AI Trends 2024: Summarizing the landscape of AI trends through 7 signs of change and new business opportunities
If 2023 was the beginning, 2024 is the year AI fully steps out of the lab and into the real world...
A decade ago, if you were told that AI would become a part of daily life, not just in the form of chatbots, but as a driver of a trillion-dollar economy, you might have considered it far-fetched. However, in 2024, those things have already happened.
AI is no longer confined to theoretical models in research labs; it has emerged as a critical force shaping business, technology, and everyday life. In 2023 alone, private sector investment in AI in the US reached 67.2 billion US dollars, or about 2.2 trillion Thai baht, which is 8.7 times more than China (according to https://aiindex.stanford.edu/report/). These figures reflect the growing confidence of businesses in AI’s potential to generate economic value on a massive scale.
Thus, 2024 marks a pivotal transition—from merely developing AI models to creating real-world AI products that drive tangible economic impact. AI is no longer just a tool for experimentation; it has become a cornerstone of innovation and a fundamental pillar of the global economy.
7 Signs That 2024 is the Transition to a New Era of AI
Sign 1: AI Companies Can Generate Real Revenue from Commercial Use
In 2024, the industry's focus has shifted from developing foundation models to using AI to create products and services for real-world use across a variety of industries. A clear example of this success is the growth of companies like OpenAI, which generated billions of dollars in revenue after launching ChatGPT and subsequently many other products such as DALL·E 3 for image creation, Sora for video creation, or the recently launched Deep Research feature, and many others.
Companies like OpenAI are currently valued at US$157 billion following their latest fundraising round in October 2024, making them one of the highest-valued private companies in the world. Reuters reported in January that SoftBank Group is in talks to lead a new funding round that could reach US$40 billion, potentially pushing OpenAI's valuation to US$300 billion if SoftBank successfully leads the new funding round.
In addition, many Generative AI Apps have become key tools in large organizations, such as:
- ElevenLabs: Dubbed the AI voice of choice for leading organizations, as 62% of Fortune 500 companies (the top 500 companies by revenue in the US) have at least one employee using ElevenLabs, clear evidence that ElevenLabs' Text-to-Speech (TTS) technology has been widely adopted at the enterprise level.
- Synthesia: AI video that is changing the way organizations communicate. Synthesia is trusted by most Fortune 100 companies, underscoring the potential of AI video to improve organizational efficiency, and is used in three main areas: employee training that helps reduce costs and increase efficiency, marketing and sales that help create product promotion videos quickly, and organizational communication that helps explain complex information in an easy-to-understand way, reducing communication errors.
It can be seen that in 2024, AI companies are no longer making money from developing models, but are starting to generate revenue from “real-world applications” in the business sector.
Sign 2: Growth Comes with Challenges
As AI is no longer just a technology confined to the research field, but has begun to play a role in every industry such as media, finance, education and politics, governments around the world have begun to introduce laws to control and regulate AI to prevent potential impacts on society. The European Union (EU) is among the first to try to introduce laws to strictly regulate AI. The most important example is the EU's AI Act.
However, the problem that arises is that technology companies such as OpenAI, Google and Microsoft are facing legal restrictions that may slow down AI development in Europe. Some companies have to choose to limit access to AI in Europe to avoid legal issues.
In addition, the problem of increasing AI resource demand also began in 2024. As AI becomes larger and more powerful, it comes with a tremendous increase in resource requirements, especially massive Compute Power, which increases the operating costs of AI companies, especially those developing large AI models.
To cope with the high costs, AI companies need to adapt in many ways to be able to operate sustainably. One of the key approaches is to downsize the model by reducing the size of the AI model while maintaining efficiency, which will reduce the demand for expensive computing or Compute power.
In addition, seeking new sources of funding is also necessary for AI companies that have increased costs in developing and using AI. Many companies are therefore looking for new sources of funding beyond Venture Capital (VC) funds, such as Sovereign Wealth Funds or investments from national wealth funds from countries such as the United Arab Emirates and Saudi Arabia, as well as partners such as large technology companies such as Microsoft and Google, which help AI companies access the resources and technology they need.
However, the fact that AI companies have to rely more on funding from abroad raises concerns about national security, especially if those funds come from countries that have a bad relationship with the United States.
A clear example is the case where OpenAI was pressured to reduce its stake in G42, a company from the United Arab Emirates (UAE), and receive investment from Microsoft, which reflects the concerns of the US government about AI companies having to rely on funding from abroad. There is also an example that Sam Altman of OpenAI tried to raise a huge amount of money to build a chip manufacturing plant to support the use of AI that requires a lot more Compute power resources.
Sign 3: NVIDIA Becomes the Most Influential Company in the AI World
NVIDIA has become a very influential company and has a market value of up to 3 trillion US dollars in June 2024 because the world of AI is driven by processing chips and NVIDIA is the most powerful and sought-after chip maker in the market.
It has a strong CUDA Ecosystem (Compute Unified Device Architecture), which allows developers to write AI programs to run on NVIDIA chips efficiently. CUDA has become a widespread standard, making it difficult for developers to switch to chips from other manufacturers.
Although NVIDIA dominates the AI chip market by about 80-90%, it has to face challenges from all sides, including major competitors like AMD and Intel that are trying to develop more cost-effective chips, including Big Tech, instead of relying on external suppliers, these technology companies are starting to invest heavily in designing their own AI chips, which not only reduces costs in the long run, but also opens up opportunities to customize chips to fit their specific needs perfectly, forcing NVIDIA to face competition from both other chipmakers and their own customers.
