Ways to use AI to generate wealth in the next decade

Original article was published by B-cube.ai on Artificial Intelligence on Medium

Ways to use AI to generate wealth in the next decade

This exciting new industry is growing by more than 42% annually and will reach a market size of $733 billion by 2027. In the future, all services and products by the time they reach the consumer have at least once encountered artificial intelligence. The growth and viability of the industry are obvious to everyone. If something is so evident, why not exploit it today and plant the seeds of our future wealth? Here are 4 ways we can make more money in the 2020s using AI.

The industry potential

If we mention the year 2020, surely everyone will immediately associate it with a pandemic. A mass of Internet memes was made about how 2020 was not the most pleasant year for humanity. Of course, this negative mood did not develop for no reason. In addition to human loss and endangering our mental health, another notable category is the economic downturn. Entire industries shut down overnight.

Artificial intelligence is fully intertwined with digital life and services. That is why this market has not suffered a hard downturn due to the months of the pandemic. According to IDC, a highly prestigious global market research firm with decades of history, revenues from the AI ​​market will be around $156.6 billion in 2020, an increase of more than 12% compared to 2019. The study notes that while growth was still in double digits, it was slower than many had expected.

Artificial intelligence revenues are all projected to multiply over time. Emphasizing this fact is very important when trying to assess future business potential. There is no jump-like revenue growth or success stories in markets that are already in an anxious age. In this sense, let us also consider the market as the body of an organic organism. An old horse is less competitive than a young one. In this situation, let’s put the horse’s competitiveness in parallel with business opportunities. In a young market, it is always easier to make good decisions.

  1. Who are the biggest companies in the AI ​​industry and how can we benefit from their success?

Artificial intelligence goes hand in hand with large amounts of data. It follows that which company has more data is also ahead of AI.

Amazon, Google, Microsoft are all in fierce competition with each other for developers, who will use their cloud service to develop their newer models and algorithms.

Let’s see for ourselves the process as the industry grows. More users arrive, more services are born, and more products. To create these, at some point, you need to take advantage of an existing AI industry pillar service provided by a giant. Think about computing power, processing storage, chips. Many small companies will depend on the services of the big ones, thanks to which they will surely grow together with the industry in this field.

These giants are all publicly traded companies, we can buy their shares on the stock market. Thereafter, we can reap the rewards from dividend or stock price increases. Investing in giants is a possible way to increase our wealth. Indirectly with artificial intelligence.

The increase in profits in the industry may lead us to conclude that the shares of large players will also increase over time. By investing in and out of these, we can embrace and sit on the train of growth.

2. Startup

Not only giant companies exist in the market and surely they will not be the only ones to solve problems. At the corporate level, with thousands of employees, decision-making and direction of development can no longer be flexible. It is for this reason that there are many problems outside the periphery of large companies that need to be solved. But this is not a problem, on the contrary, an excellent opportunity. Small startups specialize in solving these problems. It’s worth mentioning here that most of these startups don’t look like “pure AI startups” but operate with artificial intelligence applied within some other industry.

These other industries could be for example healthcare, finance, insurance, and so on. Massachusetts startup PathAI uses machine learning to be able to produce more accurate cancer diagnosis.

With startups, we can also profit as an investor, but of course, we have to be capital-strong for this. Another possible way is to set up a startup ourselves to solve a similarly burning problem. To do this, we need to find a workable solution to a well-recognized problem and team up with professionals who know the right technology. The management can then decide on the fate of our startup company’s revenues.

Another option is to exit our small company. We sell our stake to a larger company or a capital-intensive entrepreneur.

3. AI trading bot

Another growth opportunity is the development of trading algorithms. This point also looks back a bit on the previous one. Data volumes are generated as a result of cryptocurrency price movements. Many are trying to develop algorithms that successfully predict market movements for this data. We can go this route on our own and try to develop such a robot ourselves. Or we can use a bot that someone has already developed. The multi-award-winning French fintech startup b-cube.ai itself specializes in the development of these AI crypto bots. By subscribing to one of them, we can integrate the bot into our own existing account at the exchange itself. With this, the robot will only get permission to buy and sell, eliminating the risk of any Ponzi scheme. Using the help of historical market movements and conclusions filtered from the sentiment of the participants, the AI engine forms predictive signals, with the aim of consistent returns in the long run. Although a 100% success rate is not possible, if the signal finds a target more than the breakeven point, we achieve nice results.

4. Contract work

Perhaps the easiest way is for us to have (or acquire) enough expertise ourselves and work for a company that wants to harness our knowledge. We see a breathtaking number if we go a little after the annual salary of a machine learning engineer. According to a study by Indeed, the average annual salary was $146,085 in 2018, an increase of more than 344% compared to 2015. This, of course, varies from country to country, this number will not be as high everywhere as in the United States, but we can agree that we will not have useless knowledge by getting expertise in ML.

Today, we don’t even have to work locally. The digital age has brought, and the pandemic has even made the mainstream consider remote or freelance work. All you need is a laptop and you can carry it from anywhere.

However, it is true for the ways of making money mentioned above that they are exclusive to some degree. For each version, we have to have something that unfortunately the majority of the population does not have. Be it capital, expertise, programming knowledge. On the other hand, if we have one or even more of these, artificial intelligence can hold for us opportunities like the Internet has meant to the brave dreamers of the time a few decades ago.

Don’t miss it!


The information provided on this website does not constitute investment advice, financial advice, trading advice, or any other sort of advice and you should not treat any of the article’s content as such. The author, website or the company associated with them does not recommend that any cryptocurrency should be bought, sold, or held by you. Do conduct your own due diligence and consult your financial advisor before making any investment decisions.