As 2024 draws to a close, we reflect on a standout year for generative AI that went beyond what many of us imagined. Looking ahead to 2025, we see key trends that will shape the industry: Agentic AI, the crucial role of data, enterprise AI, the growth of multimodal and open-source models, and the importance of thoughtful AI regulation.
This year, generative AI has truly reshaped industries and changed the way we work and learn. A 2024 McKinsey survey shows a significant uptake in AI usage, with 65% of businesses now integrating AI tools into their daily operations—twice as many as last year.
With 2024 winding down and 2025 on the horizon, let's explore the key breakthroughs that have marked this year and look forward to the innovations that await us. Whether you're a tech enthusiast, a business strategist, or just keen to keep up with rapid changes, the next year promises to be just as thrilling in the world of generative AI.
We've looked at the trends and talked to experts, and now we're ready to share the top six AI predictions for 2025. Some of these trends have already made a big impact, while others are just starting to show their potential.
Data: Every company’s goldmine
The better the data, the better AI works. This is the mantra that every company using AI needs to take seriously. As Databricks CEO Ali Ghodsi voiced the concern of all organizations using AI, "I don't care about standard benchmarks, I want the model to do well on my data." This reflects a common viewpoint among businesses using generative AI. They're not just interested in how AI performs on tests but need it to work effectively for their specific requirements. Ghodsi also pointed out that 85% of generative AI projects haven’t gone live yet, mainly because businesses aren't utilizing their data effectively.
Every company's data is their gold mine. Consider customer service, for example. If your company has been collecting a lot of customer feedback or has detailed records of your supply chain, that's invaluable. However, the real challenge lies in transforming this data into practical AI applications.
Looking ahead, the key to AI success in 2025 and beyond will be how smartly you use your data, turning it into training data that powers your AI solutions.
Enterprise AI
In the business world, the real power of generative AI comes from fine-tuning models to suit specific needs. AI in 2025 will be in the hands of enterprises using it.
It's not enough to have a lot of data; the key to success is adjusting AI models to work effectively with that data.
Companies need to turn their raw data into useful training sets that can specifically guide and improve AI performance, and that’s where SuperAnnotate steps in. We help companies build large-scale multimodal LLM fine-tuning and evaluation datasets tailored to their specific use cases to train the models on these datasets. We aim to ensure businesses can effectively use their data to get ahead with AI.
Multimodal AI
Gone are the days when AI could only handle text. Now, in 2025, multimodal models are the new cool. These models can write, talk, see, and even understand videos.
The Multimodal Al Market’s size was valued at USD 1.2 billion in 2023 and is expected to grow at a CAGR of over 30% between 2024 and 2032.
Why is multimodality so hot right now? It's simple: these models are closer to how we humans perceive the world. We don't just read or listen—we see, hear, and process information from multiple sources at once. Multimodal AI is catching up to our multitasking brains.
There are several multimodal AIs out there—GPT 4o, Claude 3, Google's Gemini—and many more are expected to come this year. The future is multimodal.
Open-source models
This year has been and will be a big one for open-source AI models, like Meta’s Llama models, Mistral’s models (Mixtral 8x7B, Mixtral 8x22B), Google’s Gemma and so on. They're more affordable and accessible, making it easier for developers and small businesses to innovate.
What's really exciting is how accessible these models are making AI technology. For instance, "Llama 3" has been turned into a tool that any company can download and use right away. This move transforms businesses of all sizes, helping them integrate AI into their daily operations. This shift to open-source allows every company to become an AI company, which is a huge step forward.
The graph below shows how the freshest open-source model, Meta's Llama 3.1, closed the gap with closed-source models for the first time in history. The assumption is that they will outdo the all-time favorite closed-source models!
Both open-source and closed-source AI models are essential. Open-source models drive widespread innovation and adoption, while closed-source models push the limits of AI.
Agentic AI
Agentic AI just popped up in mid-2024, and it's the hottest topic for 2025. What's so special about it? This new kind of AI can operate on its own, making decisions and acting without needing us to guide it every step of the way. This is quite different from older AI, which only did what we told it to. These AI agents are especially useful in customer service, where they can handle tasks more efficiently, saving time and increasing productivity, or in finance, where they quickly analyze data and offer recommendations.
LLM agents are particularly interesting. They manage complex text generation tasks, providing answers to tough questions that simpler models can't handle.
AI regulation and ethics
As AI becomes a bigger part of our lives, it's important to discuss how we keep it safe and fair. This trend is about making rules to ensure AI is used in a way that's good for everyone. Governments and organizations around the world are working on these rules right now.
They're focusing on things like how AI should handle our personal data, making sure AI doesn't treat people unfairly, and keeping AI decisions open so we can understand and question them. The idea is to ensure that as AI gets more powerful, it helps us without causing problems or leaving anyone behind. This is about using AI responsibly and making sure it's a positive addition to our world.
Closing remarks
AI is growing incredibly, and it seems like everyone is becoming an AI company now. If you're not involved with AI, you've already missed out. As more enterprises enter the Gen AI race, it's important to carefully observe the trends and predict what will happen next.
The future of generative AI relies on data, embraces multimodality, prioritizes customization, sees great potential in open-source, and recognizes the need for ethics. So, if you're involved in AI, make sure these trends are on your radar!
