‘Need to find two-way communication to include technology & data’
Vishakha R M, Managing Director & CEO, IndiaFirst Life Insurance, spoke about ‘AI in Marketing: Pros & Cons’ at the e4m Screenage Conference 2022
“Look at AI from the perspective of a CEO who is signing off on the budget,” said Vishakha R M, Managing Director & Chief Executive Officer, IndiaFirst Life Insurance, while kicking off her talk on ‘AI in Marketing: Pros & Cons’ at the e4m Screenage Conference 2022.
Sharing her experiences, Vishakha said: “On a personal level, I am fascinated by AI. I started working in the pre-digital era. We had a ledger, we used to have notes in banks and you had to consolidate balance sheets taking big papers with columns and plot numbers to total.”
Vishakha asked marketers presented in the room about driving results from AI. She said, “I am as fascinated with AI as a child with a toy. You say all this is fine but how are you going to get any results? What are we saying about the way so-called AI models are implemented? I want to differentiate here between what we are calling data modelling, which has nothing to do with AI.”
Citing an example of using data to define a tree, she said: "What are we seeing about the way so-called AI models are implemented? I want to differentiate between what we are calling data modeling which has nothing to do with AI, but the ability to define the tree to the last mile possible. And as detailed as you can make a tree is as detailed as the app that gets generated, this has nothing to do with AI.”
“Are we really using AI models which are interactive in real-time. That is a big question mark that I have got. Are we actually spinning off just data models that are logic and tree as AI? I see more and more data models beings spun off as AI. We do not have real AI. This is from the perspective of somebody who's looking at the ROI,” she added.
“Can you change your communication because that's what data scientists will give you? Data scientists are giving that last granularity but I don't see marketing able to gear up like that I don't see the product. Do we even have the capacity to really take so much data and dump them into 3 broad categories that we understand? Data science modelling is not cheap and if you get it wrong the cost of misalignment is very high.”
“If all of you are going to work around a lot of data, please find two-way communication with your technology and your data scientist because if that not happens the model is not going to be a successful model.”
Her last concern was about mobile marketing. “My big concern is we are not measuring dissonance.”
“I think we need more work from the marketing and tech team for AI in marketing to be a reality,” she concluded.
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