of the world, the average occupancy of cars is around 1.5 passengers. Even before voice chatbots and voice assistants, seeing people with their mouth open while driving is common. They’re either talking to themselves, singing to themselves, or talking to someone on a call.

The car is thus a great opportunity for voice tech to shift into gear. Not only is talking alone while driving socially accepted, but the car is an enclosed space. A quiet background reduces conversation misunderstandings with everyone, including voice assistants.

Buttons, knobs, and chatbots

In August 2022, Swedish car magazine Vi Bilägare published a study comparing 11 modern cars with touchscreens against a 17-year-old Volvo V70 without a touchscreen. Vi Bilägare measured the time needed for a driver to perform different simple tasks, such as changing the radio station or adjusting the climate control, while driving at 110 km/h (68 mph). You can guess the result: physical buttons were much less time-consuming to use than touchscreens. The study found that the driver in the worst-performing car needed four times longer to perform the simple tasks than in the best-performing car.

It’s thus no surprise that in 2023, carmakers like Volkswagen (including its subsidiary Porsche), Hyundai, and Nissan took public stances about bringing back buttons and knobs for a safer, more distraction-free driving experience. Touchscreens look great, but they’re not safe and they’re useless for relying on muscle memory.

Neither is opening an app while you’re driving. It’s simply not a good user experience.

Even when my phone is connected to my car, I still find myself grabbing it to perform tasks that I know will be faster or take less effort directly in my hand. Touchscreens are fantastic on phones but largely suck in cars. Conversely, using your voice sucks on the phone but could be fantastic in the car.

Ideally, when I’m in my car, I only need to press physical buttons, turn physical knobs, and talk—or better yet, keep my hands on the wheel and just talk.

LLMs are a huge opportunity to make voice the default mode of interaction in a car, or at least the secondary one to pressing buttons and turning dials. Carmakers are moving away from touchscreens for good reason, and they should be investing in voice tech instead.

At this stage in the race, we should be able to design an assistant that is smart enough to know when I want to turn up the music, when I want to ask about what restaurant used to be on the corner that I just passed, when I am talking to someone in the car, and when I am talking to my car. This is not about what AI can do for me, but what I can do with AI.

I don’t care which company is ultimately responsible for making voice tech the car’s default input, but it needs to happen soon. Once humans get hooked on good tech, we don’t easily let go.

Self-driving cars won't

let voice tech win

Self-driving cars won't let voice tech win

If voice tech can leverage LLMs to conquer the car, it could lead to better voice features for smartphones, smart speakers, and the smart home at large. There’s just one problem with this gateway drug leading to more addiction: there’s not enough time.

Voice tech is not going to happen quickly enough. Technology is moving faster than we can adapt to it. I worry that autonomous cars will be the norm before carmakers and tech companies figure out voice tech.

The window of opportunity is closing: If autonomous vehicles become more prevalent first, humans will quickly become distracted by any number of screens, gadgets, and sex, forgetting to talk to their self-driving cars.

Voice input by default can’t be born on the road if self-driving cars turn it into roadkill.

In a world of autonomous cars, voice isn’t as compelling. If no company gets a generation addicted to voice tech, I may never get to talk to my car.

Early in the AI era, smart devices are still dumb

Emil Protalinski
Managing Editor, ON_Discourse

With CES 2024 closing out last week, we’re beginning to distill and synthesize the most important and unique perspectives as part of our Intelligently Artificial Issue. CES 2024 might be over, but there’s an emerging narrative that we’re just beginning to weave together.

Our hardware vs. software debate led us to a predictable conclusion in the AI era: To build a moat, you can’t rely on just hardware or just software. Instead, business leaders must figure out how to leverage software-enabled hardware to deploy robust data strategies. Your differentiator is not your hardware or your software, but how you are collecting data, extracting utility, and offering insights.

More than just a new TV

We were transfixed by transparent TVs from LG and Samsung, but not because they were the most visually impressive devices to see at the convention. The discussion quickly focused on where such transparent screen tech can best be deployed—retail use cases being more likely than the home.

Quantified health leaps forward

Health was the category with arguably the most promise. We saw devices that suggest more granular diagnostic health data is within reach, pending approvals and clearances from government bodies around the world. While large language models have been trained on text scraped from humanity’s printed word, health care models could soon be trained on data scraped from human bodies. The quantification of our bodies means exponentially more health data, including everyday vitals and patient-led diagnostics, leading to new services, new user experiences, and new business models.

New connected health products from companies like Abbott and Withings, in the home and at the clinic, seem inevitable, collecting far more useful data than current wearables. Although we wondered whether an abundance of health devices and excessive health tracking could lead to new mental health issues, the consensus was that consumer wellness tech could have a profound impact on preventive health care. On the flip side, companies expanded beyond the human body to gimmicks like AI dog collars. We pointed to countless examples of “AI-washing”, wherein companies offer no useful AI capabilities but plenty of marketing material claiming otherwise. Every company wants to be an AI company and we found ourselves frequently weeding out hype from reality.

Every company wants to be an AI company and we found ourselves frequently weeding out hype from reality.

Maze of people at CES

Swapping one buzzword for another

In years past, companies were labeling every product and service as “smart.” Now, companies are prepending, inserting, or appending AI to their brand and product names. Nonsense terms like “bespoke AI” don’t help. We posited on our floor tours that while mentioning AI is currently best for your company valuation, using a term like “smart” is more consumer-friendly and representative of what people want from their technology. It’s only a matter of time before marketers come up with something less ominous than “AI” and as apt as “smart” for brands to promote.

Brands, organizations, and UX

Speaking of brands, ON_Members at our briefing event debated whether AI will turn most brands into commodities and whether brands will lose their importance or become more valuable than ever before. There was a general agreement that employers need to hire more experts who understand the human experience, not more experts who understand AI. We also discussed how the AI age could be an opportunity to bring more of the human condition into the user experience.

The death of the smartphone?

The UX discussion often centered on the latest trend of supplementing or outright replacing the smartphone, and what interface would be required for such a device to be successful. These devices fall into two categories: new gadgets, like Humane’s Ai Pin, and AR/VR.

Rabbit’s R1, a palm-sized smart personal assistant device that doesn’t run any apps but can connect to your existing apps, created a lot of buzz. It’s sobering to remember that plenty of CES products, including the exciting ones, ultimately flop (relatedly, Humane wasn’t at CES but laid off some staff during the same week).

