What you need to know about AI in 2025

By: Amanda Phagan, Edited by: Marie Custodio Collazo

Published: June 5, 2025

Artificial intelligence (AI) has dominated headlines so consistently over the past few years that it's hard to believe that the technology hasn't been around forever. In 2025, just two years after world-changing advancements catapulted it into the mainstream, AI continues to capture our attention and revolutionize the way we interact with technology.

3 AI trends to watch in 2025

1. Increased AI integration

In 2025, AI has become synonymous with in-app tools and plug-ins. While many developers have prioritized AI integration for years, more companies have jumped on the bandwagon.

Since around 2023, content creation apps like Canva have increasingly incorporated AI tools that allow users to edit, experiment, and streamline their workflows.

In the summer of 2024, Meta introduced its AI Studio tool on Instagram. Around that same time, Google Workspace added Gemini — a generative AI tool — to Google Docs, Sheets, Slides, and Drive. Since then, they've added even more functionality to their "smart" in-app tools.

This year, companies like Duolingo have announced strategies to integrate AI technology. In the short term, it seems likely that apps will continue to find ways to integrate AI into their existing platforms.

2. An eye on "responsible" AI

With the widespread, rapid adoption of AI comes a slew of ethical questions and pushed boundaries. Now that the world's top AI platforms have been popular for a few years, people are beginning to notice the social, economic, and environmental consequences of misusing the technology.

In January, California introduced several new AI laws to protect user privacy, healthcare data, and victims of deepfakes. Meanwhile, countless other researchers, companies, and universities are grappling with ways to regulate AI.

According to Stanford University's 2025 AI Index Report, mentions of AI in legislature have risen globally since 2023 by 21.3% — a ninefold increase since 2016. This number is expected to rise in 2025 and beyond.

3. A focus on AI's workplace impacts

This year, expect an increased focus on AI's impact on the workplace.

Per Stanford's 2025 AI Index Report, generative AI has seen especially strong momentum in the private sector. GenAI attracted $33.9 billion in private investment in 2024, and 78% of organizations reported using AI that same year, compared to 55% the previous year.

Many people are finding that AI boosts productivity in some roles and hinders it in others. According to a 2023 study by researchers at Harvard Business School and the University of Pennsylvania's Wharton School, GenAI improved highly skilled worker performance by nearly 40% when used within the boundaries of its capabilities. In situations where GenAI was asked to perform complex tasks outside of its capabilities, it hindered worker performance by 19%, on average.

Despite mixed productivity results, AI's workplace impact is expected to remain an important focus as the technology advances.

AI terms and acronyms to know in 2025

To stay informed about AI advancements, it's important to know the AI terms people are already using. Some of the top terms you should know in 2025 include:

• Agentic AI: Often considered the "next frontier" in AI, agentic AI uses complex reasoning and planning capabilities to solve multi-step problems without human intervention. A customer service bot that performs tasks like checking an account balance and recommending the type of account best suited for paying the balance is an example of agentic AI.
• CAIO: "CAIO" is the acronym for chief AI officer — a new executive role dedicated to overseeing the implementation of AI at an organization. In some cases, a CDO (chief data officer) or CTO (chief technology officer) may handle similar responsibilities.
• Multimodal AI: Multimodal AI is a type of AI that uses deep learning to process multiple different types of data. While a typical LLM can only process text, multimodal AI platforms can analyze text, images, audio, and video. An example of multimodal AI is an autonomous vehicle, which processes information from multiple sensors, cameras, and user inputs to make real-time decisions.
• LLM: LLMs — large language models — are a type of AI that processes language-based information like text to hold a conversation and perform tasks. Popular LLMs include OpenAI's ChatGPT, Google's Gemini, and Meta's Llama.
• GenAI: GenAI — short for generative AI — is a type of AI that creates content based on prompts. This content may be images, text, or videos. OpenAI's DALL-E, an image-generating tool, is a popular example of generative AI.