Artificial Intelligence for Business - Opportunities and Challenges

This report discusses the opportunities and challenges of adopting AI techniques in business decision-making, with a focus on AstraZeneca. It explores the benefits of AI, such as performing complex tasks in a short time and easier marketing, as well as the challenges, including lack of advanced computing and data privacy concerns. The report also explains how AI can be used in decision-making, including coordinating data delivery, making quick and accurate decisions, analyzing data trends, providing forecasts, developing data consistency, and providing crucial information.

Artificial Intelligence
for Business

Contents
INTRODUCTION...........................................................................................................................3
TASK...............................................................................................................................................4
Opportunities in adopting AI techniques.....................................................................................4
Challenges in adopting AI techniques.........................................................................................4
AI techniques utilisation in decision-making of Astra Zeneca....................................................5
CONCLUSION................................................................................................................................8
REFERENCES................................................................................................................................9

INTRODUCTION
Artificial Intelligence is demonstrating human intelligence within machines. It can also be
used be applied with any machine that shows the human intelligence and human traits as human
mind in their working, operating, learning and other related operations and functions. There are
many existing examples in today’s world and these are face IDs, recommendation and many
more. AstraZeneca is international science leading biopharmaceutical business company. In this
report, AstraZeneca is discussed along with its future use of artificial intelligence’s opportunities
and challenges and how artificial intelligence will be used in decision making of AstraZeneca is
explained.

TASK
Opportunities in adopting AI techniques
Use of AI techniques in organisation leads to many benefits and with the future use of
thse techniques by AstraZeneca will provide it with a lot of opportunities in future
(Ameen, Tarhini, and Anand, 2021). Some of these opportunities are discussed below:
 Performing complex tasks in short time: AI techniques use by AstraZeneca will led to
easy performance of complex tasks in its organisation in a short span of time. While the
same work will take a lot of time when employees of AstraZeneca perform these tasks.
 Easy working with bigger tasks: The use of AI techniques by AstraZeneca will help it in
making all its big data in small sections, making it easier to record and maintain with it for
future referencing.
 Easier marketing: AstraZeneca wants to maximise its marketing strategies and for that it
will utilise AI techniques as an opportunity in building and monitoring and analysing all its
marketing strategies and its implementation.
 Tracking competitors: Competitors will be easily tracked by AstraZeneca when they will
use AI techniques in their utilisation (Anderson, Rainie, and Luchsinger, 2018). Tracking will
be done with the help of different channels, websites, social media and other.
 Support to customer solutions: Use of AI techniques by AstraZeneca will help it in
providing support and guidance and solutions to all customers. There will be a decrease in
waste of time by the use of AI techniques.
Challenges in adopting AI techniques
There will be many challenges with the use of AI techniques by AstraZeneca. Some of them are
explained below:
 Not so advanced computing: As there will be a lot of utilisation of processing power and
data by AI, there will be lack of enough power with implementation of AI techniques in
AstraZeneca (Collins, and Moons, 2019). So there will not that much use of advanced
computing.

 Lack of support: People of AstraZeneca won’t get support from other business who won’t
understand the concept of AI. This will be a major challenge with the adoption of AI
techniques as business will not interested in investing money and working with AI
development and its products.
 Lack of trust: People working with AI machines won’t trust these mechanical appliances
easily and won’t feel comfortable in understanding how decisions are made or are taken in
AstraZeneca in future. AI won’t be able to build trust among people with its technology.
 Data privacy and security: This will be a challenge as basis of AI application is massive
data that are used for making intelligent decisions (Glikson, and Woolley, 2020). These
systems are dependent on data and information which are personal and sensitive and use of
these in AstraZeneca will lead to no security of data handling and data privacy will also lost.
 Scarcity of data: with change in time, there will a lot of access of information and data to
AstraZeneca. But when these data will be applied to AI applications and machines in
AstraZeneca, their learning will also be rare. These powerful and specialised AI machines
will need special training and learning under clear supervision. This will limit the use of
labelled data as it will be limited and difficult to understand.
AI techniques utilisation in decision-making of Astra Zeneca
The artificial intelligence is considered as major technology based approach which helps
companies to perform quick and accurate operations. The Artificial intelligence helps a business
to overcome key challenges and issues which arising at the marketplace. Astra Zeneca company
should use the application of Artificial intelligence in decision-making (Khisamova, Begishev,
and Gaifutdinov, 2019). This will help me making and formulating key decisions of the
organisation as well as help the organisation to overcome major obstacles and hurdles that arises
in its operations. In the information and technology, there are key benefits which are to be
analysed by the company in order to focus on operations development. The Astra Zeneca
company should use the application in decision-making to make all decisions in an intelligent
and well defined manner. Key role of management of Astra Zeneca is to develop effective ways
of solving a problem which is related to its functions and tasks. Most of the successful
companies in the international and national marketplace focus on increasing approach based on