User holds phone in front of a crowd of people

We spotted plenty of products that were solutions in search of a problem. AI and smart labels aside, most devices are still dumb: they’re not anticipating our needs and thus can’t take any useful action.

Even if nothing seemed ready for prime time, the most striking innovation seemed to be around input devices, spanning wrist wearables, smart mirrors, and even AR/VR controllers that tap into our bodies’ electrical signals. We saw that AR/VR still isn’t ready in 2024, even with Apple’s usual attempt to try to steal CES, this time with some Vision Pro news.

VR is powerful, but cumbersome, and doesn’t have any use cases outside of porn, gaming, and maybe exercise. AR is more useful, but the form factor has major trade-offs: poor battery life or few features.

Regardless, it’s clear that someone needs to upend the current touchscreen UX to displace the smartphone.

Most devices are still dumb

In sum, we spotted plenty of products that were solutions in search of a problem. AI and smart labels aside, most devices are still dumb: they’re not anticipating our needs and thus can’t take any useful action.

This brings us back to where we started: The future will not be prompted. While everyone is understandably focused on text prompts, we focused on hints that we could be heading toward a future of ambient data collection and anticipatory interactive technology. If brands can make the move from personalization to anticipation, our behavior will become the prompt for AI.

This is just the beginning of our Intelligently Artificial Issue’s next phase, in which we’ll be presenting unique insights driven by provocations and mapped to our three areas of focus:

  • Will AI drive a new UX?
  • Will AI reorganize the re-org?
  • Will brands matter in the AI era?

Are you interested in being part of the discourse, and contributing to this and future Living Issues? Is there a perspective you think we might be missing? Tell us what you think.

ces

Can

Be

Fixed

With

Discourse

Toby Daniels

Co-Founder, ON_Discourse

ON_Discourse co-founder Toby Daniels, a veteran of CES,
has taken over our CES planning meetings with hot takes
from his ample experience from the show. We thought we
should give him the pen to write a mini confessional about
the world’s biggest consumer tech conference. 
—ON_D

Toby Daniels

Co-Founder, ON_Discourse

CES is not new to me. I’ve been attending the event for over 15 years, having walked the crowded halls, networked in one event after the other, and seen countless overhyped tech unveilings.

Executives who report feeling disoriented and isolated.
Subscribe
To Our Newsletter

Receive CES event updates, plus preview articles and more.

CES’ primary problem is the whole event is confusing and crowded, while also
being extremely isolating. I am not alone in making this diagnosis; I have had
countless conversations with fellow convention goers and tech executives who
report feeling disoriented and lonely (especially during loud networking events).
This problem creates the conditions that lead to the second, most common issue.

In this mode, agreement is chosen over conflict, and innovation is nothing but an empty vessel of conventional ideas.

The event’s secondary problem mirrors a major issue in business, tech, and
media: groupthink. The show is an echo chamber with familiar faces and
conventional ideas wrapped in flashy tech. In this mode, agreement is chosen over
conflict, and innovation is nothing but an empty vessel of safe concepts.

CES is often touted as “a beacon for leaders in business and technology," where
the future meets today’s reality. While this paints a picture of innovation and
forward-thinking, it often masks the event’s superficial nature. CES, in all its
glory, can sometimes be more about shiny objects and getting into the hottest
party or VIP event rather than the depth of conversation. Despite the countless
curved TV screens that are never going to be a thing, I believe in the value of this
event and that we can fix CES.

The discipline of discourse is a forcing function that enables us to provoke, argue, challenge, and listen.
Learn More about
ON_Discourse

ON_Discourse is a private membership community and is made up of an expert network of business leaders who participate in the Discipline of Discourse in order to cultivate perspectives, decision-making, and meaningful relationships.

True perspective, I’ve learned, comes from heated debates, uncomfortable questions, and a willingness to listen to opposing viewpoints. This year, we are bringing our discourse and community to CES.

The discipline of discourse is a forcing function that lets us provoke, argue,
challenge, and listen – not just to reply, but to understand and consider. These
authentic engagements help us break free from the cycle of redundancy and
uncover truly groundbreaking ideas and new perspectives.

It's not just
about the technology; it's
about the intelligence behind it.
Learn more about
Intelligently Artificial Issue

How do we distinguish between artificial hype and intelligent opportunities?

At CES 2024, the ON_Discourse team will make the show in January worth
attending for our members, who will be organized into “Pods”, or small groups
that attend sessions together, join dinners, hit up parties, and practice the
discipline of discourse as a single unit. They will also get a guided experience,
including a kick-off briefing, a discourse-driven tour of the convention floor, and
invitations to a carefully curated list of events.

The discipline of discourse is a forcing function that lets us provoke, argue,
challenge, and listen – not just to reply, but to understand and consider. These
authentic engagements help us break free from the cycle of redundancy and
uncover truly groundbreaking ideas and new perspectives.

Apply for
Membership

Join ON_Discourse and get access to the ON_CES Intelligently Artificial Issue, exclusive events, and a discourse-driven floor tour showcasing the latest innovations in AI and tech.

As we move towards CES 2024, I feel a renewed sense of purpose. Our approach
is different – we won’t be there just to observe; we’ll be there to engage and
disrupt the status quo of conversations. We’re setting up to ensure our members
experience CES not as a showcase of gadgets, but as a forum of intelligent,
meaningful dialogue.

I am hopeful that with our concerted effort, this CES will mark a turning point.
Our next Issue, “Intelligently Artificial," will capture this shift from superficial
tech displays to rich, meaningful exchanges of ideas. It’s not just about the
technology; it’s about the intelligence behind it – the thoughts, the debates, and
the discourse.

Toby Daniels

Co-Founder, ON_Discourse

AI will

brainstorm

your next

re-org

Matt Chmiel
Head of 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: Before the launch of the Intelligently Artificial Issue, we invited Peter Smart, the global CXO of Fantasy, to give a demo of a new AI-powered audience research tool the company calls Synthetic Humans. This article is a distillation of the discourse from that event.

Digital product design does not happen in a vacuum. Designers, product owners, marketing teams, and business stakeholders all have extensive conversations with customers before, during, and after designs are ultimately shipped. This process is timely and expensive and it feeds a thriving user research industry; consumer brands pay a premium for access to real people from target audience segments to record reactions and develop concepts. The vendors and design teams then plot that feedback into thousands of slide deck pages across the land. The testers get paid, the vendor gets paid, the design staff gets approval, and the designs ultimately ship.

