Top 6 AI Trends to Watch in 2025 and Beyond

Whether you’re working in education, marketing, sales, or human resources, it’s probably clear to you that AI is making quite a splash right now.

According to a recent G2 report, more than 76% of software vendors have either already implemented or are in the process of implementing AI.

We’ve already seen some impressive use cases develop for technical and non-technical users alike. Uizard, for example, helps non-technical users design impressive user interfaces, while companies like Frame are making it much easier to gather and analyze customer behavior and sentiment data. And platforms like our very own Colossyan empower the easy creation of video content using text to video AI. 

So, what’s next for 2025? In this article, we’ll dive into half a dozen cutting-edge AI trends that we expect to hear more about as we move through 2025 and beyond. 

6 key AI trends to keep an eye on

Between the push to regulate AI and efforts to expand the accessibility of new tools, there’s a lot going on in the AI space as we head into 2025. 

Here’s some insight into the AI trends we expect to see.

1. Generative AI

Have you used AI to write text, create images, or even to code? If the answer’s yes, then you’ve already familiar with the capabilities of generative AI. 

Generative AI refers to a class of artificial intelligence systems capable of creating new content by learning the patterns and structures of an existing data set. Advanced models – such as large language models like ChatGPT – are able to generate original outputs based on input prompts or training. Generative AI doesn’t just replicate data – it creates new content from scratch. 

This differs from predictive AI, which is typically used in social media algorithms to make predictions using existing data. In contrast, generative AI is much newer, and creates all new content rather than making predictions. 

People across the world are already using generative AI to streamline workplace tasks like writing and editing copy, structuring new content, and brainstorming new ideas. In 2025, we’re likely to see adoption of generative AI tools continue to grow as the technology improves. 

There are many different use cases and generative AI tools out there, but here are a few examples of generative AI that you might encounter: 

AI-generated text 

Producing AI-generated text is extremely straightforward. Using a large language model like ChatGPT or Claude, all you need to do is simply prompt the model with the text you’re looking for. 

For example, you might write a prompt like: “Write me a definition of generative AI in one paragraph.”

In seconds, the LLM will deliver a response within the parameters you gave. In 2025, we can expect to see the quality and accuracy of AI-generated text continue to improve. 

AI-generated video 

Historically, creating a video has been extremely resource intensive. But with AI video, you can now convert text to video in minutes. 

AI video generators like Colossyan allow you to produce professional-quality videos using AI avatars that can speak any script in any language or accent. This way, you can skip the filming process and create high-quality content in minutes without actors or equipment. 

To create a video in Colossyan, all you need to do is add a simple prompt on what you want your video to be about, and the platform’s AI will convert your idea into a video draft. From there, you can edit it to your liking, before generating the final result. 

AI-generated speech

With advancements in generative AI, there’s no need to manually record voiceovers anymore. Instead, AI voices allow you to turn any text into an AI voiceover. Not only is AI-generated speech faster than traditional voiceovers, but you can also pair them with any language, accent, and emotion. 

2. Multimodal AI

Multimodal AI models integrate multiple types of data – including text, images, video, and audio – to create more sophisticated outcomes, allowing for more comprehensive user experiences. 

Traditionally, AI models process information from a single modality, such as text or images, which comes with limitations. 

Instead, because multimodal AI models synthesize diverse data, it can grasp more complex contexts, such as interpreting spoken words alongside facial expressions, which traditional AI cannot do. 

So, why is multimodality a trend to watch in 2025? 

For starters, continued advancements allow the models to combine data sets for richer and more contextualized responses – not only improving the user experience, but also increasing the use cases for these AI models. Applications like virtual assistants are made possible by multimodal models. 

For example, there are already many AI tools in the healthcare industry working to improve diagnostic accuracy and patient care. But with advancements in multimodality, AI might have the capacity to analyze medical imaging, patient records, and physician notes for more accurate diagnoses, rather than relying on a single data set. 

Multimodal AI models will make AI systems significantly more accurate and contextualized, making them more useful across nearly every industry. 

3. AI-driven personalization

AI's ability to analyze vast amounts of data in real time allows for individualized experiences on a massive scale, paving the way for heightened user engagement with content. 

The power of personalized content is already evident with TikTok, as the social media app’s global popularity is tied to its personalized recommendations algorithm. 

Personalization is a powerful tool with the ability to boost viewer engagement, add greater value to viewing experiences, and forge stronger connections with the content being consumed. 

