Artificial
Intelligence is an inevitable part of our future and one of the most utilized practices
of AI is machine learning. Every business in every industry wants to use some
aspect of machine learning to get ahead in the competition. The growth of machine
learning is quite exponential. It’s also quite possible that you are already
using some form of machine learning in your everyday life even without realizing
its presence.
Machine
learning is simply a computer program performing some form of cognition like that
of the human brain. It is this aspect that gives the edge to machine learning applications
from ordinary computer programs. Using ML (machine learning) computers don’t
need explicit commands or instruction to perform a task that humans(us) want
them to. They achieve this by working on
the sample data and making predictions or decisions to carry out an assignment. Every application
of ML is revolutionizing industries in the ways we cannot imagine. In this article, we will investigate the top 3 applications of ML.
Personal Assistant
I say Hey
google at least 5 times a day, and I know many of us are in close contact with
Siri, Alexa, and Google. Personal assistant’s
success lies in its ability to learn your pattern of queries, collecting and retrieving
answers more suitable to your needs. You can also ask your assistant to set alarms,
read your schedule, send directions or even order something online.
With
natural language processing (NLP) which is based on machine learning, assistants
can be programmed to process and analyze human language input. The first step in this process is to let
humans communicate with the system in their own language. The second aspect
involves in personal assistant understanding the commands and performing the
required tasks.
According
to Grand View Research, the voice and speech recognition market hit $9.12 billion
in 2017. And It’s expected to grow at a compound annual growth rate
of 17.2% from 2018 to 2025. The bottom line here is that the market for personal
assistant driven by machine learning is growing. With more companies joining in to make their
services accessible with voice recognition ML-powered personal assistants are going
to take over most of our everyday personal digital chores.
Sales
By 2020,
30% of all B2B companies will employ AI to augment at least one of their
primary sales processes according to Gartner. AI/ machine learning has the potential to eliminate the time-consuming,
manual tasks of sales teams and help them spend more time with customers. With
ML, we could automate account-based marketing support with predictive analytics.
This would support account-centered research, forecasting, reporting, and would
be able to recommend things like which customers to upsell first.
Machine
learning technologies are good at pattern recognition and enables sales teams
to find the highest potential new prospects by matching data profiles with
their most valuable customers. Most AI-enabled CRM applications do provide the series
of attributes, characteristics and specific values that pinpoint the
highest potential prospects. This helps
the sales team to save thousands of hours a year in selecting and prioritizing
new prospects.
According
to Salesforces’ latest State
of Sales research study majority of guided selling adoption will accelerate based on
its ability to rank potential opportunities by value. Machine learning-based guided selling will be
based on prescriptive analytics that provides recommendations to salespeople of
which products, services, and bundles to offer at which price.
Manufacturing
According
to Deloitte. Machine learning improves product quality up to 35%
in discrete manufacturing industries and is only expected to grow up. McKinsey predicts that 50% of companies that embrace AI/ML over the
next five to seven years have the potential to double their cash flow with
manufacturing leading all industries due to its heavy reliance on data. The
bottom line is ML is providing insights on improving shop floor productivity thus
maximizing the product quality and production yields.
According
to a recent survey by Deloitte, streamlining the inbound supplier quality is the priority
in the manufacturing industry. Machine Learning /AI technologies can consume a
lot of data including audio and video making them the best quality analysts in
the production floor. Systems equipped with Machine Learning capabilities are
already preventing the breakdowns by quickly identifying the anomalies in the production
equipment or processes. Even better AI-enabled systems are predicting the
patterns with respect to failures using sensors enabling the industry to focus
on preventive measures to address that.
Machine
learning AI-powered systems are particularly helpful in automating complex tasks
consistently to improve throughput, energy consumption, and profit per hour.
Summary
While these
are some of the industries ML has revolutionized there are several more that
needs to be talked about. In business, Machine learning has a wide range of
uses. In fact, most of us interact with AI/ML in some form or another daily.
From the mundane to the complex, AI/ML is already disrupting virtually every
business process in every industry. As ML technologies proliferate, they are
becoming an imperative for businesses that want to maintain a competitive edge.
Talk to us to understand how we can support in finding that competitive edge
for your business.
Srivatsan Aravamudan - Sri
Senior Solution Consultant
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