Implementing AI: When and How?
In this special guest feature, Venkat Viswanathan, Founder and Chairman of LatentView, discusses how organizations determine when artificial intelligence (AI) should be utilized to amplify human intelligence. Venkat Viswanathan is the visionary behind LatentView Analytics with more than 18 years of experience in management consulting, technology, and global IT services management. He has spent the better part of a decade helping global businesses adapt to the business challenges created by disruptive new technologies.
The use of artificial intelligence (AI) applications in business is growing, but AI and machine-learning aren’t yet an efficient use for every business task. While there are many aspects of a business which can be automated, and should be automated, tasks that require judgement, prioritization, and trade-offs still require human intelligence.
Actions that require computation or organizing large quantities of data are all better handled by machines, and applying automated solutions that use AI will wipe out other traditional business models. Organizations accumulate massive amounts of data from business operations, social interactions, and sensors. Harnessing the power of this big data to build automated solutions and provide insights will lead to sustainable competitive advantage.
With that said, how do organizations determine when AI should be utilized to amplify human intelligence?
Is AI right for your organization?
It’s understandable that the distinction may become blurry, especially as AI technologies advance. To determine the best course of action, organizations should question whether the task at hand allows for repetition, high volume, a pattern, and low cost of mistakes. The tasks that satisfy these specific criteria are starting points for AI implementation.
When considering customer requests that require decisions to be made based on empathy, AI should be avoided. On the other hand, AI can be used to provide better responses to transaction requests by efficiently collecting historical chat data. Processes at the periphery of business, in which the cost of making mistakes is low, is also a perfect opportunity to apply AI.
