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Enterprise AI vs. Consumer AI: Why ChatGPT Falls Short in the Workplace
Have you ever felt like you’re missing something in the AI boom? Sure, chatbots are amusing, and having improved predictive text and grammar tools for emails is helpful. Some people even use ChatGPT for meal planning, grocery lists, or workout routines.
However, if you handle sensitive data or work on cutting-edge enterprise projects, consumer AI may not significantly enhance your workflow. That’s where enterprise AI steps in.
What is Consumer AI?
Consumer AI is what most people picture when they think about artificial intelligence. ChatGPT, a Large Language Model (LLM) released in late 2022, has played a major role in the AI surge, engaging thousands of users. But it’s not the only consumer AI available—applications like Google Translate, Otter, and Grammarly have been utilizing AI for years.
In essence, consumer AI tools process vast amounts of data to provide answers, generate text, or create images based on patterns they recognize. These tools can function as chatbots, writing aids, portrait generators, , transcribers, grammar checkers, and even search engines (though verifying their responses is always advisable since ChatGPT occasionally hallucinates like a festival-goer). While tools like ChatGPT or Perplexity can be helpful, they often serve more as entertainment than reliable work assistants.
ChatGPT is making its way into workplaces, with employees using it to optimize schedules, summarize meetings, or even draft emails, reports, and code. However, consumer AI’s primary limitation becomes evident here: it lacks context. These tools operate similarly to general search engines, relying solely on publicly available data rather than company-specific knowledge.
For instance, if you wanted to check how much vacation time you accrue monthly at your company, ChatGPT could only provide a general estimate based on publicly available information. When asked about Coda’s vacation policy, ChatGPT couldn’t provide an answer because it didn’t have access to that specific information. To obtain accurate details, you’d have to manually input your company’s policies into the chatbot.
Moreover, consumer AI lacks the ability to process dynamic, sensitive, or proprietary data. If you wanted to transcribe a call and transform key points into an organized email with action items, you’d need multiple tools. Otter could transcribe and summarize the call, but you’d then need another AI tool to extract action points and another to format them into an email—hardly more efficient than manually summarizing the meeting yourself.
What is Enterprise AI?
Enterprise AI is designed specifically for business environments. AI-powered apps like Notion, Atlassian, and Outlook assist employees in organizing work-related data more effectively than standard chatbots. However, these tools only work with data that users input and organize, making them a bridge between consumer and enterprise AI. While they offer secretarial support, they don’t provide insights or take action beyond what is explicitly programmed.
Many companies have implemented AI-powered chatbots on their websites in recent years. These bots, which fall under mid-level enterprise AI, are often LLM-based and use generative AI to answer customer queries. Since they are trained with company-specific policies and support information, they provide more tailored responses than generic AI tools. These bots can understand user inquiries, direct customers to relevant help articles, or escalate complex issues to human support teams.
However, the most advanced enterprise AI models go a step further by incorporating proprietary data. This enables them to provide highly relevant answers and actionable insights tailored to workplace needs.
The Power of Full-Context Enterprise AI
Imagine an AI tool that could retrieve company sales figures from before you joined, convert calls into actionable task lists, or identify the best colleague to answer a technical question. Such a tool would be far more useful than a generic chatbot that generates emails based on Wikipedia entries.
For enterprise AI to be truly valuable, it must be customized with business-specific data. High-level enterprise AI often employs Retrieval Augmented Generation (RAG) to add rich context to its LLMs. While they may resemble consumer AI chatbots, these tools integrate seamlessly with company databases, drawing from institutional knowledge in a way that would be neither secure nor feasible with consumer AI. For example, they can instantly retrieve vacation policies from the employee handbook, something ChatGPT simply cannot do without manual input.
Turnkey enterprise AI tools like Glean integrate with workplace apps and databases, acting as a knowledge hub for institutional data and expertise. These systems transform enterprise AI into an invaluable asset rather than just a content-generation tool.
ChatGPT is useful for general content creation, but enterprise AI solutions offer far greater utility when they are built with company-specific knowledge. Take Coda Brain, for example—this AI platform understands company data and empowers employees to act on it. By synchronizing with all workplace tools, Coda Brain creates an interconnected “company brain” that enhances productivity.
Specifically, enables communication teams to access impact metrics without relying on data teams, helps customer success teams track feedback, and allows employees to generate tasks and calendar reminders from meeting transcripts. Beyond organization, it sparks innovation by identifying potential clients or high-value sales opportunities. Instead of merely answering generic questions, it provides intelligent insights that drive business decisions.
The Key Difference: Context Matters
AI is only as effective as the data it can access. Relying on consumer AI for workplace needs often means spending unnecessary time copying and pasting proprietary information into an unsecured chatbot. With enterprise AI, businesses have greater control over data access, ensuring responses are both accurate and relevant to the organization’s specific needs.
Ultimately, enterprise AI is not just a chatbot—it’s a trusted and knowledgeable assistant, built to understand and enhance workplace operations.
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