Top 7 AI Predictions and Trends for Business in 2024

Artificial intelligence has been a transformative force in 2023, and understanding AI trends became essential for every IT specialist or business owner. Just a few years ago, AI technologies were only available to companies with data scientists or machine learning engineers but now, everyone has access to AI tools.

With the rapid growth of the AI sector and various emerging technologies shaping the future of numerous industries, knowledge about predictions and the latest trends in AI is crucial for gaining a competitive advantage and staying ahead of the curve. Here are seven 2024 AI trends that will play an important role in various industries and our everyday lives.

Generative AI

Widespread usage of generative AI tools across numerous industries is one of the most prominent current trends in AI. There is no sign of generative AI becoming any less popular in the next few years. Today, millions of businesses and individuals use such tools as ChatGPT, Bard, GitHub Copilot, or DALL-E to manage their everyday tasks. These solutions leverage natural language processing (NLP) and offer impressive AI capabilities for automating tasks, boosting productivity, and reducing costs. It is still difficult to imagine generative AI replacing the majority of writers, software engineers, or designers, but AI-generated content has significantly impacted many professions and industries

According to Gartner, by 2026, 80% of companies will use APIs and generative AI models in their day-to-day operations, compared to 5% in 2023. The biggest generative AI trends we can expect in the next few years in this field are fully multilingual and multimodal AI systems that are able to generate text, images, and synthesized speech in real time. Also, with many IT companies currently working on their own generative AI solutions, we can expect fierce competition and constantly emerging advancements in this field.

Open-source AI

Without a doubt, one of the biggest trends in AI in 2024 will be the rise of open-source models. Compared to proprietary ChatGPT, open-source solutions will offer businesses and individuals numerous advantages that can’t be overlooked:

Open-source large language models (LLMs), such as LLaMA or Mistral, enable individuals, startups, and non-profit organizations to use AI-powered tools with impressive capabilities. Also, software developers, data engineers, and other IT professionals with different levels of experience and backgrounds have access to artificial intelligence, which leads to an increased speed in the adoption of AI.
Faster innovation. Open-source AI development benefits from a collaborative environment and community, sharing the latest insights about AI developmentbehind these tools. The collective effort from developers and users from all over the world leads to more rapid evolution, faster problem-solving, and increased agility.
With source code behind AI systems available for thorough review, companies and individuals can be sure that the tool’s developers uphold ethical and legal standards. Considering that bias behind machine learning algorithms and other ethical concerns are one of the most important AI trends today, it is an essential advantage.

While proprietary AI tools and LLM models are still very popular, their open-source counterparts are quickly gaining traction in the AI space. According to Forrester’s predictions, by 2025, 85% of companies will go with AI market trends and implement at least one open-source model.

AI coding tools and assistants

According to Gartner, by 2028 three out of four software developers will use at least one AI coding tool in their work, compared to one out of ten in 2023. Today, artificial intelligence can help coders with automating many routine tasks, such as code refactoring, debugging, or documentation generation, freeing up more time for creative tasks that require human involvement. Also, coding assistants offer great capabilities for improving the quality of code.

Future trends in coding AI include further incorporation of NLP capabilities for code analysis and generation, recommendation systems for coders that help to choose the best frameworks, libraries, and coding practices, and continued integration of AI in routine tasks. While AI coding tools are still far from replacing developers entirely, we will witness more and more efficient collaboration between human developers and artificial intelligence in the next few years. Software engineers and business leaders need to pay close attention to these tools that quickly become standard practice to avoid falling behind competitors.

Quantum AI

The implementation of quantum computing is one of the biggest AI technology trends. Today, artificial intelligence capabilities are often constrained by the limitations of traditional hardware. Quantum computers offer capabilities that are able to revolutionize not only AI space but also whole computer science. Currently, this technology is still available mostly for niche and experimental purposes, but with rapid development and significant investments in quantum computing, we can expect full-on quantum AI sooner than later.

