2025 will bring advancements in autonomous AI agents that can plan, execute and adapt tasks with little human intervention: Moody's Ratings

New Delhi [India], January 15 : Autonomous AI agents capable of planning, executing, and adapting tasks with minimal human intervention are expected to make significant strides in 2025, according to Moody's Ratings.
These systems could revolutionize industries by driving operational efficiencies and supporting AI adoption across diverse sectors.
While the broader economic benefits of AI may take years to fully materialize, the ongoing competition among AI developers is already creating a wave of accessible and capable products. As industries increasingly integrate AI, the technology's potential to enhance productivity and innovation appears limitless.
The race to dominate artificial intelligence (AI) is entering a new phase in 2025, as competition among foundation model developers drives innovation in features and usability rather than just scaling data and computational power.
Major AI research labs are reaching comparable performance levels, with industry leaders pushing boundaries to deliver better, user-friendly products tailored to diverse use cases.
The performance of leading foundation models has converged in benchmarks assessing accuracy and task diversity. Open-source models have added to the competitive pressure, offering affordable and flexible alternatives to proprietary systems.
These innovations aim to integrate seamlessly into workflows, accelerating adoption across industries like finance, media, and automotive.
The exponential scaling of AI models is hitting diminishing returns, with high-quality datasets becoming scarce and additional computational resources yielding smaller performance gains.
As a result, developers are turning to synthetic data, which mimics real-world scenarios to address data shortages. While promising for structured domains like cybersecurity and healthcare, synthetic data has limitations in handling complex, unstructured tasks such as natural language processing.
AI model improvements now hinge on enhancing the inference process, where AI systems process and respond to user prompts.