Exploring the Impact of AI on Business Analysis Practices (Fall 2024)

Desklib provides past papers and solved assignments for students. This report analyzes AI's impact on business.

ARTIFICIAL INTELLIGENCE

TABLE OF CONTENT
LIST OF FIGURES....................................................................................................................2
ABSTRACT...............................................................................................................................3
RESEARCH APPROACH & METHODOLOGY....................................................................3
DESCRIPTION OF THE SIGNIFICANT TREND IDENTIFIED...........................................3
REFLECTION & COMMENTARY ON THE IDENTIFIED TRENDS..................................6
IMPACT OF THE TREND ON BUSINESS ANALYSIS PRACTICE..................................10
CONCLUSION........................................................................................................................10
REFERENCES.........................................................................................................................11
LIST OF FIGURES
Figure 1: Artificial Intelligence Domain....................................................................................3
Figure 2: Artificial Intelligence relationship with Big Data......................................................4
Figure 3: RELATIONSHIP BETWEEN AI, ML & DL............................................................5
Figure 4: Machine Learning Process Flowchart........................................................................8
Figure 5: Oppurtunities in Artificial Intelligence.......................................................................9

ABSTRACT
Artificial Intelligence is trending in technology as it’s a promising market and also gives
many companies new opportunities and interesting prospects. It is basically a term used to
describe how the computers are programmed to show intelligence just like humans such as
learning and problem-solving. AI is making businesses transform in a way that they possibly
could never have imagined. There has been widespread in analytics investment and outcome
predictions in recent years. AI techniques and technologies are still not in use that much as
only the large companies are able to invest in the expertise that is necessary. The analysis
with the use of prediction has helped companies in solving very complex problems and
saving lots of money. Over the traditional automation, artificial intelligence is clearly at an
advantage as businesses have so much to lose or gain whether it is increasing productivity
with several improvements or increasing the sales process.
Figure 1: Artificial Intelligence Domain
RESEARCH APPROACH & METHODOLOGY
The main aim is to identify a significant trend in business systems analysis. All the
information in this report was collected from the case studies of several companies, several
websites providing solutions and Gartner and google scholar reports. Business journals,
articles based on AI with business systems and forester articles based on research.
DESCRIPTION OF THE SIGNIFICANT TREND IDENTIFIED
Artificial Intelligence made lives of the people very easy and the businesses are coming up
with new ideas to make use of the Artifical Intelligence so that the processes can be made
easier and generate more revenues. According to the Forrester research report, 2019 will give

rise to new digital workers with increased and massive competition for Artificial Intelligence
skilled data professionals. The Forrester report also noted that the 22 big data technologies
have flourished. Their trend was similar to what was predicted. There has been an increase in
popularity as well as the overall effectiveness of the AI based chatbots in recent years. Of all
the technologies flourished, there are some which have the most important for the businesses
in the upcoming years.
ARTIFICIAL INTELLIGENCE ON BIG DATA
With the help of the real-time methods & the algorithms, businesses are making the
use of the data to make decisions. AI helps the business to break down the large data
and then use it for different purposes. Deep learning & machine learning are also a
part of the artificial intelligence which helps in improving the predictive analysis and
then business can easily offer the users whatever they want or are looking for.
Figure 2: Artificial Intelligence relationship with Big Data
ARTIFICIAL INTELLIGENCE ASSISTANTS
The most common and used Artifical Intelligence technologies are Siri and Alexa. So,
the time is not far when the digital assistants will make their way to the business
offices. With the help of the voice assistants, the business can be benefited on a larger
scale.

Figure 3: AI voice assistant google
Artificial Intelligence was one of the most important trends in the Gartner 2019 Strategic
Technology trends report. The combination of the AI with automation, it interacts with its
environment. AI can also be defined as the science which aims to make machines to do what
is generally executed by human intelligence. It’s a fact that AI affects our lives very much as
these things are evolving our way of interaction with the data and analytics management. The
real-time data analysis demand is increasing and with the IOT i.e. Internet Of Things coming
into play it's providing an amount of data which is uncountable and hence will promote the
statistical management and the analysis on a priority.
Figure 3: RELATIONSHIP BETWEEN AI, ML & DL
There is a wide range of issues which are needed to be solved as the current business world is
getting complicated day by day. Every business has some collection of data and its
procedures and this stored data will be used to solve various issues. In the Gartner report, it
predicts that deep learning & artificial intelligence will become the most common and widely
used methodologies for new data science apps. The prediction done by the IDC shows that
the overall expenditure on the artificial intelligence as well as machine learning will increase