Here’s the thing about all of this testing: what if it’s fake? What if real people are the problem?

Real people are too human to be reliable. They lie, they cut corners, and their attention wanes. They’re in it for the money, which obscures their true opinions as they are not invested in the experience. They resist change with red-hot passion before they embrace and ultimately celebrate it. They are not useful testers.

The proliferation of user research as a design process is responsible for standardized and conventional design practices online. It is hard to produce a differentiated design when we try to meet people where they say they are.

Put bluntly, real people are a waste of time and money.

Can AI fix this?

Fantasy believes that the solution to this human problem of qualitative testing is to use AI to develop a new, scalable audience research ecosystem built on synthetic humans.

A synthetic human is a digital representation of a human being, built using an LLM that converts a massive amount of real survey data into a realistic representation of a human being. Think of it as a digital shell of a human cobbled together using thousands of psychographics data points.

Prompting a synthetic human should give you a realistic response. As a result, if you train a synthetic human to deliver feedback and reactions to developing ideas, you should get actionable audience data. These modern-day AI-generated avatars are much more powerful than a chatbot because they generate and sustain their own memories.

We are not talking about Alexa or Siri here. A synthetic human initiated with a preliminary dataset (age, demographics, location, income, job, and so on) can determine, without any other prompt, that “she” has two daughters, aged 5 and 3. These daughters have names and go to a certain school. Their teachers have names and each daughter has a favorite subject or cuddle toy.

If you don’t interact with this synthetic human for six months and then prompt “her” again, these daughters would still be in “her” mind, as would the teachers and the school. In the intervening time, the children might have celebrated a birthday, or entered the next grade, all aspects that get folded into the profile and leveraged for realistic responses. As a result, “her” opinions about your developing ideas can feel more reliable.

Organizations can train these humans to react to developing concepts, or brainstorm new concepts outright. They can also leverage their generative memory capabilities to help organizations overcome embedded workflow obstacles, like stubborn stakeholders.

Let’s say an organization knows that “Bob” in audience development has a reputation for capricious feedback that often causes a production bottleneck. The organization can train a synthetic human to brainstorm ways to overcome Bob’s reputation.

Here’s another example. Imagine prompting two contradictory synthetic humans (one is aggressive and the other is conservative) to collectively brainstorm an idea over the weekend so that you can arrive on Monday to a fresh batch of thinking. These two personalities are not just coming up with ideas; they are reacting to each other’s ideas, giving feedback, rejecting suggestions, and building on top of promising sparks.

What's the catch?

There is always a catch. And at ON_Discourse, we lean into the questions that hide underneath the inspiring claims of innovative technology. There is no denying the potential of synthetic humans. It is a direct response to the biggest issues that plague the audience research industry today. Synthetic humans can stay focused, can offer candid feedback, and can be scaled to deliver deeper insights at a lower cost. These are good things. But there are gaps in the capabilities of these tools. Our virtual discourse on November 30 unpacked some of them and thus the limitations of synthetic humans for audience research.

Synthetic humans cannot predict the future. They are locked in the snow globe of their initial configuration. Their generated memories cannot incorporate the development of novel technology or cultural revolutions. As a result, we should not expect this kind of tool to unlock perspectives for new developments. This is notable, given that we are living in an era of rapid, unpredictable change. What humans think about specific disruptions will have to come from other sources.

Synthetic humans do not access deeply human emotional states. They do not grieve. They do not get irate. They do not get horny or goofy, and they do not long after something that is just out of reach. These powerful emotions provide the source material for some of our most inspiring technical and creative accomplishments. Our guests provoked this concept with real-world examples of powerful emotional moments. There are limits to what we can expect an avatar to create – we cannot prompt a bot to dig deeper. Synthetic humans are calibrated to maintain a level set of emotions.

The issues we explored regarding synthetic humans speak more to the role of audience research than to the capabilities of this tool. The collated test results that are plotted on slide decks represent an unintentional hand-off of creative thinking to the masses. Forward thinking organizations are going to recognize the value of synthetic research for solving the achievable problems they face in design and product development. And they will leave the big thinking to the people that still run their business with their head, heart, and with their real human teams.

Are businesses

even asking the

right AI questions?

Dan Gardner

Dan Gardner

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

Dan Gardner

Dan Gardner

Co-Founder and Exec Chair,
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

The AI landscape is changing quickly. So quickly that as soon as we think we’re starting to understand its power, there seems to be another giant leap forward. It doesn’t help that we are surrounded by fake AI experts who claim to have all the answers.

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:

For real customer insights, ask fake people

Should we ignore the hardware?

Truthfully, given all the unknowns, there are more questions than answers today. Each question has a cascading impact on other questions and seems to only bring a series of new questions. The answers right now are only guesses, predictions at best based on hopefully thoughtful reasoning, meant to provide a productive discourse that drives perspectives and decision-making. Any verifiable answers will only reveal themselves tomorrow.

From the editor: The takes below are based on a projection toward the end of the 2020s and are intentionally opinionated and incomplete. We aim to go deeper on each question in future content and at future events, including via ON_CES.

01

What is the future of

SaaS and BI tools?

Today, businesses use siloed tech with a questionable data strategy.

Tomorrow, the SaaS ecosystem will consolidate into very few companies.

Companies of all sizes currently rely on a fragmented ecosystem of technologies. BI tools are siloed not due to the tech itself, but due to a lack of data strategy and organizational structure. People own different elements of the chain (separate teams own social, the web, and so on). This has given discreet software companies the opportunity to solve specific use cases.

The global SaaS market is projected to grow from $273.55 billion in 2023 to $908.21 billion by 2030. In the past decade, marketing software alone has grown from 150 tools in 2011 to 11,038 tools in 2023. There is a high likelihood that the ecosystem could consolidate, eliminating the opportunity and the role of discrete software systems.  

One of the core advantages of AI is its unique ability to assess, simplify, and make sense of large amounts of information. By making sense of data, AI can communicate more easily and effectively given the simplified semantic interfaces, a previous pain point for large consolidated systems.

Since the advent of ChatGPT, we’ve seen a gold rush of companies using LLMs to change the way we process, communicate, and execute decisions. This technology is evolving so quickly that we could see it swallow the companies being built upon it. This should lead to fewer, but better, SaaS and BI tools, bringing up other questions about how companies differentiate themselves and the role of humans.

