My point of view on AI Adoption by CIOs as perceived from Indian Tech service. This is a purely personal viewpoint and not mapping to any specific company's strategic position.

1. AI ADOPTION
As seen from the Indian Outsourcing Market

2. Introduction
AI impact on IT Service construct is the most
talked about thing among the IT Sales enablement
team and among the senior leadership community
since 2016 onwards. I see a little has been
percolated into the delivery through contract sign
off . However from 2018 onwards this would strike
as a differentiator how one company can depend
on AI enabled modernizationand showing a
saving or augmenting value to the enterprise
customers.
In this document I have collated my thoughts and
visions on how AI will bring in changes in
Application Maintenance and development
contracts in next couple of years.
This is a forever—in-progress
document where I come back
once in a quarter and register
my revised opinion, This is a
purely personal view compiled
based on my reading , work
exposure and talking to friends
in the industry . This document is
no way a picture of a specific
company operation processes
and strategies

3. What are the asks from Enterprise CIOs
Domain centric AI solution
Image Analysis related
NLP Oriented solutions
Virtual Agents based solution
Value of AI LeverageVendor patronized AI solutions
as proof of concept
The conversation solutions for
information searching / CRM
NLP and structured data
analysis for conventional IT like
MES other operational purposes
Advanced analysis –structured
and unstructured
Strategic AI

4. The outsourcing companies and AI
Vendor consulted AI solutions
as proof of concept
The conversation solutions for
information searching / CRM
NLP and structured data
analysis for conventional IT e.g.
MES other operational purposes
Advanced analysis –structured
and unstructured
Strategic AI
When the existing vendors are position many
solutions as value propositions to maintain
the edge over competitive vendors. During
2018 this is the mostly observed trend .
Most of the enterprises are choosing to
opt for conversation solution as entry
point AI. At times these are mere
replacement of FAQ and sometimes as
a recommendation solution
Predictive analysis driven solutions are the
second popular items next to the VA .
However, these are mostly gift solutions
from the vendors . Enterprises are yet to
deploy any production solution beyond Biz
Analytics
In the enterprise IT domain the
non structure data riven AI is yet to
be explored. This area will be
leveraged more with the expansion
of IOT and physical security or
warehouse management
Some enterprises who are seriously considering
AI as strategic lever are often choosing to set up
their own CoE to work on the business solutions

5. AI Delivery Maturity Path
Point solution for value preposition
to initiate the customers in AI led
services
Data Platform solution where
multiple applications can be
integrated and AI is part of it along
with a strong delivery framework (
agile ,DevOps testing) and taking AI
Being part of customers Data
Strategy where AI will be a
component
The adoption of the new data
( Data Lake, real time ETL are
still at the inception phase )
The adoption of the new data
( Data Lake, real time ETL are
still at the inception phase
AI solutions on its own will not
deliver values to customer until
the time a proper data strategy
in place

6. Conclusion
■ IT outsourcing companies should focus more on the end to end data strategy set up
■ Vendor AI platforms are becoming matured and fewer Data Scientist and more data
engineers are required for Enterprise IT
■ Probably the key differentiators are presence of strong dev-test-release platform
testing methodology for the success of AI applications