to somewhere around 380% from 12 billion dollars to 58 billion dollars in the years ranging
from 2017 to 2021.
AI will bring some changes in the report making process. It will certainly make clients invest
less time in planning the reports and giving them extra time to utilize the time to make their
decision making better. By 2021, Gartner predicts that around 75% of all the reports that are
prebuilt will be conveyed. Around 61% of the enterprises said that machine learning and AI
will be the most crucial data initiatives to fetch in the coming next years. If we look at a
greater extent then automation with the help of artificial intelligence can actually increase the
overall productivity development by 0.8% to 1.4% every year on a global basis. As artificial
intelligence capability are getting better, they make their own set of problems that must be
solved to take the full advantage. When conventional analytics is compared with artificial
intelligence then we found that the conventional methods are a lot easier to conceptualize for
the customer as they can easily imagine the procedure which leads to the outcome. It’s really
simple to understand as we humans tend to not believe in something that we are not able to
understand or don’t want to.
REFLECTION & COMMENTARY ON THE IDENTIFIED TRENDS
Artificial Intelligence uses big data and several machine learning methods, NLP (Natural
Language Parsing) & other fields too. The overall impact of artificial intelligence on the
business analysis is good and some of the points are mentioned below.
HIGH BIG DATA VOLUME
The big data is rapidly increasing at high speed and in different forms. The big data is
so powerful that it can provide necessary insight for the enterprises. Most companies
are starting to invest in the tools related to the big data and want to develop ideas from
it.
INSIGHTS REAL-TIME
With the increasing success rate of the bid data and the pace at which the market
shifts have made it impossible to make old data-based decisions. With just a click of a
button, the artificial intelligence helps businesses perform real time. If the data is
fresh then it's important that it is dealt with in the real time itself.
NOT ENOUGH DASHBOARDS
A basic scenario is that an analyst fetches and uses data from only one dataset but
what if there are several data points which are coming from multiple data sources in

real time. It is clear that in the coming times most companies will use artificial
intelligence as there are limits to human beings when it comes to handling several
different tasks at once.
The changes that the artificial intelligence will bring to businesses are expected to be
positive and if businesses start using it earlier then they can help their own business to
grow over these years.
CHALLENGES
There might be various benefits of artificial intelligence but the most important part
for some businesses is the adoption of the AI as its not a simple journey. As per the
report, it's clearly shown that only 5-6% of the total businesses are able to use AI
easily. The most challenging things that the businesses face while implementing the
artificial intelligence solutions to its processes are listed below.
 To make sure the artificial intelligence applications are deploying
successfully, the business requires deep learning specialists who can
understand the whole process and then are able to deploy the application. This
is an important factor as AI is trending and the lacking of knowledge in this
domain can actually be a bad thing for the business. One more concern is that
there is a human resource lack which hinders the overall process of finding a
solution to the problem.
 The technologies related to artificial intelligence are too costly to deal for a
particular business. Every big business has to make a separate budget for the
implementation of artificial intelligence for research purposes. So, not every
business is able to implement artificial intelligence as it is not having big
amounts.
 Many of the AI systems present in the industries are input dependent on the
sensors data so it's really challenging to store and acquire the data. The sensor
data is huge and it may have some noisy data which might be hard to analyze
& store. Hence, a real challenge.
 The artificial intelligence needs a trained professional for its implementation
and handling. But to find such professionals is really difficult and expensive.
Professionals such as data engineers, scientists, and subject experts are rare to
be found. The businesses which have less budget allocated towards the
artificial intelligence part are not able to hire any good professional which
causes an obstruction.
 As artificial intelligence is getting popular day by day, its challenges related to
ethnicity and morality. There are AI bots which have successfully started
perfectly mimicking human conversations. So, as of now, it is really difficult

