5 Things Founders Must Know About the Future of Business in the AI Era

The exponential growth in interest in artificial intelligence that came with the introduction of ChatGPT in the past few years has brought the discussion of how it might affect businesses to the forefront.

The launch of several AI-powered features in everyday tools from tech giants like Google, Apple, Microsoft, and Amazon, who spent billions designing them, and the excitement that these create, is one of the many reasons for the sudden interest in AI, as captured by the surge in searches for the “AI” keyword on popular search engines.

In this article, we aim to introduce you to some of our predictions about the changes that we might witness as AI-powered processes become more acceptable and widespread.

We’ll talk about the likely outcome for businesses that refuse to adapt and point you to the very predictable successes of companies that have embraced AI to their advantage, starting with perhaps the most important of the five things you must know.

Only the Strong Will Survive

There is no better way to capture the scale of the shift currently happening with artificial intelligence and the level of impact it could have on industries than as succinctly as this very simple truth.

As we’ve seen with big tech giants who took an early lead in AI spending, investing in digital transformation as a small business entrepreneur will more than likely be the only reasonable way to survive the upcoming onslaught that widespread mainstream AI adoption will usher in for businesses that fail to adapt.

In fact, we are already seeing the kind of maladjustment in 2026.

The progression of AI. The first image shows a screenshot from ChatGPT in 2022.

The second announces that a yet-unreleased version of the program has just proven several decades-old problems in Math; Weeks after multiple AI companies, including the current frontier GPT model, proved several of their own.

With the increasing ability of the newer models, which seem to defy previous thresholds and thinking, there has been an increasing number of capabilities being unlocked for mainstream users, leading to saturation in the business landscape. At the moment, this is mostly only visible in the application publishing space, where the surge in app submissions is leading to slower and slower app growth, but this is a trend that is bound to spread across industries.

We recently reported on our blog about how Frontier AI Labs’ focus is shifting from generative AI models being mainly an automation tool to one that helps with discovery. In the article, we concluded that the new era of discovery incentivizes business disruption in ways unseen before and highlighted how Duolingo manages to use experimentation to fish for competitive business insights to continue to stay relevant.

With over ~95% of screen jobs projected to be affected over the coming decade as AI matures, according to Anthropic, it may be worthwhile to experiment with multiple different adaptation scenarios ahead of the coming difficult changes to the business landscape.

The Speed of Service Delivery Will Become More Important

 

“Through AI, computers have the ability to harness massive amounts of data and use their learned intelligence to make optimal decisions and discoveries in fractions of the time that it would take humans.” —Mike Thomas

 

One of the most common use cases for AI today is to quickly perform routine tasks that would otherwise have taken a lot of time. An example of this could be seen when the entire runtime of Bun was rewritten in Rust with Claude.

With the increasing introduction of artificial intelligence robots and processes that perform these tasks quicker and more efficiently than humans ever could, we’d argue it makes sense to believe that the general public will become increasingly less tolerant of a slow delivery cycle for products and services.

An illustration of this reality in 2026 is the pace of evolution of the models themselves. Since the introduction of large language models, the amount of time it takes for newer versions to arrive has shortened.

This is primarily due to how competitive the AI space has gotten recently, but it is also a picture of the appetite of model users.

Another example is how we saw the importance of the speed of service delivery that AI enables in the health industry during the pandemic, where it helped doctors to identify diseases more quickly and accurately and speed up drug discovery.

As a matter of fact, a specialised language model was just used to design bacteriophages in what is the world’s first of its kind.

Since the speed of service delivery is a strong factor in the feeling consumers associate with your brand as an entrepreneur, it would be wise to take advantage of AI to try and nurture this positive feeling.

All Industries Will Be Disrupted

One of the few insights emerging from the AI scene in 2026 is the prediction of an increasingly likely disruption to society from Anthropic we mentioned above.

AI lab founders such as Sam Altman have always alluded to this reality too, and this year, with the launch of it GPT -6 Astra model in September, netizens are starting to report an acceptance of the fact merely from how good models are getting.

But this wouldn’t stop, of course. Not with 3D artists, mathematicians, game developers, graphic designers, software developers, etc., thinking it would stop here is naive. This exponential increase in model power is coming for every possible industry! And as both folks inside the labs and the wider industry have predicted, the future will look more like a coalescence version of the present.

More on Industry Disruption

One thing we’re seeing as a bottleneck for growth today that we didn’t see three years ago is compute.

For founders whose business relies heavily on semiconductor products, it’s wise to plan today, regardless of your sentiment toward what’s happening in the tech ecosystem.

In a recent interview, Cerebras’ CEO, Andrew Feldman, speaking on the reason why the company’s share price has surged since its listing on NASDAQ, highlighted how strong and profitable compute capacity has become with the rise in AI usage.

According to Andrew’s observation, this new era of widespread use of artificial intelligence is leading to a large-scale workforce compute shortage.

Analyst already estimates that GPU “usage [will] concentrate in the hands of leading AGI companies (e.g., OpenAI, Anthropic, xAI) and the AGI-focused development efforts within larger tech companies (e.g., Google, Meta), the largest two or three of which will have a 15-20% share of the globally available AI compute by the end of 2027 (around 15-20M H100e).”

Although primarily a GPU and model training and inference problem, the forecasted shortage also affects storage device prices, which directly drives up cloud costs.

Data Gets More Important in 2027

 

“For artificial intelligence to be truly smart, it must respect human values, including privacy. If we get this wrong, the dangers are profound.” – Tim Cook

 

As the adoption of AI becomes widespread, companies and people alike are likely to place a premium on the importance of data.

This years we saw this play out in the recent controversy surrounding how OpenAI solved the Navier-Stokes equation.

Because data may become the only advantage founders have over competitors, and because consumers are becoming increasingly aware of how this data is being used, acquiring more data from customers in 2027 may become contentious.

As a result, it is therefore safe to say that the value of user data will very likely become exponential in the near future.

In conclusion, we believe that understanding and preparing for these changes we’ve identified are essential for entrepreneurs to continue to thrive in this new era of AI-powered solutions.

The likelihood that a business survives, let alone thrives, is now heavily dependent on how much more knowledgeable and prepared for the changes ahead its founders are.

 

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