Industry executives and experts share their predictions for 2025. Read them in this 17th annual VMblog.com series exclusive.
By Vasagi Kothandapani, President of Enterprise Services, RWS
According to a new global study conducted by RWS, 62% of consumers are excited by the emergence of Gen AI. But they also have concerns – they highlighted the need for greater transparency from organisations around their use of AI, with 81% saying it’s important that AI-generated content produced by companies be clearly labelled. So, what’s in store for businesses and consumers of AI in 2025? Here are our top five predictions.
1. The rise of AI agents
As we move into 2025, the adoption of AI-powered agents will continue to grow, as they evolve to make increasingly complex decisions and take actions based on continuous learning. They will permeate all aspects of our lives, augmenting human effort at work and at home, simplifying tasks by harnessing powerful functionality. They will be developed to enhance human capabilities by handling complex tasks autonomously, freeing up humans’ time to focus on higher-value work that requires creativity, emotional intelligence, and strategic thinking.
AI agents will not only work in isolation but will also be connected to build powerful agentic workflows that collectively collaborate, share information, and solve complex problems across domains and organizational boundaries. These interconnected agent networks will create sophisticated, adaptive, and intelligent systems that simplify intricate challenges into manageable subtasks, coordinate seamlessly, and achieve outcomes beyond the capabilities of individual agents or human teams working on their own. They have the potential to transform business by autonomously handling complex tasks, improving decision-making processes, and significantly boosting efficiency.
2. Wider adoption of small language models
Another anticipated development is a shift towards small language models (SLMs) to effectively address growing concerns around data privacy and reduce latency in AI applications. SLMs will be developed to run locally on mobile devices, protecting individual data privacy and delivering faster response times. This shift will also help democratize AI technology by making it more accessible and user-friendly. It will open up new possibilities for personalized AI assistants and edge computing applications, fundamentally changing how we interact with AI in our daily lives.
The move towards SLMs further emphasizes the need for carefully curated, high-quality training data and Gen AI fine-tuning for specific use cases along with innovative approaches to model compression.
3. AI at the edge
2025 will also see a substantial shift towards edge AI, with more computation moving to inference at the edge. Pre-trained AI models will run directly on local devices or edge servers, close to where data is being generated and used. This transition will dramatically improve the speed, efficiency, and data security of AI applications by enabling real-time processing of data on local devices, reducing latency and bandwidth usage while enhancing privacy. This shift will be particularly impactful in IoT devices, autonomous vehicles, and smart city initiatives. By bringing AI capabilities closer to the data source, edge computing will unlock new possibilities for AI applications, enabling more responsive and context-aware systems that can react to local conditions and user context, and operate effectively even in low-connectivity environments.
4. Smarter, more creative, and more intuitive AI
In 2025, AI models are expected to demonstrate significant capability advancements, including improved reasoning abilities and problem-solving skills across domains such as science, coding, mathematics, law, and medicine. These enhanced models will be able to do everything from efficiently comparing complex contracts, to generating sophisticated code, and executing complex multistep workflows with precision. Their ability to process and analyze vast volumes of data will lead to breakthroughs in research and development across industries, streamlining processes, accelerating innovation, and opening up new possibilities for solving complex global challenges.
But at the same time, AI will also become easier to use, better at understanding our emotions, and more creative in its ideas, which will further boost its widespread acceptance and adoption. As user interfaces become more intuitive and accessible, individuals, regardless of technical knowledge, will be able to easily leverage AI capabilities. Additionally, advancements in emotional understanding will enable AI systems to respond more empathetically, fostering stronger connections with its human users. This combination of user-friendliness and emotional intelligence will further embed AI into our daily lives.
5. Fragmented regulatory landscape
As AI rapidly evolves, the global regulatory response will continue to be fragmented, as regulators struggle to keep pace with AI development. The European Union’s AI Act, one of the world’s most comprehensive AI regulatory frameworks, categorizes AI applications by risk levels and imposes strict requirements for high-risk systems. The EU AI Act will be partially implemented, with prohibitions on unacceptable risk AI systems and obligations for general-purpose AI models taking effect in 2025. Other regions, such as the United States, are expected to continue to rely more heavily on sector-specific guidelines and voluntary standards, creating a regulatory patchwork that will complicate cross-border collaboration.
This regulatory fragmentation will pose significant challenges for businesses operating globally. Companies will have to navigate varying regional standards for data use, transparency, and accountability, increasing compliance costs and operational complexity. As a result, there will likely be growing pressure for a more unified global AI regulatory framework to address inconsistencies and close loopholes. Regulatory fragmentation is also expected to significantly impact AI development and deployment strategies, with companies having to invest in region-specific compliance measures, while advocating for consistent international standards.
AI. Its future relies on collaboration between humans and machines.
With all the hype surrounding AI replacing humans, it’s important to remember, AI, at its core, is designed to enhance human capabilities. Companies see the biggest performance gains when humans and AI collaborate. Humans are needed to develop and train AI, explain its outputs, and ensure its responsible use. AI systems augment human decision-making, offering data-driven insights, while humans provide context, creativity, and ethical oversight. And based on our new study, 81% of those who care about AI say knowing humans were in the AI development loop would increase their trust in AI. It’s clear the future of AI lies in seamless human-machine partnerships – artificial intelligence and human intelligence working together to achieve genuine intelligence.
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ABOUT THE AUTHOR
Vasagi Kothandapani, President of Enterprise Services, RWS
Vasagi is President of Enterprise Services, responsible for multiple global client accounts at RWS, as well as RWS’s TrainAI data services practice which delivers leading-edge AI training data solutions to global clients across a broad range of industries. She has 27 years of industry experience and has held various leadership positions in business delivery, technology, sales, product management, and client relationship roles in both product development and professional services organizations globally. She spent most of her career working in the technology and banking sectors, supporting large-scale technology and digital transformation initiatives.