Sign 4: There is Competition Leading to Development and Expansion of Scope
2024 is the year that Proprietary AI models can no longer monopolize the market. From GPT-4 that once dominated the LLM market completely, now other models such as Claude 3.5 Sonnet, Gemini 1.5 and Grok 2 have been developed until the performance gap has narrowed significantly.
At the same time, Open Source models are gaining momentum, especially Llama 3 from Meta, which is popular among developers because it provides flexibility in controlling data and privacy. Fierce competition forces providers to reduce prices and increase the efficiency of AI models to maintain competitiveness. This is the end of the Proprietary AI market monopoly and opens up more choices for users, while competition drives innovation to better meet the needs of users.
In addition, in 2024, AI does not stop at creating text or images, but moves to thinking, analyzing and planning. Researchers are focusing on developing AI to solve problems and reason effectively. Reinforcement Learning allows AI to learn from experience and adjust its own strategies, while Self-Improvement algorithms allow AI to continuously develop itself without relying on humans much. Obvious examples are AI that can plan business strategies, control robots in new environments, or solve advanced math problems.
Sign 5: Sanctions fail to halt China's AI advancements.
Despite US sanctions, China continues to develop AI relentlessly, focusing on increasing processing efficiency, developing large Chinese language datasets, and expanding the use of AI in the industrial sector. The Chinese government is a major driving force, supporting both budgets and policies, such as pushing AI in manufacturing and medicine.
China is also accelerating the reduction of reliance on foreign technology by developing its own AI chips, such as Huawei's Ascend 910, which can compete with chips from NVIDIA. In addition, there are projects to develop national-level AI models such as WuDao 2.0 developed by the Beijing Academy of Artificial Intelligence, which has more parameters than previous versions and can support Chinese accurately.
Earlier in 2025, we saw one of the major advances, DeepSeek, a large language model developed by China itself to reduce reliance on Western models, which became a topic of conversation around the world and caused Nvidia's tech stock to plunge 17%, with a market cap of US$600 billion (about 20 billion baht) disappearing.
Sign 6: The AI Economy is a Golden Age Full of Opportunities
The AI economy is in a golden age full of opportunities, but it still has to prove itself. The value of AI-related companies has soared to nearly US$9 trillion, such as Nvidia with a market value of $3.313 Trillion, Microsoft with a market value of $3.051 Trillion, etc., which reflects investors' confidence that AI is the technology of the future.
Although the overall picture looks bright, the AI economy is still unbalanced. Investment remains concentrated in companies listed on the stock exchange rather than private AI companies, which may reflect investors' concerns that are still hesitant about the potential of small AI startups. Competition in this industry is also becoming increasingly fierce, forcing companies that want to survive in the long term to have both outstanding innovations and sustainable business models.
Companies that can generate real revenue from AI are mostly companies with infrastructure and models that are popular in the market, such as OpenAI (ChatGPT), Google (Gemini) and Anthropic (Claude), which are examples of companies that can turn AI development into a real money-making business. At the same time, applications that use AI to create video and audio such as Synthesia, ElevenLabs and RunwayML are starting to prove that there is a market ready to support this technology and can create real added value for businesses.
Overall, the AI industry is entering a major turning point. Companies that can create innovations, build a user base, and convert technology into sustainable revenue will be able to survive and grow in the long term, while companies that do not yet have a clear business model may face more challenges in the future.
Sign 7: Risks and Sustainability are Real Problems
Although many times people tend to view AI in a dystopian world as something that will cause disaster for humanity, as we enter 2024, the view of AI has changed significantly. Concerns about AI being a serious threat have decreased, but the real risks have not disappeared, but have become tangible problems that need to be addressed urgently in the present world, that is, problems of risk and sustainability.
The misuse of AI is one of the most worrying issues. Although AI is not yet able to create biological weapons on its own, it can accelerate the research and development process of these weapons to become more efficient exponentially. AI is also being used to create fake media in the form of Deepfakes, which can make images, sounds and videos so realistic that it is difficult to distinguish. This capability may be used to create fake news to manipulate the public, damage personal reputations, or even interfere in elections.
Cyber threats are another area where AI is being used in an undesirable way. Smart algorithms can develop increasingly sophisticated techniques for attacking computer systems. Another issue that is being talked about more is the environmental impact of AI. Because AI technology requires a huge amount of energy, especially in training large models such as GPT or Gemini. This level of data processing requires data centers that use a lot of electricity and leads to worrying amounts of carbon dioxide emissions.
Many technology companies are beginning to realize this problem and are trying to find ways to reduce the Carbon Footprint of AI, such as developing algorithms that use energy more efficiently, using renewable energy in data centers, and investing in technologies that help reduce environmental impact.
The current trend of AI development is still driven by the Silicon Valley Mentality that emphasizes speed and innovation, which may cause safety and ethical issues to be overlooked at times. There are many cases where companies launch new technologies without adequate risk prevention measures.
Therefore, it is important to have a comprehensive assessment of the impact of AI, both in terms of opportunities and risks, so that decisions about the development and use of AI are made carefully and are most beneficial to society.
References:
https://www.stateof.ai/2024-report-launch
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