6 Step Guide for CIOs to Implement AI for Business Transformation
Artificial Intelligence (AI) environment has risen from data scientists to reach the boardroom as a pre-curser to digital transformation. Clayton Christensen, author of The Innovator’s Dilemma, a disruptive technology adds to the premise writing AI “enables new markets to emerge” to disrupts an existing market status-quo.
The adoption path of AI needs a well thought out strategy to evolve in response to the dynamically changing technology parlance. These changes are well equated to the waves in an ocean, where either CIOs need to learn how to ride the wave or be overpowered by its force.
The guide to implementing AI is not a piece of cake, here is a blueprint guide, CIOs may consider implementing Artificial Intelligence in modern enterprises-
Artificial Intelligence defined in business parlance are algorithms that imitate human thinking applying to compute systems using logic, decision trees and if-then rules. AI brings pattern recognition and predictive maintenance from big data to provide intelligently and help businesses make strategic decisions.
Algorithms used in this early type of AI are reactive and lack memory. This implies that for a specific input, the output will always be the same. Machine learning models which use this type of AI are effective for pattern recognition and simple classification tasks.
Limited Memory Machines are built on the concept of how the neurons connect and the human brain works. This type of machine “deep learning” is programmed to handle complex classification tasks and use historical data to make predictions. it also is capable of complex tasks, such as autonomous driving.
Reinforcement Learning AI is capable of understanding human intent and reasoning. Reinforcement Learning AI can forget its previous algorithms and re-learn to deliver personalized results-based business requirements. Reinforcement Learning AI is also referred to as artificial general intelligence (AGI), it can contextualize and generalize information, and extrapolate knowledge to a broad set of problems.
