Application of AI in CRM: Issues, Benefits, and Technology Overview

This report provides a detailed analysis of the application of Artificial Intelligence (AI) in Customer Relationship Management (CRM) within the United States. It explores four key aspects: strategic issues, benefits of AI implementation, implementation challenges, and the required technologies. The report identifies strategic issues such as a lack of clear implementation strategies, data strategies, AI governance, and communication regarding organizational changes. The benefits discussed include virtual assistance integration, automated data collection, enhanced customization, improved client service and management, and data analytics. Challenges addressed encompass data integration, data auditing, complex infrastructure requirements, the need for trained professionals, implementation costs, and legal considerations. The report also examines the technologies essential for AI integration in CRM, including Natural Language Processing (NLP), Machine Learning, AI databases, and search engines. The report highlights the importance of proper infrastructure and strategic planning before investing in AI to improve CRM performance.

Running head: APPLICATION OF AI IN CRM
APPLICATION OF AI IN CRM
Name of student
Name of university
Author’s note:

1
APPLICATION OF AI IN CRM
Executive summary
There are various benefits of implementing the artificial intelligence in CRM which are
integration of virtual assistance, providing context for automated data collection, offering
enhanced customization, client service and effective management and proper data analytics as
well. However, there are some issues as well which are designing strategies for Data
integration, ensuring effective Data auditing, requirement for Complex infrastructure, Trained
professionals, Cost for implementation and Legal issues for applying the artificial intelligence
in implementation of CRM. Therefore, it is important to ensure proper infrastructure before
investing in the artificial intelligence for improving performance of CRM.

2
APPLICATION OF AI IN CRM
Table of Contents
Introduction:...............................................................................................................................3
Application of AI in CRM:........................................................................................................3
Issues associated with strategy:..............................................................................................3
Benefits:.................................................................................................................................4
Challenges:.............................................................................................................................6
Technology:............................................................................................................................7
Conclusion:................................................................................................................................9
References:...............................................................................................................................10
Appendix..................................................................................................................................13

3
APPLICATION OF AI IN CRM
Introduction:
The report describes about the application of the Artificial intelligence in Customer
relationship management in United States. While describing the application of AI in CRM,
four aspects are considered which include Issues associated with strategy, Benefits of
application, Challenges of implementation, Technology required for the application. The
issues that are identified in terms of implementation strategy are Lack of clarity for
implementation strategies, Lack of strategy for data, Inefficient AI governance strategy, Lack
of communication regarding organization change. The benefits that the report has considered
are Integration of virtual assistance, automated data collection, Enhanced customization,
Client service and effective management and Data analytics. Some of the issues that are
described in this report are Data integration, Data auditing, Complex infrastructure, Trained
professionals, Cost for implementation and Legal issues of application of the artificial
intelligence in implementation of CRM. In this context some of the technologies related to
the artificial intelligence are considered as well which are Natural language processing
(NLP), Machine learning, AI Databases, and Search engines that are required for integration
of the artificial intelligence with CRM.
Application of AI in CRM:
Issues associated with strategy:
Lack of clarity for implementation strategies: It is often seen that companies who invest in
AI lacks proper strategies for implementation. It is not only about who will implement the
project, it is about analysing culture of the organization (Hopkinsona, Perez-Vegab and
Singhala). The main issue is identifying whether the leadership embraces the change that AI
will bring in the culture of the organization in terms of execution of organizational roles and
responsibilities, or whether they are against this. Even if the leadership decide to implement

4
APPLICATION OF AI IN CRM
AI applications, defining how and when it will be done is an important challenge that affects
the efficiency of the AI implementation strategy (Bergdahl 2018).
Lack of strategy for data: In order to integrate AI in CRM, it is required to source data from
various resources which include market data, sales data, consumer data, invoice and purchase
data, data from social accounts and other data sources according to the organizational
requirements (Chatterjee et al. 2019). If the strategy for data sourcing and data integration is
not proper, then it will affect the application of AI in CRM.
Inefficient AI governance strategy: It is not only enough to define strategy for AI
application, it is also required to define a proper strategy for data governance as well (Deb,
Jain and Deb 2018). However, organizations, not only in US, but in other countries as well,
finds it difficult to audit and monitor data, that makes data sourcing and integration less
effective because in AI application, quality of data is an important requirement.
Lack of communication regarding organization change: Application of AI in CRM will
bring changes in roles and responsibilities with most of the activities of consumer
management will be automated (Kolbjørnsrud, Amico and Thomas 2017). Therefore, most
often employees consider it a threat to their job security. The main issue is that how
application of AI will bring change to the organization and whether it will affect the job of
the employees or not is not properly communicated, due to lack of proper communication
strategy.
These issues are described in CRM evaluation document by Infosys (Infosys.com 2019).
Benefits:
Integration of virtual assistance: Application of AI in CRM will provide feature of virtual
assistance which is capable of interacting with the consumers anytime anywhere and resolve

