AI 2024: 10 Predictions

As we look towards the future of artificial intelligence, several key trends are shaping the landscape for 2024. These developments span various aspects of AI technology and its application, reflecting both the rapid advancement and the evolving challenges in the field.

Let’s delve into some of these significant predictions for the coming year:

Closed vs. Open Models: Closed models like GPT-4 will still outperform open-source models, but will become increasingly comparable. An example: Mistral AI is Releasing an Open-Source GPT-4 Level Model in 2024
Small Language Models (SLMs): A shift towards smaller, high-quality source trained models like Microsoft’s PHI-2 and Mistral 7B. These SLMs fit perfectly in the MoE approach.
Note that Microsoft’s efforts on embracing Open Source (see PHI-2) underlines the friction in Microsoft/OpenAI Alliance which might further augment.
Evolving AI Terminology: Terms like “large language model” becoming less common because of Multimodal AI Models: AI models will combine data like images, text, and audio. Key examples are OpenAI’s GPT4 and Meta’s Llama 2.
Agentic AI: Shifts from reactive to proactive AI with AI agents exhibiting autonomy and independent goal-setting, as an example see AutoGen.
New AI Architectures: Emerging AI Architectures like Mamba Expanding the Horizons of Possibility.
Quantum AI emerging: the marriage of quantum computing and AI, known as quantum AI, is a rapidly emerging field that opens up vast possibilities.
AI TriSM will gain in importance as organizations adopt more AI. AI TriSM stands for Artificial Intelligence Trust, Risk, and Security Management. It is a framework that helps organizations manage the risks of developing and deploying AI models. According to insights by Gartner, by 2026, companies that use AI TRiSM to manage their AI systems will make better decisions by removing 80% of inaccurate or fake data. Such frameworks will be needed to tackle Legal, Ethical and Regulatory Hurdles in AI.
Rise of Chief AI Officers: Adoption in Fortune 500 companies for AI leadership. Fortune 500 companies are increasingly appointing Chief AI Officers to lead their AI initiatives, mirroring a trend set by the U.S. government’s recent mandate for federal agencies to do the same.
Democratized Generative AI: a massive shift in application and solution development, allowing non-experts to create sophisticated AI-driven content and applications.
This democratized AI implies Shadow AI, which is the use of AI within organizations without IT department approval, often by non-technical workers. This raises concerns about security, data privacy, and compliance.
AI redefining work: 2 job trends
- AI upskilling, where professionals acquire new AI-related skills
- New AI-specific roles such as AI Product Managers, AI Engineers, AI Ethicists, AI Input and Output Managers, Sentiment Analyzers, AI Regulatory Specialists, and AI Human-Computer Interaction Designers.