Student's Name
Institutional Affiliation
Course
Professor's Name
Date
Artificial-based intelligence marketing for Nokia
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Abstract
Due to globalization, the world is always becoming more technologically dependent, so
firms must keep current to remain competitive. Adopting artificial intelligence in marketing
customer relations is more crucial than ever. Automating tasks that once required human labor is
another benefit of technological advancement (Akinsola, Adeagbo, Oladapo and Akinsehinde,
2022). Artificial intelligence (AI) is a growing topic in computer science that makes inroads into
the corporate world. It's critical to comprehend what artificial intelligence (AI) is and how it may
be used in a business's marketing operations due to the complexity of the notion itself. As a
result, it is crucial to think about and assess the potential effects of technology on customer
relations, particularly in the marketing process.
The employment of artificial intelligence will be taken into consideration, and in this
project, the critical applications of AI that may have an impact on marketing will be highlighted.
To develop a comprehensive understanding of the present and potential uses of artificial
intelligence in marketing, the facts and viewpoints gathered from specialists in the domains of
computer engineering and programming, business, and marketing are presented in this proposal.
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Background
AI has substantially impacted customer loyalty and profitability for companies that have
integrated it into their customer relationship management (CRM) and overall marketing strategy
(Chintalapati and Pandey, 2021). Software and IT companies specializing in creating customized
marketing strategies and programs for customer engagement and marketing have emerged in
recent years. Using modern technology and data, companies worldwide are becoming more
competitive, improving customer experience, and even introducing entirely new business models
thanks to the massive amounts of data and cloud computing access available (Carson, 2015).
They are sharing data so that they may progress faster and achieve better, more accurate results
in areas such as automation and machine learning.
As a percentage of the overall number of organizations with HR, the use of AI
technology is still relatively low. For the sake of cost and benefit considerations, AI is most
commonly deployed in giant corporations, which is a good thing. Artificial Intelligence is
becoming increasingly popular, but this does not change the reality that it is becoming more and
more popular. According to the research findings, it has numerous advantages for the business,
saves money, and increases productivity.
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Research Questions

What can we expect in the marketing and AI industries in the future?

For Nokia's marketing, what are the potential AI-enabled solutions?

Does sharing so much personal information with a machine pose any risk, especially
regarding businesses and their employees?

Is AI-powered technologies for marketing and sales a trend?