With the ability to process vast amounts of data in milliseconds, artificial intelligence and machine learning algorithms will be able to handle tasks that are now out of their reach, such as more accurate climate change predictions, financial modeling and risk assessment, drug discovery, and advanced material design. The combination of AI and quantum computing will solve numerous problems that are deemed impossible for traditional hardware and revolutionize many industries, including logistics, energy management, finance, and healthcare.

AI legislation and ethics

Artificial intelligence’s rapid growth raised a lot of concerns about its transparency, security, privacy, and data quality. AI regulation has become a focus for many companies, industries, and whole countries. In the USA, over 190 AI-related bills were introduced in 2023. Twenty-eight nations signed the Bletchley Declaration during the first-ever global AI security summit in the UK, the European Union adopted the Artificial Intelligence Act, and many countries worked on strengthening their regulations. In 2024, we can expect more countries to join global regulations and the United States to pass the previously outlined AI Bill of Rights.

In addition to nationwide and global regulations, we have seen widespread adoption of the AI TRiSM (Trust, Risk, and Security Management) framework that comprehensively covers such areas as:

Helping organizations understand artificial intelligence and machine learning models to avoid issues and identify bias.
Providing ModelOps tools and processes for automating and monitoring the lifecycle of AI systems.
Safeguarding sensitive data used in training AI models.
Continuous tracking of systems’ performance for deviations and unintended outcomes. Analyzing input and output to help organizations identify data anomalies.
Assessing and managing risks while integrating third-party AI technologies and models.

TRiSM adoption and focus on advanced security measures will enable companies that use artificial intelligence in their operations to make more informed decisions and provide more accurate AI-generated content to their customers.

Small language models

Recent advancements in artificial intelligence are often connected to the evolution of large language models. Tools like ChatGPT contain more than 100 billion parameters and can be used for a wide variety of tasks, such as answering questions, generating texts, or summarizing documents. However, the massive size of LLMs often leads to limited customization, efficiency, and higher costs. This is the main reason for the emergence of small language models. These models are also trained on large datasets and can be used for the same tasks as LLMs but can better fit small niches due to smaller sizes and fewer parameters.

AI experts and data scientists still argue about what to consider small language models, with thresholds ranging from less than 100 million parameters to less than 1 million. However, everyone agrees on their significant advantages, including increased efficiency, lower costs, more customization options, and shorter training periods. While training LLMs can take days, many companies can train and fine-tune such solutions as virtual assistants or sentiment analyzers in several hours. In 2024, we can expect widespread adoption of SMLs as one of the main AI future trends in the finance, insurance, and entertainment industries.

New AI-related jobs

As artificial intelligence continues to play a more and more vital role in various aspects of our lives, from using image generators for fun to implementing supply chain management AI-powered solutions, new jobs connected to AI and machine learning are emerging. This change started at the C-suite level, with many Fortune 500 companies creating a new title called CAIO (Chief Artificial Intelligence Officer). This executive is in charge of staying on top of all the latest AI trends and developing the company’s AI strategy.

Experts in prompt engineering, data analysis, and machine learning operations are coming into high demand. New jobs expected to gain prominence in 2024 include:

AI ethicist. Responsible for the development and deployment of ethical and responsible AI systems, addressing issues of privacy, transparency, and bias.
AI human-computer interaction (HCI) designer. Designs user interfaces for AI applications to enhance user engagement and experience.
Input and output manager. Is in charge of input data used for training AI systems and interpreting output provided by these systems.
Regulatory specialist. Keeps up with the constantly evolving regulatory landscape and ensures that the company stays up to date with the latest regulations.

Also, one of the AI industry trends is AI upskilling. This process includes learning new skills and obtaining information about AI trends to improve employee performance and career prospects.

Conclusion

Artificial intelligence has been a center of attention for business leaders, IT professionals, and other individuals for the last couple of years. Now, it is obvious that AI and machine learning are essential for gaining competitive advantage and achieving success in the modern business landscape. Fully understanding current and future trends in the artificial intelligence landscape will enable you to avoid many issues and utilize AI tools and models to achieve great results.