Impact of AI in Automating the Work of Business Process Outsourcing/Call Centre Workers

This report examines the impact of AI on the automation of work in BPOs and call centres, and discusses strategies to mitigate its negative effects on human resources. It explores how AI technologies are reshaping the industry and the potential for job loss and creation. The report also highlights the role of chatbots, voicebots, and speech analytics in improving customer service efficiency.

Impact of AI in Automating the Work of Business
Process Outsourcing/Call Centre Workers

Table of Contents
Introduction................................................................................................................................3
Background................................................................................................................................3
Issues analysis............................................................................................................................4
Strategies....................................................................................................................................6
Conclusion..................................................................................................................................8
References..................................................................................................................................9

Introduction
The impact of automation and artificial intelligence (AI) has become a significant topic of
discussion for every industry. AI is the ability of a computer, BOT or robots to function like
human beings. It is an advanced computer science, which evolved after conducting various
research studies to learn about the functioning of the human brain. These technologies are
also affecting business process outsourcing and call centre workers to a significant range
(PwC, 2018). AI could eliminate a number of white collar jobs in coming future. Its impact
can be felt within the call centre industry but, there is still no substitute for humans being
utilized for the purpose. It is the disruptive technologies that have fundamentally reshaped the
ways of working in the BPOs and call centres. Though, it has made the human resources
more efficient and productive in their jobs but, it also raises the concern of non-requirement
of human resources when technology can perform the job in place of humans. In this report,
the impact of AI technologies on the automation of work in BPOs and on call centre workers
will be identified and, the strategies that could be utilized to neutralize the negative impact of
AI technologies on human resources will be discussed.
Background
The development of bots and automated messaging have already changed the concept of call
centres, which are usually considered as being at risk of becoming out-dated in the world of
AI. The call centres are considered to be at the frontline of all big organizations that provide a
vital link between the businesses and customers (Concentrix Corporation, 2017). Through
call centres, the brand experience could be made or broken down. So, while various forms of
AI could be seen in the call centre in the present scenario, trained and intuitive human
resources could not be entirely replaced by the robots.

There is twofold potential for AI in call centres. Firstly, it can impeccably provide customers
with the right information required by them at the right time by offering them with self-
service options, eradicating the requirement for a call to customer service. The deployment of
AI in contact centres can address interactive voice response (IVR) pain points and could
improve customer self-service with chatbots that create conversational as well as streamlined
customer experience. Secondly, AI possess the potential to give customer service
representatives more information in order to help them in dealing with the complicated issues
that could not be resolved through self-service (Ponomareff, 2019). Considering the
continuous relevance and importance of customer service function, dealing with the second
issue would be more required. However, getting familiar with bots enable the customers to
resolve their issues through self-service channels, call centres use AI to serve organizations
and to help customer service representatives to deal with a huge range of customer services
(Capgemini, 2017). AI software has been developed to enable listening to the calls as well as
to interpret their impact on the customers such as how the issue was resolved, whether
customer loyalty is going to increase in future due to call and what could have been done to
help resolving the issue in the case of customer getting upset.
Issues analysis
There are a number of countries in the world that have been established as an outsourcing hub
for the firms across the world in search of low cost solutions to fulfil their IT and BPO
requirements. Millions of people enter the workforce every month but with the increasing use
of automation and AI, the service industry will lose millions of low-skilled jobs to
automation in the next few years (Bundhun, 2017). In the context of technology functions
performed in the IT industry, automation and AI solutions can increasingly deal with tasks
that could previously have been performed manually by human workforce (West, 2015). Due

to such innovations, the majority of companies have moved towards an increased reliance on
chatbots as well as on voicebots in order to respond to the queries made by customers online
and on the phone calls, which is likely to have huge consequences for the BPO sector and for
the call centre workers (Diversify OSS , 2018). A large number of human resources working
as first responders are going to lose their jobs. However, all those BPO people who are quite
alive to this possibility are themselves getting used to chatbot start-ups and such others. There
are a majority of companies that are investing heavily on investigating various ways to utilize
AI and automation in order to reduce the number of people required to perform the tasks
assigned as well as to improve efficiency (Americas, 2016). With the use of AI, chatbots and
voicebots, the turnaround times could be reduced from the first enquiries received from the
prospective clients to sharing the information required by them and converting it into a
qualified lead slowly and steadily for a particular project. Other initiatives in this context
include software testing, which is considered to be as highly labour intensive task (Muro et
al., 2019). From the technology and development point of view, lot of manpower is required
to test the app, game, or website across devices or browsers, so, implementation of automatic
testing not only reduces the manpower requirement but also the time taken to test a particular
software product and help in launching the products at a faster pace. A mobile app
development project that might have required four to six developers now require only one to
two people (Fersht & Snowdon, 2017). This issue has raised a serious concern as there is
uncertainty for the employment prospects for skilled and well trained software engineers,
which might force BPOs to adjust their operations to deal with the situation.
In order to improve customer service experience, AI is taken into consideration by the firms
so as to identify common problems and to give more feedback to the call centre agents to deal
with this priority. Speech analytics are used by the BPO call centres to find out what
frustrates or pleases the customers. On the other hand, AI in the call centres is based on

