Let’s discuss whether a few companies, big tech or smaller startups, could come to dominate the AI Industry. But first, we will look at some AI statistics to illustrate the significance of Artificial Intelligence in the near future (and check out the source for more interesting artificial intelligence statistics).
- As of 2022, the global AI market is valued at over $136 billion
- AI industry value is projected to increase by over 13x over the next 8 years
- The US AI market is forecast to reach $299.64 billion by 2026
- The AI market is expanding at a CAGR of 38.1% between 2022 to 2030
- By 2025, as many as 97 million people will work in the AI space
- AI market size is expected to grow by at least 120% year-over-year
- 83% of companies claim that AI is a top priority in their business plans
- Netflix makes $1 billion annually from automated personalized recommendations
- 48% of businesses use some form of AI to utilize big data effectively
- 38% of medical providers use computers as part of their diagnosis
It is pretty clear that there’s no way around AI and this technology will impact every company as well as everyone’s lives.
So, let’s get back to the initial question of whether big tech companies or startups will shape this future.
We can currently see that the big tech companies won’t necessarily lead innovation as AI research laboratories such as OpenAI can come up with revolutionary ideas – ChatGPT is a good example. However, in that case, Microsoft’s involvement and investment also shows that smaller startups will have a difficult time to reach scale completely on their own.
Big tech companies such as Google, Meta, Amazon, Microsoft, and Apple have three major advantages:
They have invested heavily in cutting-edge research and development over the last years, and have built large teams of domain experts in the field. For example, Yann LeCun is Chief AI Scientist for Meta AI Research (FAIR) and one of the leading AI experts in the world. This in-house expertise makes those companies also much faster in commercializing new AI technologies.
Data & Computing Power
Another important factor is access to data and computing power. AI models require large amounts of data to train and improve, and access to large amounts of computing power is necessary to run and deploy these models. Big tech companies have access to vast amounts of data, as well as powerful computing resources, which gives them a significant advantage over smaller companies.
Big Tech has deep pockets and has been able to acquire many smaller companies and startups that are working in the space, which helped them to gain a significant advantage. They use the acquired companies to build new products and services, or to acquire new talent and technology. For example, Google acquired British AI research laboratory DeepMind to strengthen their own capabilities. Startups don’t have the financial resources to compete and have to completely rely on their new idea.
Those three factors have allowed big tech to quickly develop and improve their AI capabilities, and to gain a significant advantage over smaller companies.
However, it is also possible for smaller startups with disruptive ideas to come to dominate the AI industry. These companies may be more agile and able to innovate quickly, and they may also be more focused on specific areas of AI.
For example, a startup that develops a novel approach to a specific problem in AI, such as natural language processing, might attract the attention of larger companies and investors, or gain a large user base and grow quickly. Again, OpenAI with ChatGPT is a perfect example that startups can compete and build new innovative products and services. With the caveat that the resources of a large company are usually needed to really scale the idea (although, this problem could potentially be solved with enough venture capital).
Summarized, while large technology companies have a significant advantage in the AI industry due to their expertise, data & compute, and resources, there are still many opportunities for smaller companies and startups to make a big impact. In the end, the key to success in the AI industry is a combination of access to resources and expertise, a strong focus on user needs, and the ability to innovate and execute.