As artificial intelligence continues its rapid evolution, the coming year is poised to bring even more changes to how we live and work—and the pace of change will accelerate in 2025.

Simon Margolis, associate chief technology officer of AI/ML at IT consulting firm SADA, discussed the shifting AI landscape on the Cloud and Clear podcast. He emphasized, "We are not just seeing growth; we are seeing [a] continued explosion of the pace of innovation and what that means for businesses." Margolis also added that new AI platforms that make advanced technology accessible to more people are emerging, and problem-solving with AI is becoming more accessible to everyone—even those without a tech background.

The latest AI trends can be summarized as responsiveness, personalization, and integration. Agents are transforming productivity by automating routine tasks, allowing people to focus on more strategic work. AI tutors can personalize education while bridging learning gaps and supporting students' individual needs, while emotion-aware AI assistants are making technology more responsive to human emotions. Meanwhile, digital avatars and AI immortality are extending our digital lives and helping to preserve memories.

As intelligent technology increasingly becomes part of our everyday lives, it promises to make a significant impact in the coming year. Creatie.ai compiled key trends in AI to watch for as companies race to dominate the technology being integrated into products and workflows.

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AI agents move beyond automation to logical problem-solving

AI agents are reshaping workflows, promising to save time and enhance productivity at work. Microsoft describes agents as "the new apps for an AI-powered world," capable of handling tasks such as balancing financial data, compiling reports, and generating customer leads. One example is Copilot Studio, which is integrated into Microsoft 365. It allows users to create tailored automation templates or even build custom agents without programming skills, freeing them to focus on strategic tasks, according to Microsoft. Meanwhile, Google’s Gemini 2.0 enables agents to function across domains, performing tasks and analysis in the real world or within video games in virtual worlds. 

The next leap for AI agents is reasoning—the ability to break tasks into logical steps and execute them autonomously, with models like OpenAI's o1 series and Alibaba's QwQ-32B-Preview as clear standouts in the field. TechCrunch reports that Alibaba's model can solve challenging problems and, according to testing by the company, outperform OpenAI's o1-preview on reasoning benchmarks. These reasoning models are more advanced than earlier generative AI tools, with Alibaba's model designed to fact-check itself and reason step-by-step through complex tasks. However, it struggles with common-sense reasoning and maintaining language consistency.

At an industry summit, Scale AI Founder and CEO Alexandr Wang noted that agents could spark a "ChatGPT moment" in 2025, with widespread adoption similar to the early days of generative AI, according to The Verge. Yet challenges remain. "The internet has shockingly little data of humans carrying [out] actions and documenting their thought processes as they go," Wang remarked.

As AI improves its reasoning skills, scaling challenges persist. Training large models like GPT-4 requires massive energy resources equivalent to powering 5,000 American homes for a year, which is far more than its predecessor. Meanwhile, the supply of high-quality training data might run out by 2028. Innovations like test-time compute, which gives models extra processing power for specific tasks, are emerging as solutions, TechCrunch reported. These improvements could make AI more efficient without relying on costly scaling.

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AI tutors and the future of education

Amid a shifting educational landscape, AI tutors could emerge as a possible way to reshape classrooms. Forty-seventh President-elect Donald Trump's proposal to shift educational oversight back to states raises questions about how schools might adapt to a reduced federal role, NPR reported. This shift creates the potential for a surge in AI-driven tutors, according to senior data scientists at the University of Chicago. Educators might also examine how AI might fill gaps in learning support.

Supporters say AI tutors offer myriad benefits, including personalized instruction tailored to students' unique learning needs and greater accessibility. Platforms like Carnegie Learning and Khan Academy already use AI-driven tutors to deliver personalized academic support. These tools' strengths include addressing student weaknesses and creating interactive and engaging experiences by providing instant feedback and resources.

Experts at the University of Chicago say integrating AI into education is "no longer a matter of 'if' but 'how.'" Still, others caution against overreliance on AI systems. Research from the University of North Florida published in the journal Advances in Engineering Innovation noted that educators should be aware of the ethical considerations surrounding data privacy, potential biases in AI algorithms that might further inequalities, and the "challenge of integrating AI seamlessly into existing educational infrastructures."

A Brookings task force also warned that gains in efficiency from automating tasks like grading or lesson planning should not come at the expense of human-centered instruction. Balancing AI's capabilities with traditional teaching approaches will be necessary to ensure technology enhances, rather than diminishes, learning and development. If implemented responsibly, however, AI could bridge educational gaps for underserved communities.

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Digital avatars and the promise of AI immortality

In a not-so-distant future, your digital self could continue telling your story long after you're gone. This is the promise of digital and AI immortality avatars. Research published in the journal Computers in Human Behavior: Artificial Humans found that virtual reality avatars typically used for social interactions are now expanding to social media and therapeutic contexts. These avatars offer varying levels of human resemblance, significantly influencing engagement and trust. This gives them vast potential, from helping individuals preserve their memories to allowing brands to create immersive, interactive campaigns.

