Trends in Artificial Intelligence: 2025 and beyond

As individuals and businesses get more comfortable with AI and AI generated content, what are the trends we should be looking for in a world where AI is becoming reality.

1. Democratization of Generative AI

Generative AI uses machine learning to create new content based on patterns and algorithms from data it has been trained on, responding to a user’s prompt. Generators like ChatGPT, Gemini, CoPilot and MetaAI produce AI-generated text: from blogs to marketing material to emails to college essays to children’s stories. Other generators produce videos, images, and web developer code.

The game changer is the wide availability of AI – text and image generators have become widely available. Being available and the fast rate of adoption – even to those without technical knowledge has created its own eco-system and its own level of sophistication.

The creation of content and creation of content faster is changing how individuals communicate with each other and is starting to encroach in business communication.

2. Utilization of AI for workplace productivity

AI has sped up and enhanced how we work and interact with each other. The automation of time-consuming and repetitive tasks has substantially increased productivity. Marketing blogs have been influenced by AI and there is a strong trend of creating presentations for customer meetings.

3. Multimodal AI

One of the critical breakthroughs with AI is utilization for unstructured data. The utilization of AI to utilize information from different data types: audio, video, and images, in addition to text, is starting to yield results. AI has transformed from operating under the Large Language Models (LLM) which processes text data to muti-variant data . AI is enabling search and content creation tools to become more seamless and intuitive and integrate more easily into other applications we already use. 

4. Virtual Assistants

Besides AI’s influence in the business workplace, AI tools are being used for consistently providing assistance without the human touch. The virtual assistants are  getting “smarter” and more user friendly – responding beyond simple text interactions. Advancement is where the machine is being trained to respond to different forms of communication – including voice.

5. Natural Language Processing (NLP) Advancements:

NLP will have a significant impact particularly with the development of large-scale language models like GPT, Gemini etc. These models have demonstrated impressive capabilities in tasks such as text generation, translation, summarization, and sentiment analysis.

6.   Edge AI:

Edge computing, which involves processing data locally on devices at the edge of the network, will gain greater traction with the utilization and democratization of AI applications. Edge AI enables real-time inference and decision-making without relying on a centralized cloud server, making it suitable for applications requiring low latency or privacy-sensitive data.