In this article, we look at the 15 AI Developments/Trends of 2024. We have also discussed the latest trends and developments in artificial intelligence (AI). If you want to skip our detailed analysis, head straight to the 5 AI Trends of 2024.
The Booming AI Market and its Impact
According to a report by Markets and Markets, the Artificial Intelligence (AI) market is valued at $214.6 billion in 2024 and is expected to reach $1.33 trillion by 2030, reflecting a remarkable CAGR of 35.7%. This growth is fueled by advancements in computational power and data which enables more sophisticated AI algorithms. Governments, particularly in regions such as Asia Pacific, are investing heavily in AI research and development. Additionally, the widespread digital transformation across industries such as healthcare, finance, manufacturing, and retail is driving the demand for AI solutions to improve efficiency, decision-making, and customer experiences. Businesses are increasingly adopting AI to gain a competitive edge through automation and personalized services, which further accelerates market growth.
AI has the potential to significantly boost global productivity. According to PwC’s Global AI Study, AI could add $15.7 trillion to the global economy by 2030, with $6.6 trillion from productivity gains, while AI in manufacturing is expected to grow from $1.1 billion in 2020 to $16.7 billion by 2026.
However, achieving this requires strategic investments in various AI technologies. Initially, AI will drive GDP growth by enhancing labor productivity, as businesses use AI to augment their workforce and automate tasks. By 2030, 45% of economic gains are expected to come from product enhancements, as AI increases product variety, personalization, and affordability, stimulating consumer demand. The largest economic benefits will be seen in China, with a 26% GDP boost, and North America, with a 14.5% boost, together accounting for nearly 70% of the $10.7 trillion global economic impact.
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AI Boom and Strategic Investments
Over the past year, generative AI has seen remarkable advancements, with technologies like ChatGPT, Midjourney, and Bard gaining widespread recognition. Major corporations have made significant investments in AI startups, including Microsoft’s $10 billion investment in OpenAI and Amazon’s $4 billion in Anthropic. In parallel, policymakers have taken AI regulation more seriously, with the European Union introducing comprehensive policies and the Biden Administration issuing an Executive Order with 150 mandates for federal agencies.
NVIDIA (NASDAQ:NVDA) plays a pivotal role in the advancement of AI due to its powerful graphics processing units (GPUs), which are essential for training and running AI models. The company is investing heavily in AI software platforms, such as its CUDA programming model, to accelerate AI development. NVIDIA’s (NASDAQ:NVDA) GPUs such as the A100 and H100 Tensor Core GPU are at the forefront of AI and machine learning.
In the fiscal year 2024, NVIDIA’s (NASDAQ:NVDA) revenue increased 53% year over year to $31.7 billion. The company’s net income increased to $15.4 billion, up from $8.3 billion in the previous year. The increasing adoption of AI across various industries positions NVIDIA (NASDAQ:NVDA) to significantly benefit from market growth. In 2024, the company is making a $8.68 billion investment in R&D, an 18.2% increase from the previous year’s $7.34 billion. Over the past five years, the company’s R&D spending has surged by 73%, reflecting its dedication to maintaining its dominant position in the AI chip market, where it holds an 80% market share. This increased investment is part of the company’s strategy to enhance its technological capabilities and create new products to meet the growing demand for AI applications.
As the AI market continues to grow, its transformative power will reshape industries and boost global economies. By 2030, AI is poised to play a central role in global economic growth AI solutions will drive productivity, enhance product offerings, and provide businesses with competitive advantages through automation and personalization.
While we acknowledge the potential of NVDA as an investment, our conviction lies in the belief that some AI stocks hold greater promise for delivering higher returns and doing so within a shorter time frame. If you are looking for an AI stock that is more promising than NVDA but that trades at less than 5 times its earnings, check out our report about the cheapest AI stock.
Now let’s take a look at the list of 15 AI developments/trends of 2024.
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Our Methodology
For this article, we sifted through internet rankings and computer and science journals to find the latest developments/trends in artificial intelligence in 2024 and then compiled a list in no definitive order. Here is the list of 15 AI developments/trends of 2024.
