AI is increasingly reshaping the way we live and work. In 2024, technological advances will continue to impact all spheres of life, changing the world of software development, business patterns, and consumer habits. It will also keep raising questions about authenticity and calls for regulation.
In this article, we explore key AI trends that are poised to redefine the technological landscape in 2024 based on the research conducted by three companies: Forrester, Gartner, and Bullhound.
AI trends 2024, according to Forrester
Forrester is a research and advisory company that publishes predictions on future technology trends every year.
Generative AI will seep into consumers’ lives
Generative AI, exemplified by models like GPT, is expected to permeate everyday consumer experiences. As these AI systems become more advanced, they will likely play a significant role in content creation, virtual assistants, and personalized user experiences. From generating realistic text to aiding in creative tasks, generative AI is poised to enhance and influence various aspects of consumers’ digital interactions, making it an integral part of daily life. Even users that are skeptical about generative AI today are expected to adopt this technology.
AI will spur the age of creativity
The continued development of AI, especially generative models, is anticipated to usher in a new era of creativity. With the ability to generate content, ideas, and artworks, AI is set to collaborate with human creators, offering novel insights and innovative solutions across various industries.
This synergy between human creativity and AI capabilities could lead to groundbreaking developments in fields like art, design, literature, and problem-solving.
Agencies will bet big on “brand-specific” AI models
Organizations and agencies are likely to invest significantly in developing AI models tailored to their specific brand needs. These brand-specific AI models could be designed for tasks such as customer engagement, marketing strategies, and product customization. The trend reflects a growing recognition of the potential for AI to not only optimize internal processes but also to create unique and distinctive brand experiences for consumers.
AI processing will hit a wall in 2024
Anticipation of a potential limitation in AI processing capabilities suggests that the current trajectory of computational power may face challenges in 2024. This could be due to physical constraints, diminishing returns on traditional computing architectures, or increased demands for energy-efficient AI solutions. Overcoming this “wall” may require innovations in hardware design, new computing paradigms, or breakthroughs in algorithmic efficiency.
Prompt engineering services in cloud-based AI development may fail
The deployment of prompt engineering services by cloud providers may not yield the expected results. Despite efforts to streamline and enhance AI model training through prompt engineering, challenges such as ethical concerns, bias mitigation, and interpretability may persist. This trend suggests that while cloud services aim to simplify AI development, certain complex issues may remain unresolved, necessitating continued research and development.
GenAI will augment customer service agents’ capabilities
Generative AI is expected to augment the capabilities of customer service agents. By assisting in handling routine inquiries, automating responses, and providing contextual information, GenAI can enhance the efficiency and effectiveness of customer support operations. This trend reflects a broader movement toward integrating AI technologies to improve customer experiences and streamline business processes.
Regulators will have GenAI in their sights
As generative AI becomes more prevalent, regulators are likely to focus on establishing guidelines and frameworks to address potential risks and ethical considerations. Concerns related to misinformation, deep fakes, and privacy issues may prompt regulatory bodies to scrutinize the development and deployment of generative AI technologies. This trend emphasizes the growing importance of responsible AI practices and the need for regulatory oversight in the face of evolving AI.
AI trends, according to Gartner
Gartner is a consulting firm from the USA, focusing on technology and business research.
Focus on AI security management (AI TRiSM)
AI TRiSM refers to the growing emphasis on managing trust, risk, and security in AI systems. As artificial intelligence becomes more integral to various domains, there is a heightened awareness of the need to establish trust in AI models, mitigate potential risks, and ensure robust security measures. This trend underscores the importance of ethical AI practices, transparency, and comprehensive risk assessment frameworks to build confidence in the deployment of AI technologies across industries.
AI-augmented development involves the integration of artificial intelligence tools and techniques into the software development process. This trend signifies a shift toward leveraging AI to enhance and automate various aspects of the development life cycle. From automating coding tasks to aiding in testing and debugging, AI-augmented development aims to increase efficiency, reduce errors, and accelerate the pace of software innovation, reflecting a broader movement towards more intelligent and automated software engineering practices.
Democratization of generative AI
The democratization of generative AI involves making advanced AI capabilities, particularly in generative models, accessible to a broader audience beyond experts and researchers. This trend is characterized by the development of user-friendly tools and platforms that enable individuals with varying levels of expertise to create and utilize generative AI applications. Democratized generative AI fosters creativity and innovation by empowering a wider range of users, including artists, writers, and content creators, to harness the creative potential of AI without extensive technical knowledge.
Rise of machine customers
The concept of “machine customers” refers to the growing use of AI systems as customers or clients. In this trend, AI technologies are employed as sophisticated consumers of products and services. For example, in business scenarios, AI-driven systems may interact with other AI systems or traditional services, making decisions, negotiating terms, and optimizing processes. This reflects a shift in how businesses and industries conceptualize and cater to AI entities as active participants in economic transactions and decision-making processes.
AI trends, according to Bullhound
Bullhound is a boutique investment company that has been doing market research since 1999.
Reduction in size of large language models
The trend of shrinking large language models signifies a shift towards more efficient and compact AI architectures. As researchers and engineers focus on developing smaller yet powerful language models, this trend disrupts the AI market by addressing concerns related to computational resources, energy consumption, and deployment in resource-constrained environments. Smaller language models are not only more sustainable but also pave the way for broader accessibility and integration of AI technologies across various applications and industries.
Emphasis on authenticity as creators challenge AI
As AI technologies, including generative models, become more adept at producing content, creators are increasingly emphasizing authenticity to distinguish human-generated content from AI-generated content. This trend reflects a growing awareness of the potential for misinformation and deep fakes, prompting creators to focus on unique, human-driven narratives and expressions. In challenging AI’s ability to replicate authentic human creativity, creators play a pivotal role in shaping narratives that resonate with genuine experiences and emotions.
Reshaped media landscape
The impact of AI on the media industry is characterized by the personalized delivery of content and strategic acquisitions. AI algorithms analyze user preferences, behaviors, and data to tailor content recommendations, creating a more personalized and engaging media experience. Additionally, media companies are leveraging AI for targeted acquisitions, using data-driven insights to identify valuable content. This trend underscores the transformative role of AI in shaping the media landscape and enhancing content delivery to cater to individual preferences.
Increasing semiconductor shortage
The intensification of the AI race contributes to the global semiconductor shortage, as the demand for high-performance chips for AI applications increases. As companies and industries invest heavily in AI development, there is a growing strain on the semiconductor supply chain, impacting the availability of key components for various electronic devices. This trend highlights the interconnectedness of the AI and semiconductor industries and emphasizes the need for strategic planning and innovation to address challenges in the production and supply of essential hardware for AI systems.
The technological landscape is on the brink of unprecedented transformation. The integration of AI into our daily lives is inevitable, and being well-informed about these trends is key to harnessing the opportunities and navigating the challenges that lie ahead.
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