What's Next for AI in 2025: Q&A with Associate Professor Wei Xu

As artificial intelligence (AI) continues to evolve, its impact on society becomes increasingly profound. To gain insights into the trends shaping the AI landscape in 2025, we spoke with Wei Xu, an associate professor at Georgia Tech’s School of Interactive Computing, whose research focuses on natural language processing and machine learning.

Q: What do you believe will be the most significant breakthrough in AI in 2025? 

A: Predicting breakthroughs is inherently difficult, as they often emerge unexpectedly. Most major advancements stem from years of incremental progress and research that suddenly converge into a solution that surprises us with its effectiveness. Usually, these breakthroughs originate in areas that are not yet widely recognized as promising or trending.

This unpredictability highlights the importance of sustained investment in diverse research directions, including high-risk projects and fundamental science. By prioritizing innovation, companies and the U.S. government can help ensure the groundwork is laid for transformative discoveries in AI.

Q: Which industries will experience the greatest transformation due to AI in the next year?  

A: In the coming year, advancements in AI are poised to transform industries across the board, both within and beyond the tech sector. Sectors such as healthcare, retail (custom service), marketing, law, education, entertainment, and many others are increasingly adopting large language models (LLMs) to enhance data analysis and improve user interactions. These models offer capabilities far surpassing traditional machine learning methods, driving a shift toward more efficient and intelligent systems.

Ethical and Societal Impact 

Q: What are the most pressing ethical challenges for AI development and deployment in 2025? 

A: Safety: One of the most critical concerns is ensuring the accuracy and reliability of AI systems, especially in high-stakes scenarios such as providing medical advice.

Privacy: With AI systems, privacy risks are heightened when users share vast amounts of personal data — such as emails, resumes, and meeting transcripts.

Fairness: Language models must be designed to account for diverse cultural backgrounds, values, opinions, and languages—including dialects and individual linguistic styles. 

Q: How do you see AI influencing education and learning in the coming year?

A: AI will significantly impact education. It can expand access to knowledge through personalized learning tools and make educational materials more widely accessible. Integrating AI into K-12 curriculums will raise public awareness and prepare students for the future. However, educators are concerned about misuse, such as students relying on AI to complete assignments without fully understanding the material.

Q: What role will generative AI play in shaping public discourse and creativity in 2025? 

A: I think Joanna Maciejewska's comment has crystallized it: "I want AI to do my laundry and dishes so that I can do art and writing, not for AI to do my art and writing so that I can do my laundry and dishes.

Research and Technology 

Q: What advancements in AI hardware or infrastructure are crucial for 2025?

A: Advancements in AI hardware and infrastructure crucial for 2025 include innovations in GPU and specialized hardware such as TPUs (tensor processing units) or custom AI chips, which can accelerate model training and inference. Equally critical is improving the energy efficiency of these components, as current AI models heavily rely on massive GPU computing and data center infrastructure. 

Q: Which areas of AI research would you say are under-funded or under-explored?

A: Many! While the field sees a high volume of publications, much of the work tends to be surface-level or rushed, with fewer resources dedicated to deep, innovative research. This can lead to the illusion of progress in some areas without truly solving the underlying problems. For instance, despite significant advancements, challenges remain in areas like machine translation. While current systems perform impressively, they often fall short in capturing nuances, cultural context, and idiomatic expressions. Similarly, tools like ChatGPT can assist with writing. However, they still struggle to match a skilled human writer's sophistication, coherence, and creativity. Furthermore, using AI in writing can sometimes result in the loss of personal linguistic style, making outputs less authentic or unique.

Q: How do you predict AI regulations or policies will evolve over the next year? 

A: Over the next year, I anticipate and hope that AI regulations and policies will become more nuanced as policymakers and the public gain a deeper understanding of AI technologies. Ideally, we will see more policymakers, such as U.S. congressional members, with science or engineering backgrounds who can approach AI advancements with a balanced perspective. Such leaders would be better equipped to craft thoughtful regulations addressing privacy, copyright, and bias while avoiding stifling innovation through over-regulation.

Additionally, I hope for a concerted effort to enhance AI literacy among the general public through media, educational initiatives, and public discourse. Greater familiarity with AI technologies can lead to more informed and constructive opinions, helping shape regulations that reflect societal values and priorities. This combination of knowledgeable policymakers and an AI-aware public could foster a regulatory environment that supports innovation while ensuring ethical and

Vision and Advice 

Q: What emerging technologies or approaches in AI excite you the most for 2025?

A: For 2025, I'm most excited about:

• AI-driven personalization: AI adapting to individual language styles, cultural backgrounds, personal knowledge, and real-time context.
• Multilingual and multi-modal models: Enhancing non-English language performance and integrating diverse data types seamlessly.
• Domain-specific foundation models: Specialized models for law, biology, and material science to accelerate breakthroughs.

Additionally, improving large language models in safety, privacy, robustness, efficiency, and better training techniques remains a fundamental focus for better overall performance.

Q: What advice would you offer to students or researchers entering AI in 2025? 

A: My advice for students and researchers entering AI in 2025 is to focus on what truly excites you. Take it step by step—read papers, deepen your knowledge, and stay grounded to avoid feeling overwhelmed. While staying informed about trends is important, aim to be an early adopter of emerging ideas or work on solving long-standing, challenging problems. By pursuing your passion, prioritizing originality, and leveraging your unique strengths, you can forge your path and make a meaningful impact in the field.