AI is making the world’s business by making the task automatic, create new products and services and to raise customer experiences. The recent rise of informal AI applications has rushed the tempo of AI. We live in a world where there is a vast amount of data gathered to get the compute power. The Machine Learning and data collected from science can modify industries through observation and prophesy. Making an strategy on AI is the best way to give inurement that our previous projects are delivered with the best value and that leads with good extension and speculation.
HOW TO BUILD A SUCCESSFUL AI STRATEGY?
STEP 1: DISCOVERY
The first step in building an AI strategy that convey value in learning .We will collect data about our organization that will help in taking blueprint decisions. Discovery is not tedious, it is the most interesting and energize phase. Due to lack of finding new things we should set a secure foundation for everything to follow. It is divided into two group:-organizational discovery and use-case discovery.
A-Organizational Discovery:-
Organizational Discovery covers all the details of the organization. It tells us how much large is the organization and the capabilities required to be in the organization .It is very important to understand that the organization will be owned by central IT or business units.
B-Use-case Discovery-
Use-case discovery is where the discovery method really gets interesting as we will be giving our own ideas for the solutions. Many information will be collection through interviews related to units of business. We should identify the problems and the points should be solved through AI.
STEP 2: REFERENCE ARCHITECTURE:-
A reference architecture consists of many diagrams and documents that gives different view in our system. Having different types of views can help the audience from different fields to understand the architecture –like of zooming in and out of a map. The reference architecture has the following elements:
CAPABILITIES:-
Our architecture should contain a diagram and a document that will describe the potential of the system.
SOLUTION LOOKING FOR PROBLEMS:-
Many Machine Learning projects are generated based on exterior ingenuity. For instance if someone has seen a good image rectifying the application at a show and aim to make a duplicate of that within the organization. Before enlarging a solution with the company we should find out how to solve the problem without the help of the organization.
INSUFFICIENT MONITORING AND OBSERVABILITY:-
A machine learning solution is the only organization that provides ethics to the business if we can clearly know the value of the business. Without observing and visibility we cannot report the success of the solutions and clarify our investments. In case we would lack the information which is necessary to upgrade the solution and solve the issue if they rise again.
BENEFITS OF BUILDING AN AI STRATEGY:-
1-We will be able to classify our capability in doing the projects based on the efforts done. After doing this we should make sure that the project has given a quick and clear win for the organization. After getting the success in the projects it helps to explain how to do more investments in the organization.
2-We can make decisions that will avert the aggregation of technical debt. An AI strategy contains architectural and the best guidance that will help the scientists and engineers to develop sturdy solutions. 3-Creating a strategy upfront will set the stage for fast implement the solutions if they are developed .We will be able to pay back the value of business as fast as possible .
DEVELOP AI STRATEGY 