AIM Research, through meticulous research and expert surveys, has identified the top trends in Data Science and AI that are poised to dominate in 2024.
AIM’s comprehensive approach involved initial shortlisting of 20 trends based on secondary research conducted by AIM Research and Editorial teams. This was followed by a survey of global Chief Data Officers (CDOs) and Heads of Analytics, who rated these trends based on their likelihood of gaining popularity in 2024. The results are categorized into ‘Emerging Interests’, ‘Growing Momentum’, and ‘Peak Popularity’, offering a nuanced understanding of each trend’s current status and future potential.
The Trends
1. Rapid Expansion of Workforce Automation
- The global AI market, key in driving workforce automation, is valued at $145.6 billion and expected to reach $302.84 billion by 2027, growing at a CAGR of 26.7%. This trend is revolutionizing job roles across industries, necessitating the adoption of more efficient and less repetitive workflows.
2. Surge in AI Training Initiatives
- With workforce automation on the rise, AI training initiatives within companies are surging to address the skill gap. Organizations are investing heavily in upskilling their employees to keep pace with the evolving technology landscape.
3. Increasing Reliance on LLM in Data Storytelling
- Approximately 54% of data and analytics professionals currently use tools like ChatGPT and Bard, with reliance on Large Language Models (LLMs) for data storytelling expected to rise to 75% by 2025. This trend highlights the growing importance of narrative techniques in data analysis.
4. Data Privacy, Security, and Responsible AI Practices
- As AI becomes more prevalent, implementing robust data privacy, security measures, and responsible AI practices are emerging as key differentiators for enterprises. These measures are vital in preventing reputational damage and operational disruptions.
5. New Revenue Streams for Cloud Providers in Generative AI
- Cloud providers and big tech companies are tapping into generative AI for new revenue streams. With the generative AI-driven revenue for cloud providers expected to grow by 30%, this trend is reshaping the cloud computing landscape.
6. Emergence of Specialized GenAI Roles
- The first half of 2023 saw a 39% month-on-month growth rate in GenAI jobs. This trend is expected to continue, with a 30% growth in generative AI jobs predicted for 2024, indicating a rapid evolution of job roles in this domain.
7. Impact of AI on Traditional Software Development
- AI assistants like Copilots are transforming traditional software development, enhancing productivity by approximately 30%. This trend is significantly reducing errors and streamlining the development process.
8. Technical Evolution of Data Professional Roles
- With the increasing centrality of AI, 41% of data professionals are already adapting to new workplace demands. The next decade will see a significant upskilling requirement, with 68% of current data professionals needing to enhance their technical skills.
9. Rise of Prompt Engineering
- Prompt engineering is becoming an essential skill in various job roles. Our study reveals that 33% of professionals in data analytics are already utilizing prompt engineering, with an additional 27% expected to adopt it for routine tasks by the end of next year.
10. Prominence of Multimodal LLMs
- Moving beyond text, multimodal Large Language Models that can understand images, videos, and audio are gaining prominence. The global NLP market, central to training these LLMs, is projected to grow at a CAGR of approximately 34% from USD 17 billion in 2022 to 40 billion by 2025.
Conclusion
The Data Science and AI landscape in 2024 is set to be dynamic, with emerging technologies reshaping traditional roles and creating new opportunities. Enterprises that stay ahead of these trends will be well-positioned to leverage the full potential of AI and Data Science in the rapidly evolving digital economy. As these trends gain momentum, they will play a crucial role in shaping the future of business and technology.
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