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15 AI Developments/Trends of 2024
15. AI as a General Purpose Technology
AI is rapidly transforming various sectors, including education, where personalized learning platforms and immersive experiences through VR are becoming more prevalent. In scientific discovery, AI is accelerating breakthroughs in areas like drug development and weather prediction. The technology’s potential to revolutionize fields such as healthcare, where AI tailors treatments based on genetic data, is growing. AI is also enhancing creativity, human interaction, and efficiency across industries such as retail and manufacturing. As a general-purpose technology, AI’s applications are expanding, making it increasingly integrated and impactful across multiple domains.
14. Expansion of Virtual Agents
In 2024, companies like Google and OpenAI are developing easy-to-use platforms that let organization build their own custom chatbots without needing to code. These chatbots provide virtual customer support services and are becoming much more advanced. Moving beyond simple customer service roles these chatbots can perform tasks such as reservations, manage schedules, and work with other services. With better natural language skills, these chatbots can talk more naturally with users and offer personalized help, making them more effective. As businesses use these virtual agents, they save time and money, letting employees focus on bigger, creative tasks.
13. Rising Demand for Electricity
The rising demand for electricity is being heavily influenced by the growth of AI and data centers. Goldman Sachs forecasts that electricity usage by data centers could increase by 160% by 2030, with AI playing a key role. The demand of electricity for data centers in the United States is expected to reach 8% of total electricity demand by 2026, up from 3% in 2022. Current AI models, such as those used in generative AI applications, consume large amounts of energy, ChatGPT uses over 500,000 kWh per day. As AI models become more widespread, the expansion of data centers is expected to double energy consumption over the next decade.
12. Advancements Amid Rising Costs
The cost of AI development and deployment is rising as AI systems become more complex and demand for advanced solutions like machine learning and natural language processing increases. The costs of specialized hardware, such as GPUs needed for training AI models, remain substantial, the cost of NVIDIA’s AI products, especially their top GPUs, has significantly increased. For example, their H100 AI GPUs are priced up to four times higher than AMD’s competing MI300X chips. The average salaries for AI engineers in the U.S. have also increased due to higher demand. As companies scale their AI projects, ongoing expenses for training models, maintaining infrastructure and ensuring regulatory compliance continue to grow.
11. Continuance of Shadow AI
The phenomenon of shadow AI, where employees use AI tools without official approval or oversight, continues to be a significant concern in 2024. Studies indicate that a large proportion of workers employ AI applications in their daily tasks, often without adherence to their corporate policies. The unregulated use of AI can lead to legal complications and the use of copyrighted materials. To mitigate these risks, organizations are increasingly recognizing the need to develop and enforce comprehensive AI usage policies, provide training, and implement monitoring systems to ensure responsible AI practices.
10. Surge in AI Investments
Despite rising costs, investment in generative AI has surged, according to Goldman Sachs Economics Research, investments in AI are expected to reach nearly $200 billion globally by 2025. While the U.S. is expected to lead in AI adoption, other countries like China may experience slower growth in AI-related investments. Over time, AI investment could account for a significant portion of GDP, with long-term projections ranging from 2.5% to 4% in the U.S. Major players such as OpenAI, Anthropic, Hugging Face, and Inflection have secured significant funding rounds which also reflects continued optimism in AI’s potential.
9. Demand for AI Professionals
The demand for skilled AI professionals is set to rise significantly in 2024 and beyond. Non-tech companies are increasingly recognizing the value of AI in optimizing operations and enhancing customer experiences, driving them to recruit talent such as data scientists, machine learning engineers, and AI developers. This growing need, not only within the tech sector but across various industries, is making expertise in AI an essential asset for businesses worldwide.
8. AI as an Enhancement Tool
In 2024, AI is being seamlessly woven into widely used software to provide practical improvements that enhance productivity and user experience. For example, Microsoft’s Copilot features within Office suites allow users to leverage AI for smarter document creation, data analysis, and task automation by reducing manual work. Similarly, Adobe Photoshop’s generative fill capability uses AI to help users effortlessly edit and create images with precision, saving time while expanding creative possibilities. This integration marks a significant development in how AI can be used as a tool for driving innovation and efficiency in everyday tasks.
