2024 Prediction Compilation: 30 of Future Gazing Insights from CustomGPT.ai

As we start 2024, one of our favorite things is reading industry predictions. And there have been many to read. We’ve compiled the best ones we’ve come across, including our own insights at CustomGPT.ai, as well as insights from influencers, analysts, and experts in the field. After putting this compilation together, it’s even more evident to us how these technologies will change how businesses work, how we use technology, and how we live our daily lives!

1. Retrieval-augmented generation (RAG) in Data Governance: 

In 2024, expect a surge in the adoption of Retrieval-augmented generation (RAG) for data governance, as enterprises prioritize the reliability of Large Language Models (LLMs). This technique, which cross-references LLM outputs with verified external data, will become essential for ensuring AI data’s accuracy and context. 

Additionally, developers will integrate AI microservices like RAG into custom, off-the-shelf LLMs, optimizing AI-driven productivity with assistant algorithms and real-time data summarization tools, enhancing the trustworthiness and functionality of AI applications.

2. Real-time Data Becoming Standard for AI Applications: 

Real-time data is set to become the standard for AI applications as businesses prioritize its use to drive generative AI experiences. This emphasis on real-time data ensures that AI models operate with accuracy and contextually relevant information. 

The shift towards real-time data integration represents a crucial step in enhancing the effectiveness of AI applications across various industries, allowing for more timely and precise decision-making processes.

3. Shift from Model-centric to Data-centric AI: 

The AI landscape is shifting from a model-centric to a data-centric approach. This change prioritizes data quality in AI projects over just tuning AI models, leading to improved outputs and reduced inaccuracies. 

Organizations now emphasize a data-centric AI approach, aligning models with high-quality, real-time data for better generative and predictive performance. This emphasis on data quality arises from regulatory requirements and the need for precise datasets in AI model training and fine-tuning. 

4. Rise of Open Source LLMs: 

In 2024, the rise of Open Source Large Language Models (LLMs), exemplified by models like Llama 2, is set to outshine their closed counterparts. This shift is fueled by their increasing capabilities, with Gartner predicting that by 2026, over 80% of enterprises will incorporate generative AI APIs, models, and applications into their operations, a significant leap from less than 5% currently. 

Open-source LLMs offer accessibility and transparency as key advantages, although they also present challenges, including the potential for misuse and heightened security risks. Balancing these factors will be crucial as organizations navigate the evolving LLM landscape.

5. Increased Corporate Investment in AI: 

Enterprises are poised for a significant uptick in AI investment in 2024. Predictions suggest that organizations will reallocate a minimum of 10% of their budgets towards AI initiatives. This shift is primarily motivated by AI’s potential to enhance productivity and the growing concern of lagging behind in the innovation race. 

As AI continues to demonstrate its transformative power across industries, this increased corporate investment signifies a strategic move to harness the benefits of artificial intelligence and stay competitive in a rapidly evolving business landscape.

6. English as a New Programming Language: 

In 2025, a significant shift is underway as English emerges as the new programming language. Innovative programming co-pilots will interpret instructions in English, making coding more accessible. This transformation democratizes programming, breaking language barriers and revolutionizing technology interaction. As coding becomes inclusive and user-friendly, it fuels innovation and collaboration in the tech industry.

7. AI Coding: 

By 2028, AI coding will become standard practice, with 75% of enterprise software engineers relying on AI helpers for code creation. This shift signifies AI’s increasing role in streamlining software development, enhancing efficiency, and reducing coding time. 

Developers will leverage AI tools to automate repetitive coding tasks, enabling them to focus on higher-level aspects of software design and innovation. This transformation promises to reshape the software development landscape, making AI an indispensable ally for developers.

8. AI-Driven Surge in Human Productivity: 

In 2025, AI is projected to significantly boost human productivity, with Goldman Sachs forecasting an increase in global GDP and productivity growth driven by natural language processing advancements. McKinsey further predicts that by 2030, 30% of US work hours could be automated, particularly affecting customer service. 

AI’s role in automating administrative and project management tasks will allow humans to focus more on creative, intuitive, and empathetic endeavors, signaling a transformative shift in the workforce dynamics.

9. AI-Driven Startups Reshaping Entrepreneurship: 

The entrepreneurial landscape is witnessing a transformative shift with small, agile teams harnessing AI capabilities. These dynamic startups are deploying AI tools to drive rapid growth, enhance operational efficiency, and scale successfully. 

This emerging trend underlines a significant evolution in business models, showcasing how AI-driven ventures can achieve significant success and reach high valuations, all while operating with a minimal workforce. This shift is redefining traditional business norms and opening new pathways for lean startups in the AI era.

