Can AIOS Find the Gap Behind Your Next 100% of Growth?

Can AIOS help a company find the gap behind its next 100% of growth?

That is deliberately provocative. We are not claiming that an AI research tool can simply double a company's revenues.

The more interesting question is whether AI can help management identify the things that ultimately drive revenue: a market worth entering, an unmet customer need, a product gap, a weak competitive position, an objection suppressing conversion, or an attribute for which customers may be willing to pay more.

We have always thought about AIOS in those terms.

AIOS is not simply an SEO or GEO tool that counts citations and mentions. Its broader purpose is to interrogate what AI knows about a brand.

What category does an LLM put the brand in? What does it think the brand is good at? What utility does it associate with it? Who does it believe its competitors are? When is the brand the default recommendation, and under what conditions does that position collapse?

With the launch of Apple's first foldable iPhone, we decided to push that premise further:

Could AIOS use the same approach to map not just a brand, but an entire product category?

And if it could, might the resulting insights be useful not only to marketers but to management teams thinking about product development, competitive strategy and market entry?

We started with the customer

We defined a customer considering a foldable smartphone.

At the beginning of the simulated journey, that consumer knows relatively little and has limited purchase intent. As the journey progresses, the questions become more informed, comparisons become more specific and the customer eventually reaches a point where they can make a decision.

AIOS simulates that progression through a large set of customer scenarios.

One question asked:

“Do foldable screens actually hold up over two years, or am I babying the hinge constantly?”

That prizes out information about durability, the flexible display, hinge life and repair risk.

Another asked:

“Between Samsung, Motorola and Honor foldables, which direction should I lean for durability and updates?”

Now the LLM has to begin assigning attributes to competitors. Samsung becomes associated with software longevity and support; Honor emerges as a hardware challenger; Motorola occupies a different part of the foldable market.

Then:

“If I had to pick one foldable today for reliability and support, what would you recommend?”

Now the model has to choose. Samsung repeatedly emerged as the safer default.

AIOS also approaches those journeys through different lenses. We test what appears without prompting the brand, compare brands directly, examine the utility language AI associates with each player, and stress-test brand positioning by introducing competitors and specific threats.

Different questions prize out different information.

For this exercise, AIOS analyzed 316 query runs across OpenAI, Gemini and Perplexity.

That produced a research surface large enough to start seeing patterns rather than anecdotes.

AIOS measured a 63% genuine citation rate across the run while separately identifying 57 ghost-citation events. Simply counting citations without validating them would therefore have produced a materially different picture.

But the more interesting findings were not citation statistics. They were what AI appeared to believe about the market.

Finding one: “Foldables” are actually two categories

The analysis quickly separated the category into two fundamentally different propositions.

• Book-style foldables turn a phone into something approaching a small tablet. Their utility is about more: more screen, more applications visible simultaneously, better reading, productivity, gaming and media.
• Clamshell foldables solve almost the opposite problem. Their utility is about less: making a full smartphone dramatically smaller and more pocketable.

The AI responses explicitly distinguished them. Book devices were favored for real multitasking; flip devices for portability and convenience.

This distinction also appeared in the gaps AIOS surfaced. The largest content and question gap was clamshell pre-purchase guidance, with 20 missed-query instances. Durability generated 13 misses, and real-world performance—battery, overheating, photography and daily usability—generated another 11.

That is already a useful market-entry finding. A company saying “we want to enter foldables” has not yet defined its market.

Do we want to make a phone that becomes bigger—or a phone that becomes smaller?

Those are different jobs to be done.

Finding two: AI had already constructed a competitive map

The answers also created a surprisingly clear hierarchy of brands.

Within the competitive-framing layer of this research, Samsung was mentioned 205 times, versus Google 93 times, Motorola 89, Honor 28 and Apple 19. These are frequencies within the AIOS research corpus, not market shares, but they reveal the relative prominence of brands in the AI answer space.

Again, the attributes behind those numbers were more interesting than the ranking.

• Samsung was repeatedly the safe default: established foldable experience, mature software, multitasking, support and an ownership ecosystem.
• Motorola had carved out a stronger clamshell identity.
• Google emerged as a credible premium book-style challenger.
• Honor appeared considerably less often overall, but increasingly around hardware engineering, productivity and durability.

This is what we mean by category sonar. AIOS was not merely asking, “Did Samsung get mentioned?”

It was beginning to answer: “What territory does Samsung own, and where are other brands beginning to encroach?”

Finding three: It identified the barriers to adoption

The analysis surfaced six recurring gap clusters:

• 20 clamshell pre-purchase misses
• 13 durability misses
• 11 real-world performance misses
• 7 budget and value misses
• 6 multitasking and productivity misses
• 6 long-term ownership confidence misses

Those numbers began to form a coherent market-entry problem statement. Consumers wanted to know:

• Will the hinge last?
• Is the inner screen still fragile?
• Will the battery get me through the day—and will it overheat?
• Is it too thick or heavy?
• Are the cameras compromised versus a premium conventional phone?
• What happens if I need it repaired?
• Does any of this justify the price premium?

AIOS also detected 31 instances of implicit negative framing in the answers, including concerns around durability, maximum battery life and price.

Critically, the competitive set was not just one foldable against another. A $1,000–$2,000 foldable is also competing with an excellent conventional smartphone.

One AI answer framed the choice directly: the foldable delivered compactness and a larger screen, while the conventional flagship retained advantages around durability and camera quality.

