Three business solutions where AI adds value

With today’s advances, AI solutions have become readily available to developers. As a result, AI found its way into applications that did not require AI capabilities, and the solution ended up being less valuable. These days we have a better understanding of the pragmatic use of AI: when it will be useful and when it will not.

For AI business solutions to find value, they must have the right features for algorithms to work well and results to be great, as is the case when we use AI in solutions that include:

  • Business applications with potential patterns in large amounts of data.

Large amounts of data contain valuable information that can help businesses make informed decisions. These can be new patterns from new data or new patterns that emerge from what an AI engine already processes and learns over time. The more data that is analyzed and the more patterns the AI system identifies, the better the AI engine becomes.

Some business applications that can leverage potential patterns in large amounts of data are: Customer segmentation, Fraud detection, Predictive maintenance, Inventory optimization or Sentiment analysis.

  • The creation of new data and/or insights.

Recommendation engines create new data by capturing user interactions with products and services. This data can be used to refine recommendations and improve the precision of algorithms. In addition, by leveraging AI, online recommendation engines better determine who they are interacting with and can be more specific in suggesting products and services related to user preferences.

Online recommendation engines are used extensively in the retail industry to create new data and understand users/customers. These engines can increase sales, often 20% or more. Companies can use this data to track customer engagement, identify the most popular products, and gain insights into customer preferences and behavior.

By leveraging machine learning algorithms, companies can analyze user behavior and preferences to generate personalized product recommendations, enhance marketing strategies and improve customer experience.

  • An existing data set combined with AI’s ability to determine new meaning.

This is why AI exists in first use. AI algorithms can be used to analyze an existing data set and identify patterns and correlations that may not be immediately apparent to humans. By uncovering these hidden insights, AI can provide a new perspective on the data and help companies gain a deeper understanding of the underlying patterns and relationships.

Companies can combine their operational data with AI algorithms to identify inefficiencies and optimize processes. By analyzing data such as production rates, energy usage and maintenance records, AI can identify patterns and correlations that may indicate potential problems. This can help companies prevent breakdowns, reduce downtime and improve efficiency.

AI can also be used to analyze financial data and identify patterns and correlations that may indicate potential risks or opportunities. By analyzing financial statements, market data and other financial information, AI can provide insight into financial performance and identify potential growth opportunities.

It is well proven that combining an existing data set with the power of AI can determine new meaning. Which helps companies uncover valuable information and gain a deeper understanding of their operations, customers and financial performance. By leveraging Artificial intelligence algorithms, companies can make informed decisions, optimize processes and gain a competitive advantage.