Deeper Thinking
In 2025, the current transition toward advanced reasoning models will likely accelerate. For example, many AI companies are currently developing and releasing chain-of-thought models, which break down tasks into logical steps and analyze each step sequentially, and are less prone to hallucinations and other mistakes. This is a relatively new approach, which results in more structured and detailed output, compared to non-chain-of-thought models, but requires more computational resources during inference. Several of the latest and most advanced models include chain-of-thought reasoning, such as OpenAI's o1, Anthropic's Claude 3.7 Sonnet, and DeepSeek's R1 models. Additionally, OpenAI recently announced that it will focus on chain-of-thought models in the near-term, and that its most recent release, GPT-4.5, will be its last non-chain-of-thought model.

AI Agents
AI agents, which are capable of autonomously performing tasks on behalf of a user, will comprise the next major shift in consumer-facing AI technology. For example, OpenAI's Operator and Google's Mariner can take control of a cloud-based internet browser and interact with websites without an API to accomplish tasks that could previously only be performed by a human. Additionally, OpenAI's Deep Research utilizes OpenAI's upcoming o3 model to iteratively browse and ingest many websites over tens of minutes to perform highly detailed, multi-step research on specific topics.

Unified Models
The increasing complexity of the AI landscape has already led to some frustration among consumers, who must choose between many different model options for each query. Currently, third-party tools exist, which interpret a user's input and route queries to the most appropriate AI system. However, in the coming year, we expect to see AI providers unify their models to simplify the user experience. For example, OpenAI recently announced plans to create a large-scale model capable of adapting its performance and approach, depending on the user's input, thereby eliminating the need for the user to pre-select an individual model for use. This approach, if successful, will streamline the user experience and allow for more efficient inference processing, likely resulting in both lower costs and an increased uptake among consumers.