When it comes to data analysis, the use of AI introduces a unique dynamic, distinct from traditional software. While traditional software offers consistent responses, AI data analysts provide a more human-like interaction. They can understand your instructions or questions, but like humans, they may occasionally misinterpret. This blend of predictability and human-like interaction is a key advantage of AI data analysts.
Embracing the Human-Like Interaction
Interacting with AI data analysts, much like with humans, can present challenges, especially with complex data. However, the standout advantage of AI data analysts is their rapid iteration time. In a matter of seconds, you can ask a question, receive an answer, or redirect your query to another AI analyst. This level of speed and efficiency is a rare luxury with human analysts, who may be tied up with other tasks or simply unable to work as quickly.
Think of the Experience as a Team of Ultra-Responsive Data Analysts
When communicating with humans, your question might be interpreted differently than you intended. This is a common occurrence and can also happen with AI data analysts. Sometimes, both humans and AI might not provide the desired answer on the first try, necessitating multiple attempts or rephrasing of the question.
With human analysts, this iterative process can take hours, days, or even weeks, depending on their availability. In contrast, AI data analysts can iterate and provide answers in about 10 seconds per attempt. If you get frustrated with one, you can immediately switch to another. There is no best AI model for this type of work, at least not yet. They all have their strengths and weaknesses. Some are better at certain types of questions, and you won’t hurt their feelings by switching to another one on the fly. Because of this, Xpress Analytics believes it is critical to provide users access to multiple AI analysts.
This switching efficiency allows you to obtain the information or insights you need much more quickly than if you are restricted to one model or one company’s family of models.
Overcoming Query Hurdles
If you receive a response resembling a query error, it simply means the AI failed to generate a valid query. In such cases, try rephrasing your question or asking it again up to two more times. Often, the AI will understand and provide the correct answer on the second or third attempt.
If you do not get a valid answer after three attempts, it is likely that this particular AI analyst cannot answer your question. The best approach, then, is to try asking another AI analyst or rephrasing your query. You will soon learn to iterate quickly and naturally through your AI team when necessary.
The Power of Adaptability
Once you get accustomed to the AI experience, you'll be able to perform complex data analyses and generate ad-hoc reports in minutes, sometimes even under a minute—tasks that might otherwise take hours or require days or weeks of calendar time when you are waiting for someone else to deliver them. The result will be faster and more informed decision making.
So, Where Are My AI Analysts From?
After extensive testing, we decided not to limit you to the capabilities of one AI company or model. There is not currently a clear winner for all situations, and they are improving (usually - sometimes they may take a step back) all the time. Xpress Analytics currently utilizes the five major AI companies (OpenAI/Microsoft, Anthropic(AWS Investor), Google Gemini, Meta, and Mistral) to provide users with a comprehensive and versatile data analysis experience. We continuously test and monitor the AI models and curate the list of available models to the best performing.
By leveraging the strengths of different AI models, you’re equipped to handle any data challenge that comes your way. Welcome to the future of data analysis, where your team of ultra-responsive AI analysts is ready to assist you at the speed of thought.