02

How do we make

AI safe for businesses

to use?

Today, businesses are worried about protecting their IP and potential copyright lawsuits, moral issues, and reputational problems.

Tomorrow, businesses will rely on new legal and procedural precedents to use AI tools liberally.

There is legal precedent, there is enforcement, and there is public opinion.

Firstly, legal precedent (including regulation and policy) will naturally unfold and become clearer. One can make some guesses and predictions here, but ultimately, for competition to thrive, the laws will have to allow for some liberal use of the technologies. This can and will be argued, but it’s a fool’s game to think you can regulate away technological progress.

Secondly, as legal precedents are set, challenges will surface around identification and consequences for any wrongdoing. These will need to be policed at some level and possibly even enforced by code. Could smart contracts on the blockchain protect and enforce IP rights? Additionally, industry collectives like the RIAA, which in the early 2000s protected music IP, may form to make examples of companies and individuals breaching legal boundaries. Alternatively, AI tool use could become so common that courts won’t even consider lawsuits regarding copyright, trademarks, and reputation (although this is hard to imagine).

Lastly, public opinion could shape business use cases. Is there a risk of bias? Does a brand face risks when it represents something inaccurately or inappropriately using AI that it didn’t control? It’s hard enough to manage scaled public relations in a world where an executive is one tweet away from being fired or losing trillions in market value. We are entering a world in which ephemeral content is generated in seconds. Brands may struggle to keep up. Organizations will need to manage AI health just like they do cybersecurity.

03

How do we make

AI safe for people?

Today, businesses own people’s personal data.

Tomorrow, businesses will offer identity protection technology.

Regular audits of public companies not only verify the accuracy and legality of their financial records but also assess whether an organization has adequate controls and processes in place to mitigate potential liabilities. Future regulations may require audits on AI tools to make sure companies are operating legally, including via people controls and by reviewing code.

The government or businesses may also offer trust systems that let people authenticate their identities to interact as themselves with public and private sector services.

Alternatively, people may try to circumvent any potential censorship or gating by masking their identities.

04

Is your

competitive landscape

being

disrupted?

Today, businesses try to understand their direct competitors.

Tomorrow, businesses will be able to analyze their indirect competitors and existential threats.

AI-powered analysis tools could soon ingest data about every market globally and make connections between businesses, causing entire industries to disappear. Businesses could leverage AI to be predictive and anticipatory, uncovering opportunities that disrupt categories they never considered entering. Super apps that can do everything are a real threat.

Alternatively, categorical disruption may not happen because businesses will train AI tools on proprietary data to maintain their competitive advantage. The role of a brand will thus still matter because companies that are more focused on designing a specific user experience will be able to continue to differentiate themselves by providing unique value, while non-focused competitors won’t.

05

What is the future of

customer experience landscapes?

Today, businesses rely on traditional personalized targeting, information architecture, and rigid user flows.

Tomorrow, businesses will rely on anticipatory semantic and potential ephemeral experiences to target behaviors.

Is the interface that consists of a simple prompt text box with a response field here to stay? Or, will interfaces across various devices foresee what humans want, need, and desire, showing only the information that is relevant to users, when and where it’s required? Instead of you prompting the interface, maybe the interface will prompt you.

AI models may be able to help companies better understand their customers, viewing each one as a whole person and generating for them a more efficient, frictionless, and possibly ephemeral, experience in real time. This could include entertainment, marketing generated to pique interest, and interface elements like CTAs and drop-downs built in real time.

Alternatively, humans may not want generated content or experiences and will opt for more directed, but still personalized, user experiences.

06

What is the future of

branding?

Today, businesses build brand identities based on static logos and brand books.

Tomorrow, businesses will build brands whose attributes can be generated on the fly based on an identity that more closely resembles a human.

Brands in the future will have to act in real time. AI will be on the front lines across touchpoints, communicating dynamically with customers. The way a brand communicates at those digital moments will largely represent the whole brand.

It’s also conceivable that ad units will evolve into more dynamic product placements or other unique constructs as the world pivots to where audiences are engaging. The interactions will seemingly be more human and therefore branding will need to be more lifelike, built into a framework that can make its own decisions.

Conversely, brands could lose meaning because every business can just mirror back to people what they want, in real time.

07

Does

authenticity matter?

Today, a brand brings authenticity.

Tomorrow, ownership will be more important than authenticity.

Companies are grappling with when and how to be transparent about their use of AI tools. As AI becomes the baseline, companies that own everything they do will stand out. They may be able to build authenticity by unapologetically using AI to offer their customers what they need and want.

The key attribute will be ownership. Whether a piece of content is a deepfake won’t matter if you own the rights to use a given name, image, or likeness. How you create the content won’t be controversial. Ownership will be a core defining factor of both uniqueness and differentiation for a brand.

One could argue that a brand will be even more valuable in the future as a lot of the market consolidates and aggregators become makers. That said, ownership and uniqueness may become harder to achieve, and unique rights might become more expensive.

08

Should a business

invest quickly or slowly

in AI?

Today, businesses either invest too slowly and leave themselves open to disruption or too quickly and spend wasted capital.

Tomorrow, the landscape will be defined by where the opportunity and need for investment is.

Businesses recognize the importance of AI but often overspend due to a fear of falling behind. Despite the influx of ever-improving tools, there’s a noticeable redundancy in these so-called “innovative” ideas, hinting at future industry consolidation. On the flip side, inaction poses its own dangers, potentially leading to business stagnation and loss of a competitive edge.

Businesses should do two things immediately: build and invest in a data strategy and create a culture of safe experimentation with AI tools. The barrier to entry is surprisingly low.

09

What will

define creativity

in the

future?

Today, businesses define creativity as a skill.

Tomorrow, businesses will define creativity only in the way humans think, not what humans can do.

The advent of generative AI could fundamentally transform how we value skills, pivoting from the traditional execution of skills to an emphasis on analytical and creative thinking. The necessity for manual skills in drawing, writing, or designing may diminish, as generative AI democratizes these abilities.

Furthermore, the reliance on human intuition for decision-making could shift toward AI-driven insights and analyses, processed rapidly and impartially. This change might render prompt engineers obsolete, as AI chatbots take on the burden of generating complex prompts.

This shift could lead to a scenario where digital content and experiences are ephemeral, created spontaneously by AI, potentially reducing the significance of human creativity in producing “things." Creativity might then be seen as a common resource, easily replicable and valued less.