speech analytics that evaluates the emotional quality of the customer calls as well as cluster
conversations into simpler groups. The speech analytics is utilized by the firms to assist
human agents to identify and to learn specific speaking skills that could improve customer
interactions. Through speech analysis, call centres distinguish between what are the feelings
of the agents during a call and how they are perceived by callers. After the analysis,
objections can be identified and eliminated that prevent the customer service agents from
providing the level of service expected by and from the firm (Kishor, 2017). Through the use
of AI in call centres, the ability of the workforce is improved and it offers thoughtful
recommendations to the call centre team to improve their existing processes so as to
consistently achieve call quality as per the expectations.
In this way, where, AI has replaced the jobs of workforce, skilled workforce is in huge
demands to manage the operations by AI. Similarly, AI contributes a lot in improving the
efficiency of call centre workforce by helping them with learning how to improve their
speaking skills.
Strategies
AI helps in predicting the customer behaviour on phone calls and provides recommendations
to the customer service representatives regarding how to deal with the issues. However,
computers cannot perform all the functions, for which, human workforce is always required
to resolve customer issues in an effective and efficient manner with the use of insights and
recommendations from AI in order to deliver messages to the customers in a certain specific
manner (Manyika & Sneader, 2019). It has been identified that best type of customer service
representative for dealing with complex customer issues is the one who can keep a control
over the conversation and proactively leads the customer on call to a mutually agreed
solution. As such, a customer service representative who understands the needs and

requirements of the customers and do not need to follow a script, they can be considered as
most appropriate to be equipped to utilize the information provided by AI to personalize the
customer interaction and to help resolving the issue. It is a well-known fact that AI has
reduced the burden of call centres through bots that can be utilized to answer simple and
usually asked questions online, without the requirement of the customer for picking up the
phone. It shows that the job of the customer service representative is becoming more diverse,
the bots answer the routine questions through an online chat or through other channel. The
people on the phone have the responsibility to resolve the issues. When AI and customer
service representatives work with a quick pace, wherein, data insights are combined with a
personable phone manner, it becomes easier to achieve best results for the customers.
However, the advancements in technology in the form of AI and automation can provide
opportunities for various firms willing to embrace the trend. In this way, threat could be
converted into an opportunity with IT outsourcing firms increasingly being in demand by the
international clients to support them in mechanizing more processes. Number of companies
will hire people with the skills to implement these AI and automated functions and thereby
jobs could be created if the companies will adapt.
So, one hand where, automation is expected to replace the jobs of human resources, it is also
expected that it will also create new jobs that will be required to manage advanced
technology and will bring higher salaries to the workers. So, it is essential for the HR
management to recruit highly skilled workers and to ensure that the workforce employed in
the sector keeps on picking up new skills continuously (Lawton, 2019).
The speech analytics is utilized to capture intelligence data related to the emotional tone or
sentiments of the customers through their communicating words. It captures data from all the
customers through all customer interactions and makes it available to other departments
within the organization through dashboards and through custom reports. It helps in

understanding how the information could be beneficial for entire firm (Huang & Rust, 2018).
The introduction of AI to speech analytics has been made in various ways. It is used for the
analysis of emotional characteristics and content of interactions of call agents as well as to
convert calls into transcripts. Such transcripts can be analysed for the compliance, efficiency
as well as for quality control. On the basis of specific content of call, customer service agent
managers can take essential initiatives to correct the issues through coaching which is agent
targeted or through customer intervention (França & Vandor, 212). There are varieties of
advanced speech recognition tools that are developed on the basis of in-depth learning neutral
networks improvising their recognition of human language with time. In a similar manner,
call transcript analysis utilizes semi-supervised machine learning as well as weighted rules
logical to automatically classify as well as score calls.
Conclusion
After analysing the impact of AI on the automation of work in BPOs and over call centre
workforce, it has been realized that AI has huge impact on the automation of the work in
BPOs and has reduced the burden of the call centre workers to an extensive level. It has been
found that millions of jobs in BPOs have been lost due to automation of work but, it has also
been realized that the jobs lost have been specifically of less skilled workforce. With the use
of chatbots and voicebots, the quick response to the usual queries of customers has become
easier. Similarly, with the utilization of speech analytics, it has become easier to identify if
the customers are frustrated or pleased with the customer service representatives or agents.
Therefore, the implementation of AI for various functions in BPOs and call centres have
automated the functions and enhanced the customer service efficiency to an extensive level.
So, it can be concluded that where, AI has replaced the human resources in BPOs and call
centres, it has increased the demand of skilled and highly efficient workforce as well.

References
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