10. Edge AI for Real-time Inferencing and Data Privacy: 

Edge AI is on the rise, enabling real-time inferencing while safeguarding data privacy. This technology is gaining prevalence, permitting local data processing on devices. The benefits include reduced latency and enhanced privacy protection. 

Edge AI empowers devices to make decisions locally without relying on external servers, which can be especially valuable in scenarios where data security is paramount. As it becomes more widespread, Edge AI is poised to transform various industries by enabling faster and more secure inferencing.

11. Leveraging Unstructured Data

In 2024, businesses will increasingly utilize generative AI to analyze unstructured data like chats, videos, and code. This advanced approach will train multimodal models, enhancing the precision of responses and uncovering new opportunities across various industries. The focus is on harnessing diverse data forms for deeper insights and more targeted solutions.

12. Shift to Smaller, Enterprise and Private Language Models: 

Enterprises are increasingly adopting smaller, specialized AI models as an alternative to resource-intensive large language models (LLMs). This shift is motivated by cost-effectiveness and the availability of suitable hardware. Smaller, more focused AI models are becoming the preference in the enterprise landscape.

13. Data Protection and Compliance

In response to data security and compliance concerns, approximately 75% of global businesses are restricting the use of large language models (LLMs) like ChatGPT. This trend emphasizes the growing priority for enterprises to protect their proprietary data and adhere to legal standards, reflecting a significant shift in organizational approach to AI technology usage and data governance. 

14. AI Jobs: 

AI job trends are rapidly evolving. Professionals are engaging in AI upskilling to meet the growing demand. Emerging roles like AI Product Manager and AI Ethicist are gaining prominence. As organizations embrace AI, the demand for AI skills continues to soar, making it a promising field for those looking to future-proof their careers.

15. Shift from Research to ROI: 

Enterprises are increasingly favoring AI solutions with direct business applications over research-centric large language models (LLMs), seeking technologies that cater to specific use cases and yield tangible ROI. 

This shift is driven by the potential of AI to automate key financial tasks like market analysis and enhance customer support, streamlining operations and improving cost-effectiveness. This trend underscores a preference for practical, results-driven AI implementations in the business realm.

16. Enhanced Role of Human in the Loop (HITL): 

In 2024, there will be a profound appreciation for the pivotal role of humans in AI systems. The concept of Human in the Loop (HITL) will gain prominence as it becomes essential for the training, supervision, and ethical utilization of AI. This recognition underscores the critical involvement of humans in overseeing and guiding AI processes, ensuring responsible and beneficial AI outcomes across various domains and applications.

17. Integrating AI in Daily Technology: 

AI’s integration into daily technology is on the rise, extending its influence beyond the AI sector. It’s increasingly embedded in various platforms and devices, shaping broader technology trends. This pervasive integration allows AI to enhance user experiences, provide personalized services, and improve efficiency in everyday tech interactions. 

As AI continues to evolve, its seamless presence across diverse technological domains is reshaping how we interact with and benefit from digital technologies in our daily lives.

18. Augmented Working & BYOAI: 

In 2024, BYOAI (Bring Your Own Artificial Intelligence) will emerge as a prevalent workplace trend, driven by the accessibility of affordable AI tools and a growing demand for AI skills. Forrester reports that 60% of workers will use their personal AI tools for tasks, enhancing productivity and fostering innovation. 

However, this trend also introduces risks such as data privacy breaches and security concerns. The concept of Shadow AI, where AI is used without IT oversight, highlights the need for balanced governance to ensure that the benefits of BYOAI are realized while mitigating potential risks effectively..

19. Video-to-Text Summarization: 

Video-to-Text Summarization is set to gain popularity, simplifying the process of obtaining detailed summaries from lengthy videos, audio content, text-based articles, and papers. This transformative technology holds the potential to substantially reduce the time required to digest information. 

Users will benefit from concise and informative textual summaries that allow for efficient information absorption, catering to a growing demand for streamlined content consumption in various media formats.

20. Vector embeddings become a core enterprise data type: 

In 2024, Generative AI places vector embeddings at the core of enterprise data strategies. These embeddings capture complex data effectively. Enterprises prioritize them, boosting adoption of specialized vector databases. Both legacy and modern database systems integrate vectorization capabilities. This pivotal role enhances decision-making across industries, making data utilization more efficient and effective.