Conversely, the future of business creativity might lie in the ability to innovate without relying on data or existing knowledge. Human distinctiveness could emerge through the generation of novel ideas, fueled by uniquely human emotions, such as passion and envy. In this scenario, genuine creativity could become rarer, yet significantly more treasured.

Final
Thoughts

AI is going to shuffle the deck of what companies do and provide, changing the competitive landscape and ultimately the workforce. Some changes will be obvious, like new forms of creative workforces, but others won’t be, like new types of departments, roles, and C-level officers around ethics, identity, and customer safety.

Do you disagree or have a completely different perspective?
We'd love to know.

The

future of

sports rights

in streaming

is drama

Andrew Rosen

Andrew Rosen is the founder of PARQOR LLC. He authors Medium Shift, a monthly column on The Information tracking the transformations underway in the media business.

There is an uneasy tension in the sports rights model across cable, broadcast, and streaming.

On the one hand, cord-cutting is eating away at the extraordinary scale of linear, which counted more than 105 million cable TV households in the US over a decade ago. The pricing of past sports rights deals reflected that, and not so much the promise of streaming.

Today, there are around 60 million homes with cable access, and over 75 million if we include virtual cable distributors like YouTube TV and Fubo TV.

On the other hand, new sports rights deals must assume both the declining scale of cable network distribution and the growth of streaming. The recent NFL deal has Paramount’s CBS, Comcast’s NBC, and Disney’s ABC and ESPN all distributing games across both linear and streaming platforms (Fox will distribute via linear, only). Deals struck in the past few years by the NHL, the PGA Tour, and WWE also have versions of the linear plus streaming business logic built in.

There are growing questions emerging about the business model of streaming. Legacy media streaming services are struggling to scale and to turn a profit. The worry is that some may not be around in a few years. In some cases, like with Paramount Global, their negative free cash flow and junk-rated debt are legitimate reasons for partners like the NFL to be worried.

Four scenarios

The uneasy tension creates four possible scenarios:

1.
Cord-cutting accelerates and legacy media streaming services do not scale.

2.
Cord-cutting accelerates and legacy media streaming services continue to scale.

3.
Cord-cutting slows down and legacy media streaming services do not scale.

4.
Cord-cutting slows down and legacy media streaming services continue to scale.

Until January 2022, the market assumed either scenario #2 or scenario #4: Everyone expected streaming to be the inevitable heir to linear distribution. When Netflix missed its growth forecast for Q4 2021, everything changed. The miss triggered a 65% drop in Netflix’s stock price and drops in the price of the legacy media companies. Wall Street reacted with new demands for profitability over growth. 

The market now seems to believe scenarios #1 and #3 are more likely as potential futures for legacy media. Legacy media companies are being priced accordingly, witnessing their stock prices decline as they struggle to deliver growth while cutting costs to ensure profitability. Sports TV broadcasts may thus never again see the scale of the past few decades. This year’s MLB World Series was reportedly the least-watched on record, averaging 9.11 million viewers. That is around 20% of the most-watched World Series of 1978, which had an average viewership of 44.28 million viewers.

Enter Amazon and YouTube

The NFL’s deals with Amazon and Google’s YouTube have introduced some new paradigms for how scale may be aggregated. In the US, Amazon has an estimated 168 million Prime subscribers and YouTube reaches 150 million people across connected TVs. To distribute Thursday Night Football, Amazon is paying the NFL about $1 billion per year through 2033, Fox, Paramount, and Comcast are paying $2 billion per year, and Disney is paying around $2.7 billion. YouTube is betting on broadcast economics for its Sunday Ticket distribution deal with the NFL—$14 billion over seven years, a 33% increase from DirecTV’s $1.5 billion deal.

Owning the fiber-optic points of connection with consumers means that cable companies market on behalf of third parties to drive tune-in. YouTube and Amazon meanwhile rely on consumers randomly visiting and revisiting their platforms for free consumption of content or shopping. All TV homes can instantly tune in with the tap of a remote control, but not all YouTube or Amazon users have those platforms readily accessible from their connected TVs, mobile devices, tablets, or desktop computers. There is more friction in the paths on YouTube and Amazon between the decision to tune in and actually tuning into the game.

That said, the 2023 NFL season has been a success so far on both platforms. YouTube has now taken over Sunday Ticket and surpassed DirecTV’s total annual subscribers (hitting an estimated 1.3 million subscribers, up from 1.2 million). Amazon’s Thursday Night Football is averaging 12.2 million viewers this season, up 26% from the 9.7 million for the first nine games in 2022. Including Amazon’s internal data with Nielsen data, Thursday Night Football is averaging 13.22 million viewers for the season, to date.

YouTube and Amazon rely on consumers randomly visiting and revisiting their platforms for free consumption of content or shopping. All TV homes can instantly tune in with the tap of a remote control, but not all YouTube or Amazon users have those platforms readily accessible”

Legacy media streaming services are struggling to scale and turn a profit. The worry is that some may not be around in a few years.”

Mark Cuban and aggregate audiences

One of the more notable aspects of Amazon’s Thursday Night Football product is that it offers Amazon Prime subscribers multiple broadcasts: the Spanish feed (TNF en Español) and the advanced stats feed (Prime Vision with Next Gen Stats), to which the company has been adding AI innovations. Amazon has also offered feeds from YouTube influencers Dude Perfect, and NBA star LeBron James and his business partner Maverick Carter. On top of those, Amazon distributes a linear feed via DirecTV to over 300,000 sports bars, restaurants, hotel lounges, casinos and sports books, retail shops and services, and other venues nationwide.

The approach mirrors a personal favorite quote from NBA team Dallas Mavericks owner Mark Cuban in an interview he gave to SportTechie in April 2020. It is worth re-reading whenever a new sports distribution rights deal is announced:

“Can we have three, four, five streams of the same game that’s going on traditional TV? You might have one where you have Twitch-like announcers; you might have two of your favorite YouTubers that are doing another stream; you might have your traditional broadcasters doing another stream; you might have a players-only doing another stream. We don’t care if there’s four, five, six streams—we care about the aggregate audience.”

There are two key takeaways from this quote. First, audiences have affinities or preferences for viewing experiences that the internet enables. Therefore, the best distribution strategy in sports is aggregating audiences across platforms. Rights deals need to enable that. Second, we are still in the early experimental days. The future of sports distribution probably involves linear distribution at a smaller scale and some evolution of the aggregation of multiple streams that capture smaller audiences around their affinities and fandoms.

