Artificial Intelligence (AI) has quickly evolved from a buzzword to a real engine of productivity across global industries. In 2025, companies aren’t just experimenting with AI—they’re deeply integrating it into core workflows to streamline operations, improve decision-making, and deliver more personalized customer experiences.
From Fortune 500 corporations to agile startups, businesses are tapping into powerful AI models to generate content, automate tasks, and mine insights from oceans of data. While dozens of models are available today, a few standout tools have emerged as favorites across the business landscape.
Here’s a look at the most-used AI tools by companies in 2025—and why they matter.
- GPT-4 (OpenAI)Â
The flagship model from OpenAI, GPT-4 remains the go-to for companies seeking cutting-edge language understanding and generation. It’s used by over 90% of Fortune 500 companies, powering everything from internal knowledge assistants to high-quality content production. With its capacity to generate, summarize, translate, and even write code, GPT-4 is the Swiss army knife of enterprise AI. Many businesses use it to automate reports, draft communications, and even assist in customer support. Its accuracy and versatility make it ideal for high-stakes use cases.
- GPT-3.5 (OpenAI)Â
While not as powerful as GPT-4, GPT-3.5 is still widely used due to its excellent performance-to-cost ratio. It’s fast, scalable, and perfect for customer service bots, internal chat assistants, or recurring tasks like writing basic reports or product descriptions. It’s also the model that underpins the free version of ChatGPT, which many companies use as a testing ground before scaling up to GPT-4 or GPT-4 Turbo.
- Gemini (Google DeepMind)Â
Google’s Gemini model family (formerly Bard) has quickly made waves thanks to its strong multimodal capabilities—understanding not only text but also images and other types of input. Businesses using Google Workspace have likely already encountered Gemini behind the scenes, especially in Docs, Sheets, and Gmail, where it helps write, summarize, and extract insights. Gemini is deeply integrated into Google Cloud’s Vertex AI platform, making it accessible to enterprise teams building their own apps.
- PaLM 2 (Google)Â
Before Gemini took center stage, Google’s PaLM 2 led the charge. It remains a widely used model in 2025, especially across Google’s suite of tools. With exceptional multilingual and coding capabilities, PaLM 2 helps companies translate content across 100+ languages, build smart assistants, and power internal tools with natural language interfaces. It’s a foundational piece of many AI-driven features in Gmail, Docs, and Android.
- Claude 2 (Anthropic)Â
Anthropic’s Claude 2 is gaining popularity fast—particularly in industries like finance and healthcare where ethical AI, transparency, and data security are top priorities. Claude is known for its “Constitutional AI” training method, designed to produce safer, less biased responses. With strong contextual reasoning and a reputation for reliability, it’s being used to build responsible AI copilots, legal assistants, and compliant customer service bots.
- CohereÂ
Designed for enterprise customization, Cohere’s models allow companies to fine-tune large language models on their own internal data. This makes it possible to create branded chatbots, internal knowledge tools, or semantic search engines tailored to company-specific terminology. With strong privacy protections and full control over data, Cohere is especially popular among companies that need to keep proprietary information in-house.
- Falcon (Technology Innovation Institute, UAE)Â
Falcon is one of the most powerful open-source models available—and it’s free for commercial use. Tech-savvy companies use Falcon to run AI locally, reducing reliance on cloud APIs and external providers. It’s a top choice for organizations prioritizing data autonomy, cost savings, and full transparency. Falcon is also supported by a vibrant developer community that continues to optimize and extend its capabilities.
- LLaMA 2 (Meta)Â
Meta’s LLaMA 2 models have taken the open-source world by storm. They’re fast, powerful, and commercially usable—meaning companies can fine-tune and deploy them on their own infrastructure. From retail to financial services, companies are using LLaMA 2 to build internal assistants, automate document analysis, and even support customer-facing applications. It’s a popular option for teams who want GPT-level performance without depending on external APIs.
- VicunaÂ
Built by a consortium of academic researchers, Vicuna became a benchmark in conversational AI after outperforming expectations for a 13B parameter model. Though it’s restricted to non-commercial use, it has inspired many commercial implementations and is frequently used in education and research. Its high-quality dialogue generation and contextual awareness make it ideal for building tutoring systems and experimental chatbots.
- StableLM & Stable Beluga (Stability AI)Â
Known for open-source innovation, Stability AI created StableLM and its chat-tuned variant Stable Beluga to give developers complete freedom and transparency. These models are frequently used in academic research, experimental chatbots, and lightweight assistant applications. While not at the performance level of LLaMA 2 or GPT-4, they offer a good balance of usability, multilingual support, and control—especially in educational or prototyping environments.
- MPT (MosaicML / Databricks)Â
MosaicML’s MPT models (now part of Databricks) are all about scalability and control. Designed for easy training and long-context tasks, MPT-7B and MPT-30B have been adopted by startups and enterprises to build custom AI solutions—like coding copilots, document processors, and internal chat tools. Many teams choose MPT when they want the power of a proprietary model but the freedom of open-source infrastructure.
- XGen (Salesforce)Â
XGen-7B, developed by Salesforce, is fine-tuned for CRM, sales, and customer interaction tasks. It’s embedded in Salesforce’s Einstein platform, helping businesses personalize sales communications, summarize meetings, and track pipeline activity. Its fine-tuned version, XGen-Sales, was trained on proprietary sales data and integrates tightly with tools like Slack and Salesforce CRM, making it a natural fit for customer-focused organizations.
- Grok (xAI)Â
Elon Musk’s AI company, xAI, launched Grok as a conversational assistant deeply embedded in X (formerly Twitter). What sets Grok apart is its real-time access to social media trends and its candid, often witty personality. Businesses in media, marketing, and communications are starting to explore Grok for trend analysis, cultural insights, and social sentiment monitoring. While still new, Grok is carving out a niche in social-data-aware AI.
Which AI model should your company choose?Â
The AI tools listed above reflect the diversity of enterprise needs in 2025—from plug-and-play solutions like GPT-4, to fully customizable platforms like Cohere and MPT. Some prioritize raw power and accuracy, others champion privacy, control, or specialization. But all are shaping the way companies work, communicate, and compete.
AI is no longer an emerging trend. It’s a core driver of innovation—and staying ahead means choosing the right tools for your goals, your team, and your data.
Would you like help integrating any of these tools into your business workflows? Let’s talk.