Ultimate Guide to AI for Businesses

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it's hard to think of an area in
business that won't be impacted by
artificial intelligence already the
application of AI in the Enterprise is
profoundly changing the Way businesses
work companies are incorporating AI
Technologies into their business
operations to save money boost
efficiency generate insights and create
new markets ai-powered Enterprise
applications can enhance customer
service maximize sales sharpen cyber
security optimize Supply chains free up
workers from mundane tasks improve
existing products and point the way to
new products however Enterprise leaders
determined to use AI to improve their
businesses and get a return on their
investment face big challenges on
several fronts the domain of artificial
intelligence is changing rapidly because
of the tremendous amount of AI research
being done by companies research
institutions and governments there are a
multitude of AI use cases with
applications for practically any
business problem or opportunity and
Business Leaders must understand how AI
Works where AI can be used and where it
can't be here we'll go over the basics
of AI Technologies and what businesses
need to know for a deeper dive explore
our complete collection on all things
Enterprise AI by clicking the link above
or in the description below
the modern field of AI dates back
several decades when the term artificial
intelligence was coined in the proposal
for an academic Conference held at
Dartmouth College in 1956. pioneers of
modern AI range from British
mathematician and World War II code
breaker Alan Turing to the inventors of
the new Transformer neural networks that
promised to revolutionize natural
language processing but the idea that
the human brain can be mechanized is
deeply rooted in Civilization myths and
legends are replete with statues that
come to life many ancient cultures built
human-like automata that were believed
to possess reason and Emotion by the
first millennium BC philosophers like
Aristotle were developing methods for
formal reasoning that effort was built
upon over the next two thousand plus
years by contributors who also included
theologians mathematicians and Engineers
early notables strove to describe human
thought as symbols the foundation for
the AI work being done today by
computational scientists as well as
economists psychologists neurobiologists
and others
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what characterizes intelligence
especially in the context of work isn't
simple to pin down broadly defined
intelligence is the capacity to acquire
knowledge and apply it to achieve an
outcome the action taken is related to
the particulars of the situation rather
than done by rote getting a machine to
perform in this manner is generally
viewed as artificial intelligence at a
basic level AI programming focuses on
three cognitive skills learning this
involves acquiring data and creating
rules called algorithms to turn the data
into actionable information in AI
applications reasoning it gives AI the
ability to choose the most appropriate
algorithm among a set of algorithms to
use in a particular context and
self-correction which enables AI to
progressively tune and improve a result
until it achieves the desired goal
the types of AI that exist today
including AI that can drive cars or
defeat a world champion at the game of
Go are known as narrow or weak AI they
have savant-like skill at certain tasks
but lack general intelligence the type
of AI that demonstrates human level
intelligence and Consciousness is still
a work in progress including both what
exists now and what's envisioned for the
future here are the four ways AI is
categorized reactive AI can consider
huge chunks of data and produce a
seemingly intelligent output but it's
incapable of analyzing scenarios that
include imperfect information or require
historical understanding
limited memory machines can handle
complex classification tasks use
historical data to make predictions and
do other kinds of complex tasks such as
autonomous driving
theory of Mind AKA artificial general
intelligence is as yet unrealized AI
defined as capable of understanding
human motives and reasoning and
therefore able to deliver personalized
results based on an individual's motives
and needs and self-aware AI or
artificial super intelligence is a
further advancement that would be aware
not only of the mental state of other
entities but also of itself with
Intelligence on par with or perhaps far
surpassing human cognition
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the value of AI to 21st century business
has been compared to the Strategic value
of electricity in the early 20th century
without AI companies can't capitalize on
the vast wealth of their data stores AI
applications come in many forms machine
learning deep learning Predictive
Analytics natural language processing
computer vision and automation all of
which can help give companies a
Competitive Edge ai's ability to make
meaningful predictions to get at the
truth of a matter rather than mimic
human biases requires not only massive
amounts of data but also high quality
