Can AI-driven Test Automation enhance Continuous Delivery?

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Can AI-driven Test Automation enhance
Continuous Delivery?
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Can AI-driven Test Automation enhance Continuous
Delivery?
Continuous Delivery is no longer a value
enhancing strategy, it is a much needed approach
in software development and release lifecycle. It
has substantially changed the way enterprises
test and launch their applications in a volatile
consumer ecosystem. The demand for Intelligent
Applications is on the rise. In fact, it is
predicted that almost all the applications will
be delivered with embedded intelligence. It
practically implies that these applications will
have the capability to scrutinize historical and
real-time data to deliver customized experiences
and results to the end-users by leveraging
Machine Learning technologies. Hence, testing
these applications will need a relevant Test
Automation strategy and a Continuous Delivery
plan. In the current Digital ecosystem,
consumers are swarmed by chat bots and virtual
assistants across diverse websites and
applications. These features are not only
automating basic activities, but are also
delivering enhanced and personalized experiences.
At a recent Google conference, CEO Sundar Pichai
opened the event by stating, Were   moving from
a mobile-first to an AI-first world. Hence, due
to growing business mandate and evolving consumer
preferences, the need to build such robust
applications is increasing by the day. AI within
Test Automation Artificial Intelligence (AI), as
we know, has been making strides across various
sectors and adding substantial value for
processes. In fact, Gartners Top 10 Strategic
Technology Trends for 2018, has listed
Intelligent Apps and Analytics in its list. The
post states, Over the next few years every
application and service will incorporate AI at
some level. AI will run unobtrusively in the
background of many familiar application
categories while giving rise to entirely new ones.
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Can AI-driven Test Automation enhance Continuous
Delivery?
It is equally challenging to conceptualize,
develop, deliver and maintain these applications
in an environment that demands constant updates,
enhancements, along with enduring cyber risks.
Eventually, the legacy applications existing
within an organizational set-up need to gear up
and keep up with the speed of these new
application structures as well. In order to build
robust applications that can deal with the
growing digital challenges and expectations, it
is important to leverage AI services/platforms
that can bring relevance for your business
objectives and support you to deliver
applications at speed. AI-based Test Automation
platforms enable development teams to manage
testing for Intelligent Apps, offer
enterprise-grade AI Infrastructure that is
scalable, along with upgraded AI tools that can
enable developers and data scientists to develop
applications efficiently, and as per their
specifications. Continuous Delivery with AI
automation tools is like agile testing that
happens in fragments and delivers results in
shorter but frequent cycles. These tools enable
testers to escape the tedious testing tasks and
take up high-level issues to deal with. Hence,
the overall focus shifts from being task-driven
to issue-driven. Automation is inevitable in a
Continuous Delivery scenario, specifically where
AI gets applicable across enterprises to
eliminate time-consuming tasks in the development
process. At the same time, collaboration between
teams is necessary, where Test Automation
programmers work closely with developers,
traditional testers, system architects, and
members from the technical team. Only with
scrupulous planning and cohesive outlook,
enterprises would be able to effectively leverage
the power of AI-based test automation platforms
for Continuous Delivery.
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Can AI-driven Test Automation enhance Continuous
Delivery?

How effective can AI Testing get for Continuous
Delivery? Perceiving Software Testing in any
potential way is fathomable when we map it
against its benefits and practical implications.
Testing ultimately enables developers to figure
out if their applications practically work in the
real world, and as expected. Ultimately, it helps
developers to effectively identify issues and
address them within demanding time gaps. Equally
critical is continuous delivery, which enables
enterprises to deal with glitches within their
application, rectify them, and roll out the
application without any downtime or gap in
experience. Read Full Blog at
https//www.cigniti.com/blog/can-ai-driven-test-a
utomation-enhance-continuous-delivery/
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