AI also showed us who shapes the market narrative

Another interesting part of the sonar was not about manufacturers at all.

AIOS showed that the foldable category was being interpreted heavily through independent technology publishers.

• Android Central appeared as a top displacer 124 times.
• PhoneArena appeared 116 times.
• Tom's Guide appeared 112 times.
• PCMag appeared 85 times.

That matters to a marketer because category positioning inside AI is not determined purely by what brands say about themselves. It is mediated by the sources the models trust.

So an AI market map can potentially tell a company not just what narrative it needs to change, but where that narrative is being formed.

Again, that is considerably richer than a ranking report.

Then Apple gave us an interesting external check

Only after constructing this category map did we explicitly compare Apple's announced product with the issues AIOS had surfaced.

A methodological qualification is important here.

The AIOS scan ran after Apple's September 9 announcement, so Apple could—and did—appear organically in some answers. But we did not use the iPhone Duo's specifications or Apple's launch claims to construct the pain-point analysis. We first analyzed what the category questions surfaced and then separately mapped Apple's product response against those issues.

The correspondence is striking:

• AIOS surfaced durability and hinge anxiety. Apple's launch emphasizes Grade 5 titanium, an IP68 rating, a hinge built from more than 100 components, structural reinforcement and a strengthened flexible display.
• AIOS surfaced the crease and vulnerable inner display. Apple specifically engineered the display surface to minimize crease visibility and says its custom polymer layer provides up to 40% greater stiffness than comparable industry materials.
• AIOS surfaced battery and thermal concerns. Apple introduced a dual-battery architecture and a custom vapor chamber designed to sustain demanding multitasking, gaming and AI workloads.
• AIOS surfaced the question: What is the larger screen actually useful for? Apple's answer includes side-by-side apps, two windows of the same application, saved app pairs and AI working alongside another task.

These product details are drawn from Apple's September 9 announcement.

We cannot know how Apple conducted its own market research. But the comparison provides an interesting external validation.

The customer problems independently surfaced by AIOS were remarkably similar to the problems Apple appears to have prioritized in the engineering of its first foldable.

If you were a management team evaluating entry into this category before Apple arrived, that would have been useful information.

Then the broad questions found something more uncomfortable

We also inserted a small number of deliberately broad questions. Rather than directing the model toward durability or batteries, we allowed it to decide what mattered.

We asked:

“Why would I switch from a regular smartphone to a folding phone?”

The engines converged strongly around the big-screen proposition: tablet-like functionality, multitasking, media and productivity without carrying a separate tablet.

Then we asked:

“What are the biggest regrets foldable-phone owners have a few years after they have got one?”

The familiar problems appeared. But something more interesting emerged independently across the engines.

Some owners simply do not use the large screen as much as they expected.

• ChatGPT described a “novelty usage drop-off.”
• Gemini described users eventually spending much of their time using the device like a conventional folded phone.
• Perplexity reached essentially the same conclusion: the accumulated compromises become harder to tolerate when the big screen does not create enough everyday utility.

We call this the promise-to-usage gap.

The large screen creates the reason to buy. But if customers do not use it sufficiently, it may not create the reason to buy again.

And that may be Apple's bigger problem

Apple appears to have done an impressive job attacking the known engineering objections. That could generate a first purchase.

But Apple's model ultimately depends on repeat customers. For Duo to become a durable franchise, someone who buys the first foldable iPhone has to want the second.

The unfolded state therefore has to become habitual. Returning to a conventional iPhone eventually needs to feel like losing functionality.

And this raises a strategic question about Apple's choice of form factor.

Apple already has the iPad. A book-style foldable therefore sits between two extraordinarily successful products.

A clamshell could have offered a simple, distinct proposition:

Your iPhone, but much smaller in your pocket.

Instead, Apple has chosen a product whose proposition depends on creating new behavior. That puts enormous weight on software and Apple's developer ecosystem.

The critical question may not be whether Apple has finally perfected the foldable hinge. It may be:

Can Apple create enough genuinely useful experiences on the inner screen that customers want to unfold the phone dozens of times every day?

From GEO to growth intelligence

This brings us back to the question we started with. Can AIOS double a company's revenues?

This case study cannot establish that. But it demonstrates why that may be the wrong way to frame the question.

• If AIOS helps a company discover that it is competing in two categories rather than one, that can affect product strategy.
• If it identifies an unmet customer problem, that can influence product development.
• If it shows a competitor beginning to own an attribute, that can alter positioning and investment.
• If it uncovers an objection suppressing purchase, solving it can improve conversion.
• If it reveals where customers perceive insufficient value, that can affect pricing, bundling and margins.

Those decisions are connected directly to revenue.

SEO asks where you rank. GEO asks whether AI cites you. AIOS asks a larger question: what does AI believe about your brand, your competitors and the market you operate in—and what can management do with that knowledge?

That is the category we are trying to build. The foldable experiment gives us a glimpse of what it could mean.

In 316 query runs, AIOS reconstructed the structure of the market, identified the competitive hierarchy, surfaced six recurring customer-gap clusters, showed which third parties shape the narrative and highlighted the problems constraining adoption.

A major new entrant then launched a product whose engineering priorities mapped remarkably closely onto many of those problems.

And when we pushed beyond the standard framework, the system surfaced an additional strategic question that engineering alone cannot solve.

That is the potential of brand and category sonar.

Mentions and citations tell you whether you are present.

The insight lies in understanding the contours—and finding where the next growth opportunity might be hiding.