The Promise Of AI
Do you as manager struggle with production planning and scheduling? As a bank employee, what if you could better predict potential credit and loan defaulters? What if the work that takes hours to get done by 50 employees, gets done within seconds by 1 person? What if your homes could ‘sense’ something being wrong such as a gas leak or unwanted intrusion and take preventive and precautionary actions unsupervised?
Enabling all this is the promise of AI
Today, AI is being used in a wide range of applications such as driverless cars, autonomous helicopters, virtual assistants and face recognition. Do these applications imply that AI is only for high tech firms such as Google, Apple, Amazon and Facebook? In this article we try to establish how AI is a notch ahead of Analytics and pitfalls that a regular enterprise can avoid in their AI adoption journey.
What exactly is AI?
Imagine a customer service application. Earlier, a customer interacted with a company through a phone and all the information about the customer’s likes and dislikes depended on data that was entered in the system by the customer service agent. If the system captured too much information, it would reduce the productivity of the call center and impact the customer experience negatively. However, a sparse information capture would reduce the richness of data and consequently the quality insights.
Simply put, AI is a decision-making technology. What is new though, is that apart from structured data that came from RDBMS, AI can also extract information from content such as images, videos, text and speech.
With AI, we can automatically analyze not just customer needs but her emotions as well. The interventions predicted by the AI application help us reduce the customer pain points precisely. This means that an enterprise would have higher number of loyal customers.