5
APPLICATION OF AI IN CRM
their queries as well (Josiah et al. 2015). This will ensure that the consumer issues are
resolved without delay and therefore enhance consumer satisfaction as well.
Automated data collection: AI in CRM will collect data related to the consumers and
categorize those data according to the type of data (Shahid and Li 2019). This will help in
organizing data effectively and therefore it will help in data processing as well. Along with
that, AI will also ensure that data collection and data categorization is accurate and help in
derive insight from it for enhanced consumer management.
Enhanced customization: AI algorithms makes segmentation of the consumers automatic
and this segmentation of the consumers are done according to the gender, geographical
location, buying habits and history, and other customized data points (Kumar et al. 2019). It
is important to note that tools related to CRM is highly customizable, and application of AI
therefore enhance this customization allowing organizations to ensure detailed
personalization of the consumers and this will help the organization to ensure that the
engagement with the customers is effective and efficient.
Client service and effective management: AI automates data collection and through
intelligent data processing helps organization to design a marketing strategy that ensure that
the right customer is targeted at the right time, ensuring better client service and consumer
management (Ayyagari 2019).
Data analytics: In order to ensure to derive the insight from the data collected from various
resources, it is important to integrate an advanced data analytics process (Massaro et al.
2019). It is important to note that the data that is collected is not structured, therefore it is not
possible to analyse these data manually. AI through advanced data analytics makes it easier
to analyse these data and derive insight from this which helps in designing effective
consumer management strategy (Cangemi and Taylor 2018).

6
APPLICATION OF AI IN CRM
IBM has provided benefits of applying AI in CRM and how this has enhanced the
organizational business process (Ibm.com. 2019).
Challenges:
Data integration: It is already defined that it is required to collect data from various
resources which include market data, sales data, consumer data, invoice and purchase data,
data from social accounts and other data sources (Dwivedi et al. 2019). However, while
integrating AI with CRM, it is important to ensure that all of these data sources are properly
identified and integrated with the CRM application. However, these data are not properly
structured and also large in volume which makes it challenging to ensure proper data
integration.
Data auditing: It is not only enough to identify data sources and collect the data, it is also
required to ensure that the data is properly audited and cleaned up when required (Krishna
and Ravi 2016). It is particularly important because to ensure that the maximum benefit is
obtained from the AI system, organization requires data that is not only accurate, but properly
segmented and updated as well. If this is not ensured then it affects the organizational
strategy made with reference to the data. However, timely data audit and data clean-up is an
important challenge in this context.
Complex infrastructure: In order to implement AI in CRM, it is important to design a
proper infrastructure that is not only advanced, but complex as well. However, it is not only
enough to invest in infrastructure, it should ensure proper design and reference architecture as
well (Dwivedi et al. 2019). If the reference architecture is not effective enough due to design
issues, then it is not possible to implement AI applications. Therefore designing a reference
architecture and implement the infrastructure according to that is an important challenges for
organization.

7
APPLICATION OF AI IN CRM
Trained professionals: Although, AI is helping organization to design excellent consumer
management strategy, it requires trained professionals for that as the technology is advanced
and complex as well (Kietzmann, Paschen and Treen 2018). There is demand in the market
for such professionals, it lacks number of quality professionals not only in USA, but in
international job market. Sourcing quality and skilled professionals is a significant issue that
organization should consider while they decide to implement AI applications.
Cost for implementation: Application of AI in CRM needs significant investment which
include cost for infrastructure development and maintenance (Shahid and Li 2019). If the
company is not a large scale company, then cost for implementation might be a significant
challenge for the organization as well.
Legal issues: While sourcing data from different resources, it is important to ensure that the
data is properly secured. As the data that is collected includes personal information, securing
the data, according to the data protection law in USA, it is mandatory for the organization to
ensure security of these personal data (Dwivedi et al. 2019). Therefore, protecting personal
data of the consumers against data breach is an important challenge for the organization in
legal context.
Some of these issues were also identified in the report of McKinsey & Company (McKinsey
& Company 2019).
Another report of Salesforce has described some of these issues as well for describing reason
for CRM project not bring successful (Salesforce.com. 2019).
Technology:
Natural language processing (NLP): Natural language processing or NLP is one of the
most significant technologies for implementing AI in CRM (Bergdahl 2018). It helps in sales,
service and marketing. NLP analyses the text of the emails that are sent to the customers, and