to say that we are talking with a chatbot or a real human. This is an issue of
ethnicity and morality which certainly makes the overall AI technology
implementation really difficult.
 For the solutions related to the AI & machine learning to b calculated there is
a need for high computation speed which is not possible sometimes as there
are no high power processors. For the short term, cloud computing and parallel
processing have looked after the requirements. The main problem arises when
there is a large amount of data present and then deep learning brings into
existence the most complex algorithms. The solution of lack of computational
speed is in the next generations computing architecture and infrastructure
solutions.
Figure 4: Machine Learning Process Flowchart
OPPORTUNITIES
There are various opportunities that artificial intelligence can bring to the businesses
of which some are listed below:
 The automobile industry is a huge industry but still, it’s a limited market as a
car can be purchased by anyone but it's not necessary that they know how to
drive it. This was the scenario when AI didn’t come into play. Blind people as
well as who suffer from some physical disorders will now be able to travel.
Self-Driving Vehicles is one of the examples.

 The integration of artificial intelligence in supply chain management can
certainly change the way delivery and logistics department works. With the
help of AI, the data can be analyzed, unified and provide insights to the
business.
 For the customer service, AI can be a good replacement as whatever happens
if a customer buys or don’t buy, even so, needs to ask something will contact
the customer service. AI can easily handle the frequently asked questions
which will help clear up staff so that they can focus on other major issues.
 AI is able to judge certain outcomes, have the ability of variable weighing and
provides the best decision based on the data provided. AI is sometimes more
accurate and gives better results than the human counterpart.
Figure 5: Oppurtunities in Artificial Intelligence

IMPACT OF THE TREND ON BUSINESS ANALYSIS PRACTICE
It is shown from the above trends that the contemporary business systems won't develop with
the use of traditional business analysis approach. For the business analysts simply knowing
the current process is not enough as they are experts for the whole process and have to
implement the business system. They are responsible to gather requirements and also develop
requirements related to the business. The analysts should keep themselves updated as the
business itself is going to take digital initiatives. With the Artificial Intelligence coming into
play it becomes really important for them to have a wide knowledge and understanding of the
process and technologies related to the business to support them. They should also have a
mindset to collaborate with the multiple stakeholders internally as well as externally. The
business analysts should provide support on the technology led projects. All these changes
made have certainly changed the overall business management system. The business analyst
can help in setting up a good knowledge management process in the company. Managers who
view AI as a kind of colleague will recognize that there’s no need to “race against a
machine.” While human judgment is unlikely to be automated, intelligent machines can add
enormously to this type of work, assisting in decision support and data-driven simulations as
well as search and discovery activities (How artificial intelligence will redefine management,
2016). If there are scattered data throughout the company then the analyst can identify the
correct data repositories & AI needed interfaces. The analyst might be able to train the AI
directly.
CONCLUSION
In the data science field, the value of a domain expert is increasing which might change the
whole normal analyst to being a combination of the domain expertise as well as an analyst. If
there will business analyst who are good at both the AI as well as analyzing the data then it
will be very beneficial for the business growth. Gathering the data is the initial for a company
towards effective grow. Though the business analysts must be able to solve the problems and
identify the particular relationships between numbers. There should be a difference between
causality and correlation. Talking about the future, it belongs to the companies which will
easily implement the artificial intelligence within their units and are the ability to successfully
predict and can combine the AI machines or tools with the power of the human judgment &
intuition. The business analysts require a Return Of Investment driven mindset as the
technologies are diverse and the business systems are capable to measure the overall business
growth. The company will be requiring new skill sets with new people as the business is
dynamic in nature and the overall process will turn towards solving more problems and
delivering processes.

REFERENCES
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Davis, E. and Marcus, G., 2015. Commonsense reasoning and commonsense knowledge in
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Ransbotham, S., Kiron, D., Gerbert, P. and Reeves, M., 2017. Reshaping business with
artificial intelligence: Closing the gap between ambition and action. MIT Sloan Management
Review, 59(1).
Kolbjørnsrud, V., Amico, R. and Thomas, R.J., 2016. How artificial intelligence will redefine
management. Harvard Business Review, 2.
Davenport, T.H. and Ronanki, R., 2018. Artificial intelligence for the real world. Harvard
Business Review, 96(1), pp.108-116.
Oana, O., Cosmin, T. and Valentin, N.C., 2017. Artificial Intelligence-A New Field of
Computer Science Which Any Business Should Consider. Ovidius University Annals,
Economic Sciences Series, 17(1), pp.356-360.