7 AI Trends To Follow In 2024

With advancements in technology, artificial intelligence has seen exponential growth, especially with the introduction of Generative AI. With various AI trends coming up, it is important to understand the most impactful AI trends that impact the future of AI.

Given below are 7 of the most important AI trends to follow in 2024:

Reality Check

Artificial intelligence created a lot of excitement when ChatGPT was introduced. Though it sparked tremendous imagination with individuals fearing the overpowering of machines, leading to job loss, a reality check was given as the dust of the excitement subsided.

In 2024, one AI trend to follow is having a reality check with a growing emphasis on grounding AI-powered solutions to ground reality and real-world applications rather than being aspirational.

The trend helps individuals move towards more realistic AI-powered solutions that deliver tangible benefits across various industries worldwide.

• Real-world Applications – Organizations are now focusing on AI use cases and applications that offer immediate value, like predictive maintenance or personalized recommendations.

• ROI-driven Approach – To have a more realistic approach, organizations are now analyzing the return on their artificial intelligence investments by critically evaluating the feasibility and impact of the project.

Multimodal AI

Generative AI trends or applications are not restricted to text generation. With technological advancement, AI-powered solutions have expanded their expertise to multiple modalities, such as image, audio, and visual.

With the growth of voice assistants, image recognition, and natural language processing, multimodal AI has become increasingly widespread.

The AI trend around multimodal AI includes systems with outstanding capabilities to understand various modalities like text, image, audio, and visual in an effective and efficient manner.

For example, Instagram uses multimodal AI to recommend personalized content based on user preferences by combining video, audio, and text analysis. 

• Enhanced User Experience – With the help of multimodal AI, there is a better understanding of natural language between humans and machines. As a result, it has led to the development of applications like virtual assistants and augmented reality that enhance user experience.
• Improved Understanding – Multimodal systems have the advantage of integrating data from various sources irrespective of their modality. As a result, a better and deeper understanding of the context is garnered, leading to more accurate predictions and insights.

Smaller Language Models and Open Source Advancements

Did you know that using AI also amounts to a massive use of energy? Every user query to an artificial intelligence model (like ChatGPT) adds to the planet’s energy consumption, leading to a potential energy and sustainability crisis.

As a result, there is an increasing need to develop smaller and more efficient language models that help in the sustainability of organizations. 

The shift towards this AI trend would lead to faster inference times, reduced computational costs, and greater accessibility through open-source initiatives.

• Efficiency – The performance of smaller language models is at par with that of their larger counterparts. Also, the smaller language models require fewer computational resources, making them more realistic and practical even in resource-constrained environments.
• Accessibility – With the help of open-source frameworks and pre-trained models, researchers and developers across the world are able to collaborate and innovate, owing to the democratization of AI development.

GPU Shortages and Cloud Costs

The next AI trend on our list of the 7 AI trends to follow in 2024 includes the challenges organizations might face to scale their AI projects efficiently.

This is because of the rising shortage of GPUs or Graphic Processing Units (which increased due to the increased demand for artificial intelligence) and the rising cost of cloud infrastructure.

Even though alternative solutions are present due to innovation in AI hardware, like Field-Programmable Gate Arrays (FPGAs) and Application-Specific Integrated Circuits (ASICs), the trend still holds considerable importance to look out for.

• Supply Chain Disruptions – Global supply chain disruptions have also aggravated GPU shortages, leading to significant challenges for AI training and development.
• Cost Optimization – To reduce the cost of cloud infrastructure, organizations are exploring various other options, such as resource pooling, workload optimization, and hybrid cloud deployments.

Model Optimization

Another AI trend to follow in 2024 includes the growing focus on optimizing AI models for improved efficiency, performance, and fairness.

This trend would involve reducing the model size and improving inference speed by using various techniques, such as pruning, quantization, and knowledge distillation.

• Efficiency – With the help of model optimization techniques, AI applications are able to run more efficiently on edge devices. This also results in reducing latency as well as energy consumption.
• Fairness and Bias Mitigation – Model optimization also leads to a fair AI system that helps to identify and eliminate biases in the AI model, leading to equitable outcomes across diverse populations.

Virtual Agents

Virtual agents have been present for a long period now in the form of ChatBots. With the introduction of GenAI in artificial intelligence, the scope of virtual agents has increased manifold.

Today, virtual agents that are powered by various AI technologies like natural language processing and conversational AI help organizations improve customer service, support, and sales interactions.

Virtual agents are used in various industries, from the healthcare sector to the hospitality industry, leading to streamlined operations and enhanced user experience.

• 24/7 Availability – With the implementation of virtual agents, organizations can provide their customers round-the-clock support, leading to improved customer satisfaction and reduced response times.
• Natural Language Understanding – Improvements in natural language processing allow virtual agents to understand and respond to user queries more accurately and contextually.

Regulation, Copyright and Ethical Concerns

With artificial intelligence’s increasing challenges, it is important to stay updated and examine the AI trend with respect to regulation, copyright, and ethical concerns.

According to Gartner’s top 10 strategic technological trends for 2024, the topmost spot is acquired by AI TRiSM (AI Trust, Risk and Security Management), emphasizing the importance of AI and AI regulations in the digital landscape of today.

With the rapid growth of AI technologies, there is growing scrutiny and regulation surrounding the ethical and legal impact that AI technology has on the world.

As a result, the AI trends in 2024 will focus on the need for more transparent, accountable, and ethical AI development and deployment practices.

• Regulatory Compliance – Many laws and guidelines are being established to govern AI development, usage and accountability by various governments and regulatory bodies. These include EU’s AI Act and the US Federal Trade Commission’s AI guidelines.
• Copyright and Intellectual Property – AI-generated content might involve issues related to copyright and intellectual property, especially if it contains artwork and music. Therefore, all AI-generated content requires careful consideration to avoid any complex legal or ethical issues.

Read Ethical considerations of Generative AI: Ethical Considerations of Generative AI in OCR.