No, AI Analytics Alone Will Not Tell You How Your Business is Performing

AI-driven analytics graphic representing partnership between ai and humans

AI-driven analytics is emerging as an invaluable business tool that can offer advantages like real-time insights and the ability to process a large volume of data at once. But they remain limited in their scope when it comes to certain tasks. Let’s discuss some of the pros and cons of AI-driven analytics and how this technology can act as a complementary strategy to traditional key metrics dashboard analytics.  

Back up: What IS AI-Driven Analytics?

Very simply, AI (artificial intelligence) is pre-programmed machine learning. It is designed to help users solve problems based on data inputs, predominantly by recognizing patterns and anomalies in those patterns. In its ideal form, it mimics a human voice and perspective, translating data and patterns into a message that is meaningful to us.  

Using AI for Business Analytics

There are, obviously, many advantages to AI-driven analytics:


One of the most important advantages to AI-driven analytics is the speed with which it can process data, and the sheer volume of data it can analyze. Where traditional key performance indicator (KPI) dashboards may analyze and present dozens of metrics, an AI-driven platform can process millions of metrics. 

Advanced Data Correlation

Furthermore, AI may be able to detect relationships between certain data that might otherwise have gone unnoticed by a business. Understanding these cause-and-effect relationships can have a profound impact on future business decisions. For example, linking a sudden decrease in ad conversion rates to a sudden spike in server latency can help you address the issue quickly and avoid further losses. 

Real Time Alerts

AI-driven analytics platforms are receiving and processing data in real time. This means business owners are alerted to important anomalies in data that might indicate a potential issue or help them take advantage of a sudden spike in interest. A KPI dashboard will alert you to certain issues, but you have to predefine those alerts in order to receive them. AI platforms can alert you to any and all anomalies in your data so you can address them quickly. 

Cons of AI-Driven Analytics

High Initial Investment

Implementing AI systems requires a substantial upfront investment in terms of technology, infrastructure, and skilled personnel. Even a small-scale dedicated AI team can cost as much as $320,000 a year! Small and medium-sized enterprises may find it challenging to justify these costs. 

What’s more, you will still require a human AI data consultant to help you implement, maintain, and interpret your analytics. AI algorithms, especially deep learning models associated with business analytics, are highly complex and notoriously lacking in transparency. Business owners may find themselves questioning the accountability of technology they are meant to trust without question. 

Biased or Incorrect Data

The accuracy and reliability of AI insights depend heavily on the quality of the input data. If the data is biased, incomplete, or inaccurate, the quality of AI results will likewise be compromised. This could lead to misguided decision making with potentially disastrous results.

Limited Problem Solving and Creativity

While AI excels at pattern recognition, it can only mimic human response and make predictions on existing data. In other words, it cannot create anything new. Businesses are, ultimately, dealing with humans. AI fails to take into account the nuances associated with the human experience and cannot offer new and creative solutions to business problems. It can alert you to new or unexpected patterns in your data, but it cannot make suggestions for what to do next unless it has already been done before. 

Balanced Approach to Analytics

As we have seen, there are pros and cons to AI-driven analytics for your business. At Impact by Insight, we feel the best approach is a partnership between AI and traditional KPI dashboards: AI can enhance our understanding of factors influencing their key indicators for example; or, it can help us choose which metrics to monitor in the first place. Meanwhile, a human data consultant can translate those metrics to you and design a dashboard that keeps you easily informed. 

If you are interested in streamlining your business analytics and learning how a dynamic dashboard can translate directly to your bottom line, call or go online today to schedule a consultation. 

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