AI in Business: Adoption Trends, Skill Shortages, and Implementation

This report examines the adoption of artificial intelligence (AI) within business organizations, highlighting its transformative impact on business processes and customer engagement. It reviews prior literature to analyze AI adoption trends, noting that proactive AI adopters experience higher profit margins. The report emphasizes the rise in AI adoption across various industries, driven by the need for hyper-personalized services and the potential for significant revenue growth. It discusses AI's application in driving customer engagement through conversational marketing and virtual assistants, as well as its role in addressing skill shortages within enterprises. The report also outlines practical ways for businesses to adopt AI, including understanding AI capabilities, identifying problems AI can solve, prioritizing concrete values, acknowledging internal capability gaps, and setting up pilot projects with external experts. Ultimately, the report underscores the importance of organizational flexibility and cultural change in successfully integrating AI to develop frictionless customer experiences and agile back-office procedures.

Running head: ARTIFICIAL INTELLIGENCE WITHIN BUSINESS ORGANIZATION
Adoption of artificial Intelligence within business organization
Name of the student:
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Author Note

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Discussion of Adoption of artificial Intelligence within business organization:
The artificial intelligence has been changing the way the businesses are conducted. This has
been also determining the daily of customers. Further, it has promised to boost various profits and
different digital transformations. In the following study various prior literatures is studied to analyze
the adoption of artificial intelligence at businesses.
Literature review on prior studies:
It has been seen that AI has been the game-of-few-players. Here various digital frontiers such
as Facebook, Microsoft, Microsoft, Amazon and Google have been incorporating technology of AI
to their various business processes. This has been mainly because of human-level performances and
the capability in predicting and automating high quantity of data. AI-based algorithms in long-run
have been served as the new general purpose as the process of invention. It has been reshaping
innovation processes as per as Steels and Brooks (2018).
The proactive AI-adopter has been seeing notably higher margins of profits. This has been as
compared to various non-adopters. Further, they have been also positive regarding future and have
been predicting grow and taking advantages even more as AI has been maturing.
Cohen & Feigenbaum (2014) highlighted that adoption of AI has been rising. As per the
current article from Forbes, 80% of the businesses has been inventing at AI. Mark Hurd, the CEO of
Oracle has agreed and has been betting the future of Oracle on the fact that most of the enterprise
data has been autonomously within 2020. Hurd stated that the future has been autonomous.
However, AI has not been mature enough and it is not needed at the niche category. Further, there
have been various practitioners and experts as it is the time to fetch how the innovation has been

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affecting the business. Moreover, there has been disrupting of business giving up on the
competition.
Rise in AI adoption around every industry:
The statement of Hurd is interpreted by Moro, Cortez and Rita (2015). They state that the
Oracle should be utilizing the machine learning for making the data integration and apps, analytics
and identity and system management autonomous. Further, Trcatia, which is a popular market
intelligence firm, has been focussing on human interactions with the technology has been releasing
researches to value of AI for the future days. Their report has shown that the quantitative analysis
has been providing market opportunities for segmenting, sizing and forecasting numerous AI use
cases. Further, Partanen, Jajaee and Cavén (2017) has pointed out that the rise in tide of AIU
adoptions around various industries has been driving notable growth for the following decade with
various AI software potential revenues to rise from $3 billion at 2016 to $90 billion within 2025. The
forecast has been a notable upgrade of the previous projection of Tractica, for the market revenue of
AI. This was been published at the second quarter of 2017 because of developed outlook for various
specific use cases around various businesses. Further, Walczak (2018) mentioned that as compared
to last few years, the AI market has begun to solidify across various real-life applications under the
speed of change that has been faster than before.
This is because the technology providers and start-ups have been rushing to develop targeted
niche solutions and platforms to solve particular problems of enterprise. Here, AI has been the key to
the way how consumer internet agencies have been operating at present as argued by Valter,
Lindgren and Prasad (2018). This has been to roll out various hyper-personalized services as
followed by the strategy of AI-first. Secondly, the rest of the market at government and enterprise
sectors has been catching up in adopting AI. However, it has been needed to understand the value

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that includes depth and breadth of various use cases along with various technology choices across AI
and its implementation methods.
Application of AI in driving customer engagements:
Boyd and Holton (2017) analyzes that the enterprises has not comprised of any specific
choice. However, in order to deploy AI, it has been not a longer strategy for the business. The
business has been acting now and applying various natural applications that have been having closer
interaction with customers. However, it has been remaining in control of the businesses’ futures. As
per as survey done in the article of Hengstler, Enkel and Duelli (2016) 40% of the organizations has
been using AI till 2016. However, this would be rising to 60% within 2018. It has been driving
customer engagements and collecting information for business for better understanding the
customers that needs to predict the needs. The businesses have been using AO regarding
conversational marketing for driving customer engagements and create loyalty for brads. This
impacts the bottom line positively. Further, people have been turning to be comfortable with various
virtual assistants.
Moreover, the human civilization requires making sense how to use this innovation. This is
helpful to languages, terminologies and what they actually needs.
Rise of AI integrations:
The tech stack of all companies has been distinct in managing various interactions of the
various technologies. It has been rousingly significant. According to Wu, Chen and Olson (2014),
any business providing software strengthens various relationships with customers through the mobile
messaging platform of the company. The organizations needed to stay relevant has been needed to
adopt the technology in some for or the other as they never need to get disrupted. Further, this tool
requires utilizing in wise manner. However, the reality is that the AI has been just a single