As for Netflix

The other player to keep an eye on is Netflix. Co-CEO Ted Sarandos told investors on the company’s most recent earnings call: “We are in the sports business, but we’re in the part of the sports business that we bring the most value to, which is the drama of sport.” By “drama” he was referring to the docuseries about Formula 1 Racing (“Drive to Survive”), the PGA Tour (“Full Swing”), and the Tour de France (“Unchained”).

But, in the same answer, he also mentioned that Netflix is “investing heavily in increasing our live capabilities so that as the demand grows for that and we find different ways, the liveness can be part of the creative storytelling, we want to be able to do that at a big scale.”

An example he cited was The Netflix Cup, which streamed live on November 14 to mixed reviews. It was a live golf tournament with the casts of Drive to Survive and Full Swing.

Sarandos’ explanation ties back to something he said back in December 2022 at the UBS 50th Annual Global TMT Conference: “the economics of live sports are built around pay TV and don’t make sense for streaming.” So, Netflix management did not see a “profit path to renting big sports”, then, because the return on investment is lower. That is likely because their model relies more heavily on subscribers, and traditional sports broadcasts have relied more heavily on advertising in network TV, as well as both affiliate fees and advertising in cable broadcasts.

The question one year later is how Netflix’s management may see the opportunity differently. If The Netflix Cup is a precedent, live streaming content needs to be related to documentary content hosted and owned by Netflix. There needs to be an interplay between the two to justify the ROI.

On this point, John Ourand of Sports Business Journal reports that Netflix is considering creating a docuseries around the NBA’s new In-Season tournament. The business model will be a step in the direction of the cable TV business, monetizing viewers with both subscription revenue and advertising revenue. But, as Sarandos told the UBS Conference, the value of the rights to Netflix will be different from broadcast because the economics of the streaming model requires it.

If The Netflix Cup is a precedent, live streaming content needs to be related to documentary content hosted and owned by Netflix.”

The NBA deal

The next NBA deal will start in the 2025 season and the league is already shopping it around. Under the NBA’s current agreement, Disney’s ESPN/ABC and Warner Bros Discovery’s TNT collectively pay $2.6 billion each year to televise about 165 nationally distributed games. One expectation is that the deal price will go up, but another expectation is that Disney and Warner Bros. Discovery will not be in a strong enough position to deliver the same audiences or ROI they were once able to.

The looming question is: why won’t Netflix imitate YouTube and Amazon’s bet on broadcast economics in any deal with the NBA in 2024?”

If the Netflix signals are right, beginning in 2024 the next NBA deal is going to be an aggregation of different distribution models. First, Disney and Warner Bros. Discovery will remain, but at a smaller scale than their current 165 games. Second, Apple, Amazon, and YouTube all seem well-positioned to capture some of those games, and perhaps more, given Disney’s and Warner Bros. Discovery’s recent challenges in the linear advertising marketplace. Last, Netflix will be distributing 67 games of the in-season tournament. 

Whether it will be ideal for the NBA and its partners is anybody’s guess. Even the NFL is looking nervously at the future of its legacy media distribution deals, with Paramount’s status facing the most questions. Aggregation is ultimately a portfolio approach to distribution and not a one-size-fits-all solution. So, whether rights deals are undervalued or overvalued will ultimately depend on how a sports league manages its portfolio of deals, and how its partners manage their various cohorts of audiences.

Do you agree with this?
Do you disagree or have a completely different perspective?
We’d love to know

Can insurgent leagues capture market share from the NFL?

This topic kept coming up in our various events: the NFL is God. And God is immune to all the forces that are challenging the other incumbent leagues like the NBA and MLB. What makes the NFL so powerful? Is it a better TV experience? Is it a better sport? The rest of the world would argue against that. (And they probably want the word football back).

Better storytelling can bring new audiences to traditional sports


The NFL is built on initial scarcity. It started with two games broadcasted one day a week in the autumn. Then came Sunday Night Football, then Monday Night Football. Then Thursday Night Football followed that. Now we have Sunday Ticket and the Red Zone channel. All of that football turned into fantasy football leagues, online gambling. And all of that engagement is padded with endless expert analysis that fills in the gaps in between all the snaps. Is this ecosystem too strong to be disrupted?

This question unlocked a lot of thinking.

What does a league need to thrive? How can an old sport evolve and find new audiences? Can a team of insurgent leagues take down the mighty NFL?

Yes, but...

Sports need tribes to survive

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What is a

better

differentiator

in the AI era?

From the editor: Below we have recreated a recurring debate from our discourse-driven floor tours at CES 2024. On one hand, the AI era is making good software ubiquitous; is that a threat to brands that are looking to distinguish themselves? On the other hand, novel hardware might be taking over as the most reliable strategy for differentiation. Two of our co-founders have polar opposite responses to the question: what is a better differentiator in the AI era?

Software

Michael Treff

MIKE TREFF

CEO, Code and Theory
Co-Founder, ON_Discourse

Hardware

Dan Gardner

DAN GARDNER

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

Think back to past CES events. There have been very few times where the hardware unveiled therein had a material impact on the world or enabled businesses to operate differently.

I wouldn’t ignore hardware, but in the AI race, software far outweighs hardware. Making supply chain changes to improve hardware is far easier than creating true differentiation in software.

You can change the form factor in a product innovation cycle more easily than you can move quickly with AI. As everyone tries to innovate, whether that be in services, operations, business intelligence, generative functions, or any other area, the differentiation when applying AI is going to be in the software, not the hardware. It’s the software that differentiates the hardware to create loyalty and habit.

So, when I’m at CES, I’m looking for the guts of things and the differences in capabilities that the guts provide, rather than the form factors.

But...

Because software is easy to iterate on, everybody can and will do so, which means the ability to have differentiation will reduce very quickly. AI’s biggest strength is the consolidation of data and action.

Finding differentiation through uniqueness of service value will diminish as consolidation enables accessing data across industries. The ease of entry means that the super apps and the larger corporations will just suck any uniqueness into their offerings.

Hardware is a different story. Physicality and context to a human being is something that can be unique and ownable. It’s very difficult and very expensive, but that’s where the opportunity is.