8
APPLICATION OF AI IN CRM
provide an estimation of potential sale and its likelihood as well. Along with this, NLP also
helps in identifying best deals possible and also provides a description of deals where the
team has a highest risk to lose. Not only this, the NLP also provides recommendation for
improving the sales process as well. The Natural language processing or NLP analysing text
content of the email, provide reply to the customer email properly to offer enhanced
consumer service as well. The Natural language processing or NLP is capable of sentiment
analysis on text which helps companies to identify feeling of the consumer about the
organization and its services, which helps in marketing as well.
Machine learning: Machine learning is one of the most important aspects of AI. It refers to
the process where computers learn from data that is provided as input to the system without
requirement of extensive programing. It is capable of analysing information contained in
email, calendars, along with CRM data and recommend actions like what is the best email
response that should be forwarded to the customer (Venkatesan 2017). It is capable of
automatic classification of cases and intelligently sent them to the appropriate service agent.
It is also capable of calculating the likelihood that a customer might open an email, make
subscription for a newsletter, or make a purchase as well.
AI Databases: AI database is another important technology for implementation of AI in
CRM. In order to store and provide data for machine learning, AI database is required
(Kietzmann, Paschen and Treen 2018). The AI database combines data warehousing,
advanced analytics, and visualizations and for this an in-memory database is required that is
integrated with the AI database.
Search engines: In order to provide data according to the requirement of the applications, it
is important to ensure that there is an effective process for searching data from different data
sources (Kolbjørnsrud, Amico and Thomas 2017). AI search engine is different from general

9
APPLICATION OF AI IN CRM
search engine. The search engine only require information where to search form, it will then
identify documents such as PDFs and texts and derive valuable insight from those
information.
A report by SAP has identified the importance of natural language processing for applying AI
in CRM (Blogs.sap.com. 2019).
Another report by IBM has identified the importance of AI search engine of Watson for
enhancing the performance of CRM (Hodge et al. 2019).
Conclusion:
There are various benefits of implementing the artificial intelligence in CRM which are
integration of virtual assistance, providing context for automated data collection, offering
enhanced customization, client service and effective management and proper data analytics as
well. All of these features plays an important role in ensuring that the consumer management
is effective and efficient as well. However, there are some issues as well which are designing
strategies for Data integration, ensuring effective Data auditing, requirement for Complex
infrastructure, Trained professionals, Cost for implementation and Legal issues for applying
the artificial intelligence in implementation of CRM. Therefore, it is important to ensure
proper infrastructure before investing in the artificial intelligence for improving performance
of CRM and therefore enhancing the business process as well through intelligence in
consumer management, an important aspect in any business. While applying the artificial
intelligence in CRM, it is also important to ensure that the required AI technologies are
selected, because there are various AI technologies, but not all are required. Therefore,
investing in technologies that are not required in this context, will not only make the process
less effective, but it will also increase the cost as well. the technologies that are report has
considered in this context are Natural language processing (NLP), Machine learning, AI

10
APPLICATION OF AI IN CRM
Databases, and Search engines, all of which are important to ensure that the CRM is effective
and efficient as well.

11
APPLICATION OF AI IN CRM
References:
Ayyagari, M.R., 2019. A Framework for Analytical CRM Assessments Challenges and
Recommendations. International Journal of Business and Social Science, 10(6).
Bergdahl, J., 2018. The AI Revolution: A study on the present and future application and
value of AI in the context of ERP systems.
Blogs.sap.com., 2019. Text Analysis: Natural Language Processing as a Core Feature of
SAP HANA | SAP Blogs. [online] Available at: https://blogs.sap.com/2014/09/08/text-
analysis-natural-language-processing-as-a-core-feature-of-sap-hana/ [Accessed 3 Oct. 2019].
Cangemi, M.P. and Taylor, P., 2018. Harnessing Artificial Intelligence to Deliver Real-Time
Intelligence and Business Process Improvements. EDPACS, 57(4), pp.1-6.
Chatterjee, S., Ghosh, S.K., Chaudhuri, R. and Nguyen, B., 2019. Are CRM systems ready
for AI integration? A conceptual framework of organizational readiness for effective AI-
CRM integration. The Bottom Line.
Deb, S.K., Jain, R. and Deb, V., 2018, January. Artificial Intelligence―Creating Automated
Insights for Customer Relationship Management. In 2018 8th International Conference on
Cloud Computing, Data Science & Engineering (Confluence) (pp. 758-764). IEEE.
Dwivedi, Y.K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y.,
Dwivedi, R., Edwards, J., Eirug, A. and Galanos, V., 2019. Artificial Intelligence (AI):
Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for
research, practice and policy. International Journal of Information Management.
Hodge, R., Papadopoulos, L., Therkelsen-Terry, N. and Schneider, C. (2019). Introducing
Watson Discovery for Salesforce: An AI-powered insight engine for CRM - Watson. [online]