artificial intelligence to gain desired success (Majumdar, Sarode, and Patil, 2018). All major
companies should also focus on making crucial decisions on the basis of outcomes suggested by
AI to develop key approach in business management. The main utilisation in decision-making
approach used by Astra Zeneca is mentioned below with the help of following techniques:
 Coordinating data delivery- The data delivery coordination is managed with the help
and assistance of artificial intelligence. In the era of stiff competition between companies,
it is essential role of Astra Zeneca to develop key solutions related to data delivery. The
data delivery is also a major aspect of increasing the chances of data development in a
short period of time. The data delivery is essential from time to time in a business to
deliver major practices related to management of data.
 Quick and accurate decisions- The decision-making approach is a key technique to deal
with uncertainties and future predictions in a company (Osoba, and Welser IV,2017).
AstraZeneca will develop a competitive approach in managing major decisions of the
company by applying an intelligent approach. The business will also get benefit of
making quick decisions which will help in increasing flow of operations in a better and
systematic manner.
 Analyse data trends- The artificial intelligence plays a major role in analysing the data
which is associated with business. Smart calculations on the basis of core data
intelligence are provided by operations performed with the help and assistance of
artificial intelligence. Analysis of data trends is also important for Astra Zeneca as it has
large customer base. The company should focus on delivering key practices based on AI
to develop an intelligent approach in briefly evaluating major data trends.
 Providing forecasts- The artificial intelligence if adopted by Astra Zeneca will also help
in development of crucial forecast on the basis of data collected. It will also help in
development of a crucial approach which is beneficial in increasing the chances of
predicting an uncertainty. Precise and systematic data forecast is also essential for the
business in order to lead the competition (Prentice, Dominique Lopes and Wang, 2020).
Also with the help of forecasts and predictions AstraZeneca will be able to eliminate risk
associated with the operations. The major companies in the global and domestic
marketplace focus on development of key forecasts in order to achieve key outcomes in
an effective manner.

 Developing data consistency- In the functioning of a business, it is very much crucial
for the IT management to develop consistency in data management. The help and support
of artificial intelligence will provide key and smart solutions for maintaining data
consistency. This approach will assist to manage crucial data of its customers along with
increasing the chances of more consistent data. The data consistency will also help the
company to move ahead of competitors and gain competitive advantage in a set period of
time.
 Providing crucial information- The crucial information related to the data is need of
Astra Zeneca in order to achieve key results and outcomes. This is major role of
management of a company to focus on development of major and crucial information
based on the subject matter related to customers. The key role of IT management of a
business is to develop major information related to products and services and it can
become easy with the support of Astra Zeneca. The precise information and its
development is also essential for the company to focus on key goals and objectives which
are decided by the management at the starting of financial year.

CONCLUSION
From the above stated report it can be concluded that Artificial Intelligence is important in
organisations with its decision making. There are a lot of opportunities and challenges that are
faced by an organisation while adopting Artificial Intelligence techniques. In this report all these
are explained along with the use of these techniques in decision making. This report is based on
Artificial Intelligence and its utilisation.

REFERENCES
Books and Journals
Ameen, N., Tarhini, A., and Anand, A., 2021. Customer experiences in the age of artificial
intelligence. Computers in Human Behavior, 114, p.106548.
Anderson, J., Rainie, L. and Luchsinger, A., 2018. Artificial intelligence and the future of
humans. Pew Research Center, 10, p.12.
Collins, G.S. and Moons, K.G., 2019. Reporting of artificial intelligence prediction models. The
Lancet, 393(10181), pp.1577-1579.
Glikson, E. and Woolley, A.W., 2020. Human trust in artificial intelligence: Review of empirical
research. Academy of Management Annals, 14(2), pp.627-660.
Khisamova, Z.I., Begishev, I.R. and Gaifutdinov, R.R., 2019. On methods to legal regulation of
artificial intelligence in the world. International Journal of Innovative Technology and Exploring
Engineering, 9(1), pp.5159-5162.
Majumdar, B., Sarode, S.C., and Patil, S., 2018. Technology: artificial intelligence. British dental
journal, 224(12), pp.916-916.
Massis, B., 2018. Artificial intelligence arrives in the library. Information and Learning Science.
Osoba, O.A. and Welser IV, W., 2017. An intelligence in our image: The risks of bias and errors
in artificial intelligence. Rand Corporation.
Prentice, C., Dominique Lopes, S. and Wang, X., 2020. Emotional intelligence or artificial
intelligence–an employee perspective. Journal of Hospitality Marketing & Management, 29(4),
pp.377-403.