If you’re able to gain permanent access in a unique way, whether via a connected device, a physical screen, a camera, a connected piece of jewelry, AI-driven glasses, or physical locations, you will be on the front lines to deliver an exceptional and differentiated experience that a software developer cannot quickly achieve. Hardware lets you create a moat in a world where software is consolidating.

Well...

If the hypothesis is that AI software development is simple, then hardware is the differentiator. Sure. I don’t think, however, that any significant differentiation or innovation in AI applications is going to be simple.

Companies that are going to use software and AI-driven software to differentiate either their services or their products won’t be doing quick software development cycles. Those are very long-term development cycles, primarily because developing differentiation and value requires creativity in how one uses the data. Achieving differentiation in turn requires a thoughtful and dedicated data strategy that may take a very long time to get critical mass to unlock the power of that data.

These are long-term software development cycles, not quick-turn things that can be replicated using open-source models with minimal layering. So, if you’re going to drive to that level of differentiation, the longer-term development timeline is all about the software, not the hardware.

I do not believe large companies with massive R&D budgets are going to rely on off-the-shelf AI software to enable the products, services, and experiences that will fuel their growth. They will invest in custom models, custom datasets, and custom AI applications, and that will become the IP that helps drive their valuations. These are long-term software development cycles, not quick-turn sprints that can be replicated using open-source models with minimal layering. So, if you’re going to drive to that level of differentiation, the long-term development timeline is all about the software, not the hardware.

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 know, but...

I think a long-term view will only give further opportunity for software to consolidate. If the view is long term, that gives you the runway to create differentiation in hardware. The software landscape is a race between dozens of companies trying to execute every imaginable idea. Over a long-term timeframe, the large-scale companies are going to swallow those up.

If you look at the landscape of software, you’re seeing a race of dozens of companies trying to execute every imaginable idea. The large-scale companies are going to swallow those up, over a long-term timeframe.

If you can surprise through unique hardware, that will be the differentiator. If you develop a piece of software over the long term, a competitor will only be able to replicate it faster and faster. If you develop a piece of hardware over the long term, especially one that resonates with people enough that they purchase it, you have the advantage of physicality and can drive your unique software differentiation through that owned touchpoint. You will own that moment in a way that no one can just iterate on.

There are dozens, if not hundreds of companies working on the same use case that will eventually come to the market. Say you spend two years on a specific use case leveraging your AI. You launch and then three months later, another company does something very similar. It’s marginally better or marginally worse. There is no moat to hold that customer in that unique way.

Conversely, say you spend two years working on a unique piece of hardware and launch it. Say people purchase it and then three months later, there’s a competitor. Your customers are not just going to buy the next piece of hardware. You’ve already beat them onto your customer’s body, into their home, or into their physical world. That creates a uniqueness that can’t just be quickly taken away from you.

So, in conclusion...

Hardware matters. Imagine a company invents new AR tech that can be easily integrated into any piece of glass. Imagine a company that builds a platform to let anyone cheaply project onto any piece of glass. Either way, every window can now be a screen. That matters. Your brand may not be the company that invents a new form factor, but you need to be able to leverage the latest innovation. Ultimately, you can’t ignore hardware or the software.

If your brand wants to build a moat, however, the key isn’t hardware or software. It’s data. To stay relevant, business leaders must figure out how to leverage software-enabled hardware to deploy robust data strategies.

The question then is: Do you have the data to be competitive?

Are businesses

even asking the

right AI questions?

Dan Gardner

Dan Gardner

Co-Founder and Exec Chair, 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:

For real customer insights, ask fake people

Should we ignore the hardware?

The AI landscape is changing quickly. So quickly that as soon as we think we’re starting to understand its power, there seems to be another giant leap forward. It doesn’t help that we are surrounded by fake AI experts who claim to have all the answers.

Truthfully, given all the unknowns, there are more questions than answers today. Each question has a cascading impact on other questions and seems to only bring a series of new questions. The answers right now are only guesses, predictions at best based on hopefully thoughtful reasoning, meant to provide a productive discourse that drives perspectives and decision-making. Any verifiable answers will only reveal themselves tomorrow.

From the editor: The takes below are based on a projection toward the end of the 2020s and are intentionally opinionated and incomplete. We aim to go deeper on each question in future content and at future events, including via ON_CES.

01

What is the future of

SaaS and BI

tools?

Today, businesses use siloed
tech with a questionable data
strategy.

Tomorrow, the SaaS
ecosystem will consolidate
into very few companies.

Companies of all sizes currently rely on a fragmented ecosystem of technologies. BI tools are siloed not due to the tech itself, but due to a lack of data strategy and organizational structure. People own different elements of the chain (separate teams own social, the web, and so on). This has given discreet software companies the opportunity to solve specific use cases. 

The global SaaS market is projected to grow from $273.55 billion in 2023 to $908.21 billion by 2030. In the past decade, marketing software alone has grown from 150 tools in 2011 to 11,038 tools in 2023. There is a high likelihood that the ecosystem could consolidate, eliminating the opportunity and the role of discrete software systems.

One of the core advantages of AI is its unique ability to assess, simplify, and make sense of large amounts of information. By making sense of data, AI can communicate more easily and effectively given the simplified semantic interfaces, a previous pain point for large consolidated systems.

Since the advent of ChatGPT, we’ve seen a gold rush of companies using LLMs to change the way we process, communicate, and execute decisions. This technology is evolving so quickly that we could see it swallow the companies being built upon it. This should lead to fewer, but better, SaaS and BI tools, bringing up other questions about how companies differentiate themselves and the role of humans.

Agree
Disagree

02

How do we make

AI safe for

businesses

to use?

Today, businesses are worried
about protecting their IP and
potential copyright lawsuits,
moral issues, and reputational
problems.

Tomorrow, businesses will
rely on new legal and procedural precedents to use
AI tools liberally.

There is legal precedent, there is enforcement, and there is public opinion.

Firstly, legal precedent (including regulation and policy) will naturally unfold and become clearer. One can make some guesses and predictions here, but ultimately, for competition to thrive, the laws will have to allow for some liberal use of the technologies. This can and will be argued, but it’s a fool’s game to think you can regulate away technological progress.

Secondly, as legal precedents are set, challenges will surface around identification and consequences for any wrongdoing. These will need to be policed at some level and possibly even enforced by code. Could smart contracts on the blockchain protect and enforce IP rights? Additionally, industry collectives like the RIAA, which in the early 2000s protected music IP, may form to make examples of companies and individuals breaching legal boundaries. Alternatively, AI tool use could become so common that courts won’t even consider lawsuits regarding copyright, trademarks, and reputation (although this is hard to imagine).