Can Nokia use artificial intelligence marketing or not.
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Objectives
The core objective of the project is to create artificial intelligence systems that can affect
resource marketing and improve customer relationship management and brand image for Nokia.
The project also aims to use the information and insights acquired from specialists in artificial
intelligence and marketing to gain a comprehensive view of the current and future potential of
artificial intelligence in marketing to make recommendations to Nokia. The goal of this project is
to create a new artificial intelligence marketing application. The proposed project will investigate
whether an AI-powered marketing platform will enhance Nokia sales by increasing the
effectiveness of marketing and sales strategy.
In addition, one of the goals is to strengthen one-on-one advertising and shift away from
mass marketing. With this research, we hope to assist Nokia in improving customer convenience,
which will lead to greater sales and market share for the company, as well as to determine the
current usage of AI applications by enterprises in particular fields.
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Research Method
available data has been analyzed to determine the next step in the project. First, the
proposal provides a brief overview of the role of artificial intelligence in marketing to help the
reader better appreciate its significance. There is a conceptualization of artificial intelligence and
the construction of its architecture, with a focus on its critical components. The use of
quantitative research will be utilized to investigate the disciplines of artificial intelligence and
digital marketing to get a knowledge of how AI is employed in Nokia's marketing and what may
be expected in the future. Qualitative approaches would have a hard time revealing the insights
derived from the main concepts.
Marketing and sales experts, as well as those in the domains of digital marketing and
artificial intelligence (AI), will be evaluated in-depth for this study using pre-determined criteria,
such as their level of competence in the topic area. To have a thorough grasp of how artificial
intelligence is used in Nokia's marketing and what future trends AI-powered marketing may
bring, it is necessary to begin by reading the works of well-known experts in the industry, such
as those found in publications, journals, and internet forums.
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Timeline
CATEGORY
TASK
START
END
Concept
Market Analysis
1/07/2022
11/07/2022
Feasibility
11/07/2022
17/07/2022
Cost Estimates
17/07/2022
22/07/2022
Design System
22/07/2022
01/08/2022
01/08/2022
10/08/202
Prototyping
10/08/2022
19/02/2022
Testing
19/08/2022
29/08/2022
Development
System Design
Architecture
Product
Development
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Resources
An expert system can be created for less than $500,000 in direct labor costs by a small
team of no more than 20 people. Several investments totaling at least $1,000,000 must be made
if Nokia continues to be in charge of the design and implementation of an artificial intelligence
system. Resources must be acquired, primarily in the form of qualified personnel and specialized
machinery. Nokia needs enough performance computing resources to fully capitalize on the
opportunities offered by AI. Basic AI workloads can be handled in a CPU-based environment,
but deep learning requires the use of numerous large data sets and scalable neural network
methodologies. It is crucial that Nokia's infrastructure can scale storage as data volume increases.
The amount of AI an organization intends to use and whether real-time decisions must be
made influence the type of storage the organization needs. The newest generation of Nvidia
GeForce chips and their cutting-edge chipset architecture offer significantly more value for
Nokia's money. They will be a useful resource for the development of the marketing platform,
even though Intel has long held a majority share of the CPU market. Another important part of
the infrastructure for AI is networking. As AI efforts grow, networks must keep up with demand
because deep learning algorithms depend heavily on communications.
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References
Akinsola, J., Adeagbo, M., Oladapo, K. and Akinsehinde, S., 2022. Artificial Intelligence
Emergence in Disruptive Technology. [online] ResearchGate. Available at:
https://www.researchgate.net/publication/358627200_Artificial_Intelligence_Emergence
_in_Disruptive_Technology
Carson, E., 2015. Persado uses artificial intelligence to help digital marketers write better copy.
[online] TechRepublic. Available at: https://www.techrepublic.com/article/persado-usesartificial-intelligence-to-help-digital-marketers-write-better-copy/
Chintalapati, S. and Pandey, S., 2021. Artificial intelligence in marketing: A systematic literature
review. [online] ResearchGate. Available at:
https://www.researchgate.net/publication/352970767_Artificial_intelligence_in_marketin
g_A_systematic_literature_review
Devang, V., Gunjan, T., Chintan, S. and Krupa, R., 2019. Applications of Artificial Intelligence
in Marketing. [online] ResearchGate. Available at:
https://www.researchgate.net/publication/337688280_Applications_of_Artificial_Intellig
ence_in_Marketing
Ellett, J., 2017. IBM Study Finds Outperforming Companies More Ready To Adopt AI For
Marketing. [online] Forbes. Available at:
https://www.forbes.com/sites/johnellett/2017/09/13/ibm-study-finds-outperformingcompanies-more-ready-to-adopt-ai-for-marketing/?sh=403173b35952
Iqbal, T. and Khan, N., 2021. The Impact of Artificial Intelligence (AI) on CRM and Role of
Marketing Managers. [online] Diva-portal.org. Available at: https://www.divaportal.org/smash/get/diva2:1526230/FULLTEXT01.pdf
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Marko, K., 2020. Infrastructure for machine learning, AI requirements, examples. [online]
Search Datacenter. Available at:
https://www.techtarget.com/searchdatacenter/feature/Infrastructure-for-machine-learningAI-requirements-examples
Mo, L. and Yang, L., 2022. Research on Application Effective Evaluation of Artificial
Intelligence Technology in Marketing Communication. [online] ResearchGate. Available
at:
https://www.researchgate.net/publication/359652407_Research_on_Application_Effectiv
e_Evaluation_of_Artificial_Intelligence_Technology_in_Marketing_Communication
Salmi, A., 2021. Artificial Intelligence Enabled Solutions in Marketing. [online] Theseus.fi.
Available at:
https://www.theseus.fi/bitstream/handle/10024/334286/Thesis%20AI%20final%20versio
n.pdf?sequence=2&isAllowed=y
Suresh, C., 2021. Recent trends in digital marketing in today’s scenario. [online] ResearchGate.
Available at:
https://www.researchgate.net/publication/359842454_recent_trends_in_digital_marketing
_in_today's_scenario
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Appendix
Gantt chart