According to the 2022 Straits Research, the global business outsourcing market is forecast to hit USD 512.4 Billion by 2030.
Business process outsourcing (BPO) and call centers are tech- and growth-driven industries that rely heavily on technology advancements and human capital. With current trends in Artificial Intelligence and Machine Learning, there is a strong possibility for these industries to experience a gradual shift into new skills leading to fewer live agent (voice-based) jobs in the call center industry.
The increasing popularity of digital channels, such as social media and instant messaging apps, has greatly impacted and shifted customer interactions away from traditional phone-based call centers. Automation and self-service options, such as chatbots and interactive voice response (IVR) systems, can handle many customer interactions with considerably lesser need for human agents.
But many industries still rely heavily on customer service and (real) human interaction, so it is likely that the call center industry will continue to exist, but the way it operates may change.
Consider Your 2023 Skills and Services Upgrade: NLP and Machine Learning
Earlier this month, the IBPAP published a 2-part deck on the top skills for outsourcing:
- MS Office
- Cybersecurity
- Cloud Operations
- Artificial Intelligence
- Machine Learning
- AR/VR
- Blockchain
- Business Intelligence
- Data Analytics
- Edge Computing
- Data Science
- Internet of Things
- Process Automation
- Web Development
- SEM/SEO
BPO Jobs in High Demand in 2023?
- NLP Engineers: As more companies adopt NLP technologies like ChatGPT, there will be a greater demand for engineers who can design, develop, and maintain these systems. They will be responsible for tasks such as data preprocessing, model training, and fine-tuning.
- Machine learning engineers: Machine learning is a key technology behind ChatGPT, machine learning engineers will be in high demand as they can design and implement machine learning models, and optimize their performance.
- Data Scientists: They will be responsible for analyzing the data generated by ChatGPT and other NLP systems to extract insights and improve performance. They will also be responsible for cleaning, processing and transforming the data to be used in the models.
- Chatbot developers: As ChatGPT and other NLP models are increasingly integrated into chatbots, there will be a greater need for developers who can design, build, and maintain these systems. They will be responsible for tasks such as creating dialogue flows, integrating with backend systems, and testing.
- NLP-based content creators: As NLP systems become more advanced and capable of generating human-like text, there will be a growing demand for content creators who can use these systems to generate high-quality content.
- Language experts: NLP is heavily dependent on language understanding, there will be an increasing need for experts in specific languages who can help improve the performance of NLP systems for those languages.
The field of NLP is evolving fast. Having a deep understanding of the fundamental concepts and staying current with the latest research and developments is critical.
There are many resources available for learning natural language processing (NLP) including:
- Online Courses: There are many online courses available on platforms like Coursera, edX, and Udemy that cover the basics of NLP and more advanced topics. Some popular NLP courses include the Natural Language Processing Specialization on Coursera and the NLP with Deep Learning course on edX.
- Books: There are several books on NLP that provide a comprehensive introduction to the field. Some popular books include “Speech and Language Processing” by Daniel Jurafsky and James H. Martin, “Natural Language Processing with Python” by Steven Bird, Ewan Klein, and Edward Loper, and “Deep Learning for Natural Language Processing” by Yoav Goldberg.
- Research papers: Reading research papers is a great way to stay up-to-date with the latest developments in NLP. Papers from top conferences such as EMNLP, ACL, and NAACL are a good place to start.
- Conferences and Workshops: Attending NLP conferences and workshops can be a great way to learn about the latest developments in the field, network with other researchers and practitioners, and stay up-to-date with the latest research.
- Open source libraries: There are many open-source libraries such as NLTK, spaCy, Gensim, CoreNLP, etc. that are widely used in NLP. By learning and working with these libraries, practitioners can get a good hands-on experience in NLP.
The push toward CX has made companies of all sizes invest in training for omnichannel tech adoption in less than 10 years. Customer Experience (CX) is now a strategic initiative for most businesses.
Related Content:
ChatGPT’s Impact on Customer Experience and Marketing
Will ChatGPT Make Content Creation Jobs Disappear?
Net Promoter Score (NPS) is a key differentiator in today’s marketplace. Customer ratings tip the scale and move the needle faster than any marketing campaign. There is a seemingly invisible but palpable overlap between new ways of acquiring and retaining customers using intuitive tech.
But still, how many times have you wished a real person would pick-up when you ‘call in the experts’ instead of an endless, circuitous automated chat exchange with a plethora of links to resources and help sections?
You might also like:
Here’s Why Voice Channels Will Remain Evergreen in Call Centers
Why I Hate Customer Service Chatbots
So whether it is producing high-quality, self-help content that drives and shapes the entire customer journey, or maintaining service levels that wow them and keep them coming back for more, the new wave of outsourcing is catching up using more intelligent, human-like responses to all types of questions and requests.
NLP is a complex and broad field, and learning it requires a combination of theoretical knowledge, practical skills, and hands-on experience. The rate of change is accelerating. ‘Future Skills’ is today’s demand. How ready is today’s workforce?