12
APPLICATION OF AI IN CRM
Watson. Available at: https://www.ibm.com/blogs/watson/2018/09/introducing-watson-
discovery-for-salesforce-an-ai-powered-insight-engine-for-crm/ [Accessed 3 Oct. 2019].
Hopkinsona, P., Perez-Vegab, R. and Singhala, A., Exploring the use of AI to manage
customers’ relationships.
Ibm.com. (2019). Creval Sistemi e Servizi. [online] Available at: https://www.ibm.com/case-
Infosys.com., 2019. [online] Available at: https://www.infosys.com/services/microsoft-
dynamics/Documents/making-crm-ready-ai.pdf [Accessed 3 Oct. 2019].
Josiah, A., Ikenna, O., Jennifer, A., Chinaedum, I., Justina, R. and Nnamonso, A., 2015. The
Relevance of Analytical CRM and Knowledge Management in an Organisation: A Data
Mining Structure. International Journal of Computer Science and Mobile Computing, 4(2),
pp.208-215.
Kietzmann, J., Paschen, J. and Treen, E., 2018. Artificial intelligence in advertising: How
marketers can leverage artificial intelligence along the consumer journey. Journal of
Advertising Research, 58(3), pp.263-267.
Kolbjørnsrud, V., Amico, R. and Thomas, R.J., 2017. Partnering with AI: how organizations
can win over skeptical managers. Strategy & Leadership, 45(1), pp.37-43.
Krishna, G.J. and Ravi, V., 2016. Evolutionary computing applied to customer relationship
management: A survey. Engineering Applications of Artificial Intelligence, 56, pp.30-59.
Kumar, V., Rajan, B., Venkatesan, R. and Lecinski, J., 2019. Understanding the Role of
Artificial Intelligence in Personalized Engagement Marketing. California Management
Review, 61(4), pp.135-155.
Massaro, A., Vitti, V., Lisco, P., Galiano, A. and Savino, N., 2019. A business intelligence
platform Implemented in a big data system embedding data mining: a case of

13
APPLICATION OF AI IN CRM
study. International Journal of Data Mining & Knowledge Management Process
(IJDKP), 9(1), pp.1-20.
McKinsey & Company., 2019. The promise and challenge of the age of artificial intelligence.
[online] Available at: https://www.mckinsey.com/featured-insights/artificial-intelligence/the-
promise-and-challenge-of-the-age-of-artificial-intelligence [Accessed 3 Oct. 2019].
Salesforce.com. (2019). [online] Available at: https://www.salesforce.com/hub/crm/why-do-
crm-projects-fail/ [Accessed 3 Oct. 2019].
Shahid, M.Z. and Li, G., 2019. Impact of Artificial Intelligence in Marketing: A Perspective
of Marketing Professionals of Pakistan. Global Journal of Management And Business
Research.
Venkatesan, R., 2017. Executing on a customer engagement strategy.

14
APPLICATION OF AI IN CRM
Appendix
It could be analysed that the integration of the artificial intelligence technology in the
businesses are increasing in the present times. Majority of the businesses are introducing this
technology for simplifying the business functions and improving the main functions provided
by the companies. The enterprise wide AI comprises of the main potential of introducing the
potential changes for gaining extensive competitive advantages in the market of the
businesses. But as per the researches conducted by the IBM company, it could be analysed
that majority of the businesses who are introducing this technology are failing to properly use
it because of the lack of proper knowledge of using this particular technology. The CRM
application has been significantly improved with the introduction of the artificial intelligence
technology and it could be improved in the future. The company IBM allows the introduction
of artificial intelligence in the CRM technology that helps the companies to predict the
customer preferences and the behaviours more accurately and efficiently.