As AI models get better at analyzing user behavior and predicting needs, companies will have greater capacity to scale the personalization of their sales, marketing, and training content, while still ensuring the content is appropriately relevant. 

In a learning and development context, training modules may be able to be automatically adjusted to user progress and feedback, or even specifically tailored to each learner’s role and skills gaps.

In 2025, we can expect advancements in natural language processing, behavioral analysis, and AI avatar realism to drive this focus on personalized content development. 

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4. Democratization of AI

As more AI tools become available, the availability of these tools continues to widen as the cost decreases. 

Consider how ChatGPT – perhaps the most well-known generative AI tool – took just 2 months to reach 100 million users after it launched in November 2022. 

This was a milestone in widespread AI adoption, as ChatGPT showed AI’s potential to millions across the globe, and allowed them to access this technology under a free plan. 

In the time since, many AI solutions have followed suit and now offer free access as well as a user experience that’s easy for even the least techie people. 

We should expect to see this democratization of AI tools continue to expand in 2025, as open-source AI models and low-code/no-code platforms help more non-technical people build and deploy AI solutions. 

Additionally, as an increasing number of office workers continue to use generative AI in their day-to-day work, more organizations and government departments are pushing for AI literacy to ensure more equitable access and adoption. 

Related: The 11 Best AI Tools to Boost Your Business

5. AI agents 

In the last year or so, you’ve likely interacted with an AI chatbot. AI chatbots are everywhere, whether you’re chasing down a customer service request or messaging with a sales representative. 

However, historically these AI chatbots have been faceless, only communicating via written text rather than spoken dialogue. This is poised to change in 2025 due to advancements in AI agents, which are AI avatars that look and sound like real humans, and are capable of real-time interactions. 

The next generation of AI chatbots will be conversational AI agents, which will pave the way for the next generation of interactive experiences more broadly. These conversational AI experiences will feel significantly more human and personalized than text-only chatbots. 

Real-time, natural conversations with avatars are becoming highly feasible due to advancements in large language models (LLMs) and speech synthesis. Real-time avatar conversations require both active listening and contextual understanding, which we’ll almost certainly see in 2025.

But although this technology is still in its early stages, the potential applications aren’t difficult to imagine. There will be significant applications for AI agents in content creation, customer engagement, multimodal analysis, and more. 

These conversational AI agents would have especially huge applications in the education space, as they will allow learning designers to develop learning experiences that go beyond static video creation. Instead, each learner will have their own personal tutor that they can ask questions to and get personalized feedback from. 

Also read: How to Make an AI Avatar of Yourself in 5 Easy Steps

6. AI regulation and ethics

Currently, the rapid deployment of new AI technologies has outpaced the creation of comprehensive legal and ethical frameworks for their regulation. 

While we’ll certainly see conversations around regulations and governance start to catch up in 2025, we will also begin to see the implementation of the EU AI Act – a comprehensive legal framework that aims to ensure that AI systems are trustworthy, ethical, and safe, without stifling innovation. 

However, it’s likely that these regulations may initially slow the adoption of artificial intelligence tools in high-risk settings – like education or high-risk communications – as companies adapt to these new frameworks. 

That said, these regulations are a welcome step toward responsible AI development. AI models are extremely powerful tools, and regulations are crucial in ensuring bad actors are not using this technology to spread misinformation, invade privacy, or perpetuate bias, for instance. 

Over the long term, these clearer regulatory frameworks will boost confidence, reduce uncertainty, and encourage greater investment in AI technologies, ultimately promoting safer and more reliable AI deployment. 

Takeaway

The takeaway here? AI is developing at an incredibly rapid pace, and there’s a ton in store for the upcoming year. 

In 2025, we will see the AI tools we’ve come to know and love continue to expand in their use cases and capabilities, allowing us to use AI in entirely new ways. 

The development of AI agents, for instance, will revolutionize personalized learning, giving anyone and everyone access to their very own always-on tutor. Or, in a non-learning setting, these conversational avatars can serve as a talking knowledge base, helping customer support agents answer customer questions more accurately and efficiently, without the need for human intervention. 

At the same time, we can expect to see larger discussions on AI regulations and ethics take center stage, as the industry – and the world at large – figures out exactly what responsible AI use looks like in practice. 

In the meantime, if you’re curious to understand how generative AI is changing video production, come see for yourself and give Colossyan a try for free today. No credit card required.