Artificial Intelligence and Machine Learning Part 13

© DataMites™ | Feb 2019 | CII – Confederation of Indian Industry | AI Transforming Business
Artificial Intelligence and
Machine Learning
Accredited with IABAC™
( International Association of Business Analytics Certifications)`
Artificial Intelligence (AI) and Machine Learning (ML) Training Courses

Investments in AI region wise
• Among countries, US investment in AI ranked first at $15 billion to
$23 billion in 2016, followed by Asia’s investments of $8 billion to $12
billion, with Europe lagging behind at $3 billion to $4 billion.

BCG Insights
• China and US are two countries leading AI
• China, has been explosion of applications of security and survelience
taking advantage of AI and computer vision technologies.
• US is focussed the use of AI around consumer use cases of big tech
companies such as Amazon, Google, Apple, Microsoft.
• China has more commercialization of Ai in China
• AI M&A is based on two trends 1. Acquiring Teams to get on-boarded
even if there is no specific business yet (more larger tech companies)
2. Acquiring for Data, AI assets / Tech Assets.

May 2018
• Goldman Sachs is reportedly automating its investment banking operations and
has revealed in a report that almost half of the 127 tasks needed to prepare for
an IPO can be done by algorithms as well.
• During the past few months, Goldman Sachs has invested extensively in artificial
intelligence and has hired top AI executives. The investment bank is working to
establish a “center of excellence to drive machine learning and artificial
intelligence strategy and automation”.
• Sachs has maintained that the arrival of technology will not reduce the
headcount; in fact, it will free bankers to focus on tasks like shaping marketing
strategy and spending time with clients.
• Investment banking is a highly paid job and automating it even partially will
reduce company’s expenses manifold.
• The bank is also moving ahead with plans to set up what appears to be the first
Bitcoin trading operation at a Wall Street bank.

62%
Potential Incremental Value
from AI Over Other analytics
Techniques

AI - Potential Value Creation
• An analysis of the value derived from McKinsey use cases[1] suggests
that AI can generate considerable value.
• Neural networks and convolutional neural networks—together have
the potential to create between $3.5 trillion and $5.8 trillion in value
annually across nine business functions in 19 industries.
• This constitutes about 40 percent of the overall $9.5 trillion to $15.4
trillion annual impact that could potentially be enabled by all
analytical techniques
[1] Notes from the AI frontier: Applications and value of deep learning. Discussion Paper - McKinsey Global Institute - April 2018

AI’s Potential impact is greatest in
Marketing and Sales, Supply-Chain
Management, and Manufacturing
based use cases

Ch 1: Build Your AI Business Case
• Gartner estimates that by 2020, AI will be a priority for more than
30% of CIOs.

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Artificial Intelligence and Machine Learning Part 13

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