Artificial IntelligenceOpportunities & Challenges

Balaji Gopalakrishnan, American Family Insurance

What is AI?

1995

Now

”We think of AI as understanding the world and deciding how to make good decisions. Dealing with uncertainty but still being able to make good decisions.” Peter Norvig

Director of research Google

History of AI

Source: NVIDIA

AI Opportunities

Business area specific Identify AI projects and prioritize them Establish connections between projects

Foundational Benefit from economies of scale Involves highly cross functional team work

Foundational AI Opportunity – Chatbot Platform

PL Agent Bot Customer Billing Bot

Claims Bot

Scalable and robust platform with components that can be easily leveraged

Leverage learnings and bring more synergy between different bot projects

Focus on intent mapping, knowledge engineering, information retrieval, etc..

Intent Engine

Reporting & Analytics

Security & Authentication Platform Architecture /

Chatbot engine

Dialogue Management

Multi-Channel

NLU/NLP

Foundational AI Opportunity – Dark Data Store (DDS)

‘Information assets that organizations collect, process and store in the course of their regular business activity, but generally fail to use for other purposes’ - Gartner Inc.

Data types – images, scanned and other documents for underwriting, police reports, etc, voice samples and transcripts, video files, free form text like notes, chat logs, sensor data, etc..

Index and tag dark data assets using ML/NLP/Deep Learning etc..

Make dark data fully searchable along with enterprise data store

Image Credits: Multiple sources from Google images

Foundational AI Opportunity – Cognitive BI

Chat with data - ask business questions on data in natural language (voice/text) and get meaningful answers

Learn from previous responses to queries –use past interactions to identify the optimal delivery mechanism

Offers additional insight from prior queries from ‘similar’ users

Reduces dependency on tech teams and data scientist

BI

AI

Foundational AI Opportunity – Labeling Platform

Cold start problem for training machine learning models

Can use Mechanical Turk, CrowdFlower, etc.. to label data

Have a formal way for SME/employees (underwriters, claims adjusters, sales, call center, etc.. ) participate in the AI data labeling process

Great opportunity to create AI awareness in the organization!

Image Credits: Multiple sources from Google images

AI Adoption Challenges

Business model redesign

Lack of resources/time

Lack of collaboration

Drive the adoption of AI models

and technologies

in the company

AI Center of Excellence (COE)

AI COE

AI Strategy

AI Models

AI Framework

AI Infrastructure

AI Business Solutions

Customer Engagement

Risk/Underwriting

Claims Handling

Sales Operations

Lead the development of a longer-term vision/strategy for AI-based evolution

Champion AI awareness within the organization

Establish best practices and alignment of AI projects throughout the organization

Lead key AI initiatives with the business