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component of larger solutions. Besides, AI has been unable to create real values till they get totally
integrated. The organizations requires to decide the most effective use-cases for AI that has been
possessing largest effect.
Application of AI in skill shortages:
Lu et al. (2018) highlighted that AI at its present form has been the ability to compensate the
notable deficiencies within enterprise, especially across skill shortages and delivering top
experiences of customers. Further, AI has been addressing various questions of various skill
shortages and AI powered that has been rousingly vital. However, this has been not in terms of
quality of service organizations can supply. However, this has been in the context of rising skill
shortages at the industry.
As per the current IFS Digital Change Survey of 150 decision makers in service industry,
retaining, training, recruiting various skilled technicians are rated to be the highest inhibitor for
growing service revenues. This has been over 30% of the business that has been claiming to feel
totally or slightly unprepared for dealing with various deficits in skills. Moreover, AI has easing the
challenges of various uncomplicated queries. This has been driving notable potential for business to
connect to voice assistants that is powered by AI. This has been beyond the scenario of enterprise
software having the abilities like scheduling optimization engines, self-service diagnostics for
appointing various slots automatically. It has been making business lighten and effective for the
burden for stretched contract centre agent workforce.
Further, the final though is derived from the article of Iafrate (2018). They stated the CEO
and founder of eXalt solutions revealed the speed if current business many times quicker than the
current businesses that has been a decade before. They have further analyzed that the highest
challenge at present has been to help customers know how to utilize AI and then digitally transform

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the business smartly. The customers are needed to be stopped from doing businesses. It has been
vital that the organizations have been taking various actions in leveraging the AT for developing
various frictionless experiences for customers and then agile back those office procedures.
Ways to adopt AI:
Getting familiar with AI:
The business must be taking some time period to understand what the current AI can be able
to do. Here, the accelerators have been offering start-ups with various arrays through the
partnerships with various businesses at the AI domain. Further, one must be taking benefits of
resources of different online data that has been available to familiarize the primary ideas of AI.
Some of the distant workshops and various online courses provided like Udacity has been an easy
way to start AI and raise the knowledge of various areas like predictive assessment under the
business.
Determining the issues to be solved by AI:
Once the basics are fastened, the following step for any business has been to start exploring
various ideas. They must be thinking about how AI can incorporate AI abilities to the current
services and products. Here, more significantly, the organizations have possessed various aims in
mind about particular use cases. This can be solved by AI for various business problems and then
provide demonstrable values. As one works with any company, they start the overview of the
primary technology problems and programs. Copeland (2015) has shown hoe processing of natural
languages, identification of images has been fitting to products commonly under workshops of any
kind of management of business. Here, the specifications have been varying across industries. For

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instance as any company performs video surveillance, they are able to capture numerous values
through adding ML to the process.
Prioritizing concrete values:
Then the potential business and economic values of various probable AI implementations
must be determined. Fan et al. (2018) states that in order to prioritize, the various dimensions of
feasibilities and potential is needed to put into 2*2 matrix. Moreover, this has been helpful to know
and near-term visibilities for the financial values of the business. To perform the stage, business
requires recognition and ownership from various managers and different level of executives.
Acknowledging the internal gap of capability:
There has been difference between what has been needed to be accomplished and what
organizational ability is needed to have under the given system. Russell, Dewey & Tegmark (2015)
states that the business must be knowing what has been capable of and what this has been from
business and technological process perspective proper launching the full-brown AI implementation.
However, it has been taking a long time to do so and there is the scope with AI in changing the
strategy and innovation has a strategic element of the equation. However, they have not possessed
any well-established procedures already. In order to address the processes, the internal capability
gaps has been meaning the identifications of what has been needed to acquire and various processes
that is needed to evolved internally prior they are achieved.
Bringing experts and setting up pilot projects:
As the business is ready from technological and organizational standpoint, it is the time to
create and integrate. Huang and Rust (2018) revealed that the most vital element of here has been to

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begin with small and have various goals in mind. This has been most significantly to be aware of
what is known and what one can know about AI. It is the place where bringing of external experts
and various AI consultants has been invaluable.
The above discussion has showed that expectations regarding AI or artificial intelligence has
been higher and determined what the current businesses has been actually doing. Here, the aim of the
report has been to provide a realistic basis that must be helpful for companies in comparing the AI
efforts and ambitions. Here, the study has shown that gap between execution and ambition has been
high for most of the businesses. The implications of AI regarding organizational and management
practices has been effective. Though there have been various models to organize for AI has been the
organizational flexibility. That has been the flexibility that has been the centrepiece across around
them. Thus for the huge companies the change of culture has needed to deploy AI that can be
daunting, as per various articles that are demonstrated before.

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