Companies like Sensay are creating digital twins that replicate human knowledge, voice, and image, providing a sort of digital immortality. These avatars provide emotional support and help preserve memories that can comfort grieving family members or those supporting dementia patients, leaving a consistent digital legacy.

On the corporate side, brands are also increasingly integrating AI influencers into their broader digital campaigns to engage consumers in new ways. Virtual influencers are being used to promote everything from cosmetics to cars for brands like BMW, Maybelline, and Olaplex, per The Drum.

AI influencers have the advantage of being customizable; since AI avatars can be tailored to different demographics, they can provide a level of personalization that traditional influencers cannot. Markets like China are leading the way in adopting virtual influencers for live streams and product endorsements, suggesting wider adoption is on its way.

Consumers, however, can often sniff out gimmicks or inauthenticity, which raises concerns about the risk of undermining trust with audiences who may be skeptical of avatars and AI-driven personas. As AI avatars continue to evolve, storytelling, character development, and clear ethical guidelines will be crucial to maintaining authenticity and audience engagement.

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The rise of emotion-aware AI

Virtual assistants can set reminders and answer questions. Soon, however, they'll be able to sense when you're having a rough day and offer a comforting response. Emotion-aware AI, or affective computing, is perhaps the most "out there" trend on this list. It pushes the boundaries of what we expect from technology.

Unlike traditional AI, these assistants don't just complete tasks; they interpret body language. Emotion-aware AI adjusts its responses based on nonverbal cues like facial expressions and vocal tones, similar to human behavior, according to MIT Media Lab scientist Javier Hernandez. OpenAI caused a stir in 2024 with the introduction of ChatGPT omni, which surpasses previous Large Language Models with its ability to improve emotional responsiveness based on close analysis of the tone, pitch, and volume of a person’s voice. 

Research published in the Journal of Business Research found that empathic AI-enabled voice assistants, such as Amazon Alexa, can increase user trust and engagement, especially in contexts like voice commerce. Empathic AI assistants combine practical functions with emotional connections to improve user experiences and build brand loyalty. According to researchers, however, careful design is needed to avoid making people uncomfortable, as overly humanlike empathy could cause unease.

This is already changing how companies understand customer experiences. In advertising, Affectiva uses technology that captures people's real-time reactions to advertisements to help brands see how viewers really feel. Cameras track emotional responses while watching commercials to give companies a deeper look at what makes an ad effective.

This approach goes beyond traditional surveys by showing moment-by-moment emotional changes. This technology is also expanding into other areas like automotive safety where it can help detect driver fatigue or distraction, the Massachusetts Institute of Technology Sloan School of Management reported.

Affective computing technologies also have the potential to enhance public services by creating emotionally intelligent interfaces that adapt their approach to improve user experience, according to a 2024 report from Deloitte on affective computing. Emotion-aware technology is also being introduced in health care, which monitors patients' emotions to provide personalized care.

However, as this technology evolves, ethical considerations around privacy and surveillance, consent, and bias must be at the forefront of people's minds. Erik Brynjolfsson, a professor at MIT Sloan, emphasized the importance of designing inclusively, with diverse training datasets and ethical considerations to ensure privacy and cultural sensitivity.

"The paradigm is not human versus machine—it's really machine augmenting human," Brynjolfsson told MIT. "It's human plus machine."

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AI-generated videos promise sophistication and scale

In December 2024, the highly anticipated launch of OpenAI’s Sora video generation tool launched a new era of video creation and production. The model can spin up videos from text prompts of, well, pretty much anything. Long-extinct wooly mammoths trampling through snow? Pirate ships sloshing around in a cup of coffee? Generating seemingly improbable scenes like these with natural—and accurate—visual quality is where Sora excels. Its ability to capture depth of field, photorealistic images, and fluidity of movement are just some of its most impressive features. 

The model also offers a storyboard feature to further refine and edit content. While the highest-quality outputs are behind a subscription paywall, Sora has the potential to bring AI video generation to scale in the coming years. 

On the heels of Sora’s debut, Google’s DeepMind announced the launch of Veo 2, a next-generation AI video tool that stole some of Sora’s thunder. Veo 2 already has a long waitlist of eager users, thanks to an exponentially higher resolution and duration compared to Sora. It also excels in capturing fluid dynamics, like syrup drizzled on pancakes, as well as the use of light, texture, and natural movement. Veo 2’s editing suite and style tools also set it apart. 

The AI video revolution is not without controversy. As AI-generated videos become more sophisticated and easier to create, it’s harder for consumers to recognize deepfake content intended to mislead, misinform, or harm. When videos can use people’s faces and voices without consent and generate images or situations that have no basis in reality, people can no longer trust their own eyes. Longstanding debates about what constitutes fair use when it comes to training AI models may also heat up. Although DeepMind’s parent company asserts that using public data is fair use, scraping content without permission, attribution, or financial compensation won’t sit well with many. Everyone from YouTube content creators and movie studio heads to filmmakers and TV writers worry that their work may be used to train AI to eventually replace them, putting them out of jobs in the coming years. 

Story editing by Alizah Salario. Additional editing by Kelly Glass and Elisa Huang. Copy editing by Paris Close.