Creating the Best AI Product: Understanding the AI Brain, Relationship with Data, and Importance of Education

Over the past two years, AI has become a mainstream and very public conversation topic.

As you read this sentence, AI systems worldwide are analyzing millions of data points and making countless decisions. Elsewhere, AI bots are understanding simple language, providing critical analyses, and answering what-if scenarios in real time.

However, public concerns about the broader capabilities of artificial intelligence have led to hesitations about incorporating a public-facing AI bot or AI assistants.

Therefore, it is important to understand the current state of AI & data and learn how computational intelligence can be harnessed to create Business Intelligence (BI) solutions.

To understand Artificial Intelligence’s, well, intelligence, we must change the way we think about the concept.

A human is typically considered intelligent based on the vast knowledge they possess, yet it is not the same for artificial intelligence. Even though AI can be trained on millions of data points, it does not necessarily mean that the AI will do what is expected.

According to Jean Baudrillard, a French sociologist, “the sad thing about artificial intelligence is that it lacks artifice, and therefore intelligence.” Though AI is constantly improving its ability to transform information into action, it is still in its infancy.

If you hand a two-year-old a bottle, your expectation would be for them to drink from it, but, as parents can tell you, that child may throw it against the wall, use it to pet the dog, or try to sit on it. AI is the world’s smartest two-year-old.

In other words, artificial intelligence is capable of growing and possessing a level of common sense that humans reflect, but it is still in the initial stages.

Therefore, instead of viewing AI as an all-powerful, all-knowing entity, this realistic context can help the public view a product through the appropriate lens. By understanding AI’s comprehension power, businesses can develop the right mechanisms to utilize it appropriately and effectively. Here’s how Strategy is doing it.

By understanding the computational intelligence of AI, it becomes easier to distinguish, develop, and deploy it as a public-facing AI product.

As AI is limited by its ability to process, it is critical for the data input to be as accurate as possible. If you give AI bad data, you are going to get bad results. Here’s an example:

The Strategy AI operates like a virtual business analyst; it knows how to use and present information, and can understand columns, rows, and data points efficiently.

If you brought in a new business analyst, gave them a piece of paper with numbers and formulas, and asked them a specific question about the dataset’s history, would they be able to answer it? No, and neither would AI.If the datasets are not prepared for AI interactions, they will negatively affect the performance and accuracy. Therefore, adding proper column names, text hierarchy, data types, etc., allows the AI to properly understand the datasets.

When developing its AI functionality, Strategy has used the above-mentioned context to create a robust business intelligence platform that helps businesses gather, understand, and visualize their data.

Strategy’s AI is trained using industry-appropriate filtering conditions and conventional data types, allowing it to properly interact with a multitude of industries and data complexities without compromising customer data.

At no point is it trained using customer data itself. Instead, an updated version of the AI is deployed directly into each MCE environment and operates independently.

Furthermore, the AI specifically works off a single dataset, allowing users to control exactly what the AI is allowed to report on. This creates proper fencing at multiple levels and decreases the risk of the AI responding in an unexpected way.

Later updates to Strategy’s AI have added more flexibility, and the introduction of knowledge assets has helped the AI answer end-user questions with even more accuracy.

By granting the AI background details on the company, industry, and different keywords that end users may use for the same metric or attribute, Strategy’s AI bot can answer a variety of complex questions.

Ultimately, the best way to ensure you have the right AI product is to set the AI up for success.

Strategy’s AI tools are a great starting point, but to elevate them further, it is important to have the right data and knowledge assets in place.

Strategy offers its own AI certifications and partners with companies like Active Cyber, which are certified and trained to work with specialized AI business intelligence tools.

Discover how you can provide industry-leading AI experience for your end users powered by your data and Strategy. Get your certification today.