How the artificial intelligence boom can bring the wave of business success

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Artificial Intelligence (Gen AI) is the buzzword of the year, capturing the global tech ecosystem. Top Sequoia of VC declare that generation AI can “create trillions of dollars in economic value,” and that thousands of businesses, from Microsoft to Fiat, have raced to integrate the technology as a way to accelerate productivity and deliver more value for customers.

Any nascent field like artificial intelligence, as is the case with Web3, also gives a lot of guesswork as to how big it can/will become. The global AI market is now valuable $136.6 billionwith some estimates that it will increase by 40% in the next eight years. Even the overall slowdown in VC trading makes an exception for Gen AI, with AI-powered startups. more than half of VC . investment in the last year.

However, while innovative AI tools are attracting the headlines and money of thrift venture funds, and while some pioneers have developed nifty AI tools that meet critical pain points, how many of these will become long-term businesses? Most of the people who have made money happen to be businesses rather than part of any long-term strategy, so what if/when they need to scale to meet demand?

There’s a lot more Gen AI startups still have to do to take this fascinating technology and truly turn it into a sustainable business. In this article, I will explain where innovative AI startups can start if they want to turn this short-term hype into long-term growth so they don’t miss out on a huge market opportunity. potential.


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Exaggeration Success

There are many barriers between Gen AI startups and long-term profitability.

First, it’s very difficult to take a new technology and actually turn it into something profitable. While Gen AI technology is certainly impressive, it don’t know how to make money or integrate it into a profitable business model. To date, some of the most successful AI startups have used the technology to increase operational efficiency — like, which automates repeatable processes that increase revenue and retention — or to help with language processing and content creation, like AI copywriting assistant But you can only have so many AI chatbots. Emerging-generation AI startups will have to carve out their own niches if they want to succeed.

It will also be difficult for AI companies to maintain a competitive edge. Many AI startups are struggling to differentiate themselves in an incredibly crowded market, and for every one entrepreneur with an innovative use case, another ten are riding the waves with no destination. – offer a “solution” without a clear idea of ​​the problem it seeks to solve. Had 130 Gen AI startups in Europe aloneand the chances for all of these companies to achieve long-term profitability are slim.

Ultimately, AI is still a nascent technology with big ethical questions, misinformation, and national security concerns to be answered. AI companies looking to streamline workflows will have to address concerns about third-party software’s access to potentially sensitive internal data before they can be widely adopted. widely, while startups leveraging the speed and efficiency of Gen AI must put in place enough safeguards to address outdated concerns that these “machines” could replace up to a quarter of our work.

Riding the wave of generalized AI: How to turn short-term hype into long-term growth

To address the above barriers, innovative AI startups that are serious about building long-term businesses need to adopt some fundamentals. It is true that the AI ​​market is particularly active with investor cash at the moment, but it is an outlier in the broader VC sentiment. With the recent market downturn, investors are more interested than ever to see examples of real, rather than projected, growth, and are scrutinizing whether their recipients get build on a scalable business platform.

Here are the key things Gen AI startups looking to turn hype into growth should consider:

  • Focus on customer needs: It’s easy to get caught up in the potential of Gen AI technology, but magic happens when that potential is applied in a way that clearly solves a problem customers already know and understand. Step one should always identify that problem, then work your way from there.
  • Plans for global scale: Most of the startups we’ve seen launching using Gen AI are pursuing product-driven development. They usually have a low monthly cost and serve an individual user. If these companies are serious about scaling, that requires being able to sell globally. More markets mean more buyers, more revenue, and faster growth. With more money in the bank, you can widen the runway and be better insulated from personal shocks and market volatility.
  • Build a thesis to make money: The automation provided by Gen AI can eliminate a lot of manual work, and pricing can be difficult to match due to the cost of the underlying infrastructure. What matters is your decision value Metric system, then test and tweak it to get the exact price. If customer needs are the beating heart of a business, then the point of making money is the means to keep that heart beating.

Ultimately, success will focus on two things:

  1. Earn money effectively:

No technology, regardless of the hype, will sell on its own, so it’s important to identify relevant Gen AI revenue streams and then package them in the right way to benefit. profit. Effective monetization will ultimately rely on three key pillars: increasing revenue, reducing costs (especially important given the lucrative nature of these businesses), and reducing risk. Ensuring a clear vision for these value levers is essential, as they will have a significant impact on the profitability of the companies that apply. Once you have all three, the money will follow.

  1. Overcoming potential barriers to growth and sustainable growth:

In the same way that AWS has increased the speed and cost of building a startup, ChatGPT enables complex operations automation with a human-like chat interface at the touch of a button. Since many AI startups are thin layers of applications built on deep but existing infrastructure, they can be brought to market very quickly through a freemium or low-cost model.

This is perfect for the self-service approach, where companies demonstrate the value of their products through use rather than sales-support pitches, which means those companies using wave AI will develop much faster than usual. However, it also means that they will encounter obstacles to internationalization sooner, forcing them to overcome operational barriers such as currency localization and payment methods and fraud handling. A comprehensive payments infrastructure is key to any successful Gen AI business, as this will enable the business to scale rapidly and grow.

The way forward

While Gen AI has the potential to create billions or even trillions of dollars in economic value, there are real questions about how many of these frontrunners will go on to create Big name businesses and how many people will eventually die out with the hype.

At Paddle, we’ve seen the growth curve of thousands of software businesses, tracking nearly $30 billion in ARR. And we’ve seen marked growth in the enterprise segment built on GPT and DALL-E 2 that generates AI for images.

When building on API Like this, the path to the product is very fast, so the real battleground becomes distribution and monetization. We’ve seen a significant increase in these businesses becoming global by default, selling through self-service to thousands of people across multiple markets at low prices. The companies that become successful are the ones that transfer as much value as possible into those first customer interactions.

Therefore, for aspiring Gen AI startups that want to create a truly global business, they need to focus on three things: defining a clear need or problem; plans to expand into new markets to get more revenue; build a monetization thesis and test and refine it to determine the right price.

While synthetic artificial intelligence may be new in technology, the principles underpinning its success are the same as for any software innovation. Master these core principles and Gen AI startups will be able to pave the way to long-term success.

Christian Owens is executive chairman and co-founder of paddlepayment infrastructure provider for SaaS businesses.

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