data cloud computing environments have
also helped enable AI applications by
providing the computational power needed
to process and manage all that data in a
scalable and flexible architecture ai's
biggest and more immediate impact on
business is its ability to automate and
augment jobs currently done by humans
labor gains from using AI are expected
to expand upon and surpass those made by
the use of current workplace automation
tools and by analyzing vast volumes of
data AI won't simply automate work tasks
but will generate the most efficient way
to complete them and adjust workflows on
the Fly
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most companies at this juncture are
looking to use AI to optimize existing
operations rather than radically
transform their business models AI use
cases span Industries including
Financial Services manufacturing
agriculture Healthcare education law and
Retail among others AI has made its way
into every business department for
marketing finance and HR to it and
business operations research firm
Gartner predicts AI will generate 2
million net new jobs by 2025. AI is
already augmenting human work in many
fields from assisting doctors and
medical diagnoses to helping call center
workers deal more quickly and
effectively with customer queries and
complaints in security AI is being used
to automatically respond to cyber
security threats and prioritize those
that need human attention banks are
using AI to speed up and support loan
processing and ensure compliance in
addition AI can potentially provide near
simultaneous monitoring of operations by
processing data in real time speed
product rollouts with shorter
development cycles and less time between
design and commercialization produce
better quality output on tasks by
reducing errors and increasing adherence
to compliance standards bolster talent
management by streamlining the hiring
process rooting out bias in corporate
Communications screening for top tier
candidates and providing personalized
service to job candidates and employees
and help organizations create and expand
business models and find new ways to
improve business processes
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one of the biggest risks to the
effective use of AI in the Enterprise is
mistrust many employees fear and
distrust AI or remain unconvinced of its
value in the workplace without increased
worker trust the business benefits of AI
won't be fully realized
and there are other risks that
businesses need to be aware of
errors AI can eliminate human error but
problematic data poor training data or
mistakes in the algorithms can lead to
AI errors and those errors can be
dangerously compounded because of the
large volume of transactions AI systems
typically process
ethics and bias companies need to guard
against unethical AI as well as AI bias
and be on the alert for unintended
consequences of using AI to make
business decisions
loss of human skills ai's expansion
could erode worker skills and should
raise questions about which key skills
Enterprises want to preserve in their
human Workforce
cyber security concerns hackers can use
AI to create more sophisticated and
successful attacks
and AI hallucinations these are the
delusional aspects of AI especially
exposed by the use of generative AI chat
Bots like chat GPT which sometimes give
users false information or simply make
things up
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many companies that have deployed AI are
realizing that figuring out how to do AI
isn't the same as using it to make money
it's also much harder to weave AI
Technologies into existing business
processes than to build or buy the
complex AI models that promise to help
optimize those processes as with any
emerging technology the rules of
implementation are still being written
industry leaders in AI emphasize that an
experimental mindset will yield better
results than a big bang approach start
with a hypothesis followed by testing
and rigorous measurement of results and
iterate using that approach these 10
steps can help ensure successful AI
deployments in your organization
first build data fluency
second Define your primary business
drivers for AI
third identify areas of opportunity
fourth evaluate your internal
capabilities and fill gaps as needed
fifth identify suitable candidates for
AI deployments sixth piloting AI project
seventh establish a baseline
understanding to measure AI success
eighth scale incrementally ninth bring
overall AI capabilities to maturity and
10th continuously improve AI models and
processes
foreign
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one of the characteristics that has set
us humans apart over our several hundred
thousand year history on Earth is a
unique Reliance on tools and a
determination to improve upon the tools
we invent
once we figured out how to make AI work
it was inevitable that AI tools would
become increasingly intelligent
the future of AI will be intertwined
with the future of everything we do
indeed it won't be long before ai's
novelty as it pertains to work in the
Enterprise will be no greater than that
of a hammer and chisel foreign
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