Lastly, public opinion could shape business use cases. Is there a risk of bias? Does a brand face risks when it represents something inaccurately or inappropriately using AI that it didn’t control? It’s hard enough to manage scaled public relations in a world where an executive is one tweet away from being fired or losing trillions in market value. We are entering a world in which ephemeral content is generated in seconds. Brands may struggle to keep up. Organizations will need to manage AI health just like they do cybersecurity.

Agree
Disagree

03

How do we make

AI safe for

people?

Today, businesses own
people’s personal data.

Tomorrow, businesses will offer
identity protection
technology.

Regular audits of public companies not only verify the accuracy and legality of their financial records but also assess whether an organization has adequate controls and processes in place to mitigate potential liabilities. Future regulations may require audits on AI tools to make sure companies are operating legally, including via people controls and by reviewing code.

The government or businesses may also offer trust systems that let people authenticate their identities to interact as themselves with public and private sector services.

Alternatively, people may try to circumvent any potential censorship or gating by masking their identities.

Agree
Disagree

04

Is your

competitive

landscape

being

disrupted?

Today, businesses try to
understand their direct
competitors.

Tomorrow, businesses will be
able to analyze their indirect
competitors and existential
threats.

AI-powered analysis tools could soon ingest data about every market globally and make connections between businesses, causing entire industries to disappear. Businesses could leverage AI to be predictive and anticipatory, uncovering opportunities that disrupt categories they never considered entering. Super apps that can do everything are a real threat.

Alternatively, categorical disruption may not happen because businesses will train AI tools on proprietary data to maintain their competitive advantage. The role of a brand will thus still matter because companies that are more focused on designing a specific user experience will be able to continue to differentiate themselves by providing unique value, while non-focused competitors won’t.

Agree
Disagree

05

What is the future of

customer

experience

interfaces?

Today, businesses rely on traditional personalized targeting, information architecture, and rigid user flows.

Tomorrow, businesses will rely on anticipatory semantic and potential ephemeral experiences to target behaviors.

Is the interface that consists of a simple prompt text box with a response field here to stay? Or, will interfaces across various devices foresee what humans want, need, and desire, showing only the information that is relevant to users, when and where it’s required? Instead of you prompting the interface, maybe the interface will prompt you.

AI models may be able to help companies better understand their customers, viewing each one as a whole person and generating for them a more efficient, frictionless, and possibly ephemeral, experience in real time. This could include entertainment, marketing generated to pique interest, and interface elements like CTAs and drop-downs built in real time.

Alternatively, humans may not want generated content or experiences and will opt for more directed, but still personalized, user experiences.

Agree
Disagree

06

What is the future of

branding?

Today, businesses build brand
identities based on static
logos and brand books.

Tomorrow, businesses will
build brands whose attributes
can be generated on the fly
based on an identity that more
closely resembles a human.

Brands in the future will have to act in real time. AI will be on the front lines across touchpoints, communicating dynamically with customers. The way a brand communicates at those digital moments will largely represent the whole brand.

It’s also conceivable that ad units will evolve into more dynamic product placements or other unique constructs as the world pivots to where audiences are engaging. The interactions will seemingly be more human and therefore branding will need to be more lifelike, built into a framework that can make its own decisions.

Conversely, brands could lose meaning because every business can just mirror back to people what they want, in real time.

Agree
Disagree

07

Does

authenticity

matter?

Today, a brand brings
authenticity.

Tomorrow, ownership will be
more important than
authenticity.

Companies are grappling with when and how to be transparent about their use of AI tools. As AI becomes the baseline, companies that own everything they do will stand out. They may be able to build authenticity by unapologetically using AI to offer their customers what they need and want.

The key attribute will be ownership. Whether a piece of content is a deepfake won’t matter if you own the rights to use a given name, image, or likeness. How you create the content won’t be controversial. Ownership will be a core defining factor of both uniqueness and differentiation for a brand.

One could argue that a brand will be even more valuable in the future as a lot of the market consolidates and aggregators become makers. That said, ownership and uniqueness may become harder to achieve, and unique rights might become more expensive.

Agree
Disagree

08

Should a business

invest quickly

or slowly

in AI?

Today, businesses either
invest too slowly and leave
themselves open to
disruption or too quickly and
spend wasted capital.

Tomorrow, the landscape will
be defined by where the
opportunity and need for
investment is.

Businesses recognize the importance of AI but often overspend due to a fear of falling behind. Despite the influx of ever-improving tools, there’s a noticeable redundancy in these so-called “innovative” ideas, hinting at future industry consolidation. On the flip side, inaction poses its own dangers, potentially leading to business stagnation and loss of a competitive edge.

Businesses should do two things immediately: build and invest in a data strategy and create a culture of safe experimentation with AI tools. The barrier to entry is surprisingly low.

Agree
Disagree

09

What will

define

creativity

in the

future?

Today, businesses define
creativity as a skill.

Tomorrow, businesses will
define creativity only in the
way humans think,
not what humans can do.

The advent of generative AI could fundamentally transform how we value skills, pivoting from the traditional execution of skills to an emphasis on analytical and creative thinking. The necessity for manual skills in drawing, writing, or designing may diminish, as generative AI democratizes these abilities.

Furthermore, the reliance on human intuition for decision-making could shift toward AI-driven insights and analyses, processed rapidly and impartially. This change might render prompt engineers obsolete, as AI chatbots take on the burden of generating complex prompts.

This shift could lead to a scenario where digital content and experiences are ephemeral, created spontaneously by AI, potentially reducing the significance of human creativity in producing “things." Creativity might then be seen as a common resource, easily replicable and valued less.

Conversely, the future of business creativity might lie in the ability to innovate without relying on data or existing knowledge. Human distinctiveness could emerge through the generation of novel ideas, fueled by uniquely human emotions, such as passion and envy. In this scenario, genuine creativity could become rarer, yet significantly more treasured.

Agree
Disagree

Final

Thoughts

AI is going to shuffle the deck of what companies do and provide, changing the competitive landscape and ultimately the workforce. Some changes will be obvious, like new forms of creative workforces, but others won’t be, like new types of departments, roles, and C-level officers around ethics, identity, and customer safety.

Do you disagree or have a completely different perspective?
We'd love to know.

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