7. Rise in Local Custom Models
The trend toward developing custom local AI models is gaining momentum in 2024. Organizations are using open-source AI models to create tailored solutions trained on proprietary data and optimize it according to their operational requirements. This approach empowers businesses to implement AI solutions that align closely with their specific contexts and compliance needs, while mitigating risks with data exposure and external dependencies. The rise of custom local models underscores a shift towards more decentralized AI development.
6. The Evolution of Multimodal AI
A multimodal AI is an advanced type of AI that can process and analyze different types of data, including text, images, audio, and video. Unlike traditional language models that focus only on text, the capabilities of multimodal models can offer more human-like interactions by combining multiple senses.
For example, Microsoft’s Copilot can now analyze an uploaded image alongside natural language and search data to provide valuable insights. Similarly, creative platforms such as Microsoft Designer allow users to generate images from text descriptions. These advancements in multimodal AI are one of the major developments in AI in 2024 and will lead to enhanced creative tools that adapt to a user’s needs with greater accuracy.
5. Rising GPU and Cloud Costs
The growing demand for AI services is contributing to increased costs associated with GPU hardware and cloud computing resources in 2024. Training and running Large Language Models (LLM) require substantial computational power which lead to heightened competition for GPUs and is driving up prices for cloud infrastructure. As a result, there is a rise in Small Language Models (SLMs) that focus on improving the efficiency of AI workflows and infrastructure.
4. Rise in Small Language Models (SLMs)
In response to the high computational and energy demands of large-scale AI models, in 2024, the focus is shifting towards Small Language Models (SLMs) which despite being smaller than their Large Language Models (LLM), are becoming increasingly powerful. SLMs that can operate efficiently even on a smartphone offline, are much more cost-effective and accessible, making them a significant trend in AI. Microsoft researchers have been at the forefront of this movement, developing models such as Phi and Orca, which challenge the notion that only large models can deliver high performance.
3. AI Video Generation
While generative models that produce photorealistic images became mainstream in 2023, the focus is now shifting towards video tools like Runway’s Gen-2 model which produces short and high-quality video clips that can rival professional animation studios. AI video generation is emerging as a groundbreaking development in 2024, enabling the creation of high-quality, dynamic video content from simple text prompts or data inputs. Major film studios, such as Paramount and Disney are exploring the use of generative AI throughout their production processes, particularly in lip-syncing, foreign-language overdubs and enhancing special effects. Additionally, deepfake technology which creates fake images, videos, or audio clips that look real is gaining traction, and companies such as Synthesia is providing tools that generate realistic avatars.
2. Increased AI Regulation
There are growing efforts by governments and regulatory bodies all around the world, to address AI risks through regulations. On August 1, the European Union entered the Artificial Intelligence Act into force, which aims to establish standards for AI safety, transparency, and accountability. The Act will be effective from August 2026. In the U.S., Blueprint for an AI Bill of Rights by the White House Office of Science and Technology was released and aims to guide the responsible design, use, and deployment of artificial intelligence (AI) systems. Concerns about intellectual property regarding generative AI, are raising questions about content ownership. There is also an increasing call for transparency in AI development, particularly in disclosing training data and methodologies. AI regulation is one of the most significant trends in 2024, governments and regulatory bodies worldwide are establishing frameworks to ensure AI systems are safe, transparent, and accountable.
1. Revolutionizing Robotics
Roboticists are developing more versatile robots that are capable of performing a wide range of tasks. Unlike traditional AI models, which are designed for specific functions, new models like DeepMind’s Robocat and RT-X are being trained to handle multiple tasks using a single, general-purpose model.
This approach has revolutionized robotics by enabling them to learn new tasks through trial and error, generating their own training data as they go. The paper Advancing Humanoid Locomotion: Mastering Challenging Terrains with Denoising World Model Learning published by Xinyang Gu and Yen-Jen Wang, discusses advancements in humanoid robot locomotion control, focusing on a new method called Denoising World Model Learning (DWL).
DWL improves the robot’s learning and adaptation capabilities to make it better equipped to utilize its mechanical freedom effectively. For example, DWL can help a robot learn how to use its ankle control to handle various terrains more effectively by better simulating real-world challenges. As AI continues to evolve, DWL will push the boundaries in robotic control and generalizable learning, marking a notable development in AI development.
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Disclosure. None. This article was originally published on Insider Monkey.