21. Rapid Enterprise Adoption of Generative AI: 

A recent study involving 672 executives revealed that 81% of enterprise companies now have dedicated internal generative AI teams, highlighting a growing reliance on AI for decision-making and operational efficiency. Smaller enterprises adopt AI more quickly. Generative AI gains momentum for productivity and innovation, integrating with corporate data for business growth.

22. AI Risk Hallucination Policy: 

With the increasing use of AI, concerns about hallucinations, false yet plausible outputs, emerge. The demand for AI risk hallucination insurance is expected to rise, addressing the potential consequences of such false AI-generated information.

23. AI TRiSM: 

By 2024, AI TRiSM (Trust, Risk, and Security Management) will be crucial for organizations employing AI, providing a comprehensive framework for managing AI risks, including explainability, ModelOps, data anomaly detection, and more. Gartner’s insights project that by 2026, companies utilizing AI TRiSM will enhance decision-making by eliminating 80% of inaccurate or fake data. 

The increasing reliance on AI across various sectors underscores the importance of AI TRiSM, ensuring the security, reliability, and ethical deployment of AI systems. This trend highlights a growing focus on robust risk management strategies in the rapidly evolving AI landscape.

24. Intelligent Apps & AI for Personalization: 

In 2024, the rise of intelligent apps, powered by AI, will mark a turning point in personalizing user experiences. Gartner’s report predicts that by 2026, one-third of all new apps will employ AI to craft personalized and adaptive user interfaces, a significant jump from the current 5%. 

This trend underscores AI’s growing role in enhancing digital interactions, ensuring that user interfaces are increasingly tailored to individual preferences and needs. The shift towards such AI-driven personalization is set to significantly boost user engagement and conversion rates, reflecting a new era of customized and responsive app experiences.

25. Transformation in Healthcare through Gen AI: 

In 2024, healthcare is undergoing a transformative shift powered by Gen AI. This revolution enhances patient handoffs, healthcare information sharing, and doctor-patient interactions, resulting in increased efficiency and improved clinical documentation and healthcare outcomes. Gen AI’s applications include managing patient cases, scheduling appointments, conducting surveys, and facilitating self-care routines, making healthcare more accessible and compassionate through advanced AI chatbots with RAG technology. 

26. AI-Powered Online Search: 

In 2024, AI-driven online search is undergoing a revolution. It offers personalized, contextual, and predictive experiences, but gaining user trust is challenging. Additionally, we anticipate the emergence of generative AI optimization, transforming content creation and search engine rankings. 

The shift from traditional link-based results to AI-powered, conversational formats is reshaping the search engine results page (SERP). This evolution in search optimization and user interaction is set to redefine the way we discover information online.

27. Consolidation of Data Platforms: 

In 2024, data leaders are focusing on consolidating data platforms. This strategic move aims to enhance team efficiency, simplify operations, and reduce the complexities linked to managing numerous tools. By streamlining data platforms, organizations are better positioned to harness their data resources effectively, driving improved decision-making and operational efficiency.

28. Generative AI Shopping Advisors in Retail: 

In the retail sector, a notable trend will be the introduction of AI-powered shopping advisors. These advisors will leverage Generative AI and will be trained on specific brand and product data. 

Their primary purpose is to enhance the shopping experience for customers by providing personalized recommendations, ultimately improving customer satisfaction and engagement.

29. Rise of Data Contracts: 

In 2024, the rise of data contracts is shaping the evolving relationship between business and data teams. These contracts assume a pivotal role by establishing clear expectations and fostering collaboration. 

They emphasize an integrated approach to data management, aligning business objectives with data strategies. This trend reflects a growing recognition of the importance of formalizing agreements and workflows around data to ensure its effective and responsible use within organizations.

30. AI-Driven Cybersecurity Defense: 

In the 2024 Gartner CIO and Technology Executive Survey, a notable 80% of CIOs revealed plans to significantly increase spending on cyber/information security, positioning it as the top technology investment category. This surge in investment aligns with the integration of AI-driven cybersecurity defenses. 

As cyber threats evolve, AI’s role in enhancing digital security is becoming crucial. AI-powered autonomous systems are being deployed to actively detect anomalies and predict potential breaches, thereby strengthening overall cybersecurity measures.

Conclusion

The year 2024 is poised to be a landmark year in the AI domain, signifying a deeper integration of AI in various facets of life and business. These advancements, from data governance enhancements to the evolution of AI in retail, indicate a future where AI’s role is central and transformative. However, this future also demands careful navigation to address challenges in data privacy, ethics, and governance. Ready to explore AI’s potential? Check out CustomGPT for tailored solutions and join the AI revolution today!