Maximizing Business Value: The Evolutionary Path of AI from Descriptive to Prescriptive !

AI has been a crucial buzzword now and it has already started playing a crucial role in core operations and business strategy and it will only become more vital in the years to come. AI in one of the top-of-mind items for any CXO’s agenda and early adoptions of innovations in AI will lead to significant competitive advantage to any organization.

This article focuses on how the journey of an AI adoption should look like and before making any huge investments in AI, every organization should explore these 4 phases of AI. It’s a journey which any organization would navigate to improve their maturity in AI adoption and drive business value.

Descriptive AI -> Diagnostic AI -> Predictive AI -> Prescriptive AI

Descriptive AI

In simple words, Descriptive AI focuses on “What happened?”

Descriptive AI involves solutions that can analyze historical data to describe what has happened. These solutions are designed to identify patterns, trends, and relationships within the data, empowering organization to gain a better understanding of historical events and occurrences. Future decisions can be based on the analysis.

Examples:

• Sales and inventory reports, analyzing past buying patterns.
• Production performance
• Analyzing spending patterns

Diagnostic AI

In simple words, Diagnostic AI focuses on “Why did it happen?”

Diagnostic AI involves solution, identifying the causes behind events or behaviors observed in the past. AI systems that analyze factors contributing to a specific anomaly, helping to diagnose the root causes of problems.

Examples:

• In healthcare, diagnostic AI involves analyzing medical data, such as images, scans, and patient records, for the purpose of diagnosing diseases and conditions, accelerating clinical trials.
• In the automotive & manufacturing industry, diagnostic AI can be used for identifying issues in equipment / vehicles by analyzing sensor data and performance metrics. This helps in preventive maintenance and reduces the likelihood of unexpected breakdowns.

Predictive AI

In simple words, Predictive AI focuses on “What will happen & when?”

Predictive AI solutions analyze historical data and identify patterns, trends ad correlations that can be used to make predictions about future events or outcomes.

Examples:

• Demand forecasting in any industry, maintenance prediction in manufacturing industry, customer behavior analysis, fraud detection and so on.

Prescriptive AI

In simple words, Prescriptive AI focuses on “What should be done to prevent? & what should be done to solve?”

Prescriptive AI solution not only analyzes data and provides insights but also suggests actions or recommendations based on the analysis. Unlike descriptive and predictive analytics, which focus on understanding past events or predicting future outcomes, prescriptive analytics goes a step further by recommending specific courses of action to achieve desired results.

Examples:

• Optimize energy consumption in buildings, factories, and other facilities by recommending efficient usage patterns, adjusting settings, and suggesting equipment upgrades.
• Improve manufacturing efficiency by recommending adjustments to production schedules, maintenance activities, and quality control processes based on real-time data and historical performance.

Domain wise use cases

Use cases across these AI stream would be countless and would depend on the imagination of any organization to drive competitive advantage, however, have tried to list few. Pls note: the real-world application and some of the use cases may also have an overlap across streams.

Any feedback, pls provide your comments / suggestions -- Mehul Chopra

My another article on - "Empowering the Intelligent Enterprise: Harnessing the power of AI in Revolutionizing Business Ops"

***Pls note**** : These views are my own and not the views of my employer