Future of the Outsourcing Business in the AI World

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The Fourth Industrial Revolution is already here, and its steam engine is AI.

William Gibson once observed: “The future is already here – just not evenly distributed.” There is no better way to describe the state of Artificial intelligence (AI) and how it is going to transform our future. For those observing technological progress, it’s no surprise that the pace of development of AI is drastically increasing. It is theorized that this acceleration is exponential and will eventually lead to a technological singularity – a state marked by disruptive and unstoppable progress.

To put things into perspective, humanity started writing around 6,000 B.C. and invented paper in 25 A.D. The twentieth century has brought far more dramatic and disruptive change than what was accomplished during the thousands of years preceding this timeframe. Think of the birth of the commercial Internet in the early 1990s and the first smartphones in the early 2000s – the first iPhone was introduced only in 2007. These two technologies alone have had a massive impact on how we communicate. There have been so many more advancements in the last century as well.

These developments have created many opportunities but also many risks. The emergence of COVID-19 and the digital transformation of commerce and society have further accelerated the pace of technological change. This raises many pressing questions. Does the Business Process Outsourcing (BPO) industry still have a future? How do you innovate and thrive under such circumstances? BPO industry will survive and thrive but it will need to be prepared to adapt and embrace fast technological progress.

Scientists from Oxford and Yale universities argued in a 2018 paper that AI will become better than humans in many common activities by the end of this decade. For instance, they project AI will be more proficient at driving a car than humans by 2027 and better at writing a high school essay than students by 2026*. This study sent shock waves across the scientific and business communities. The impacts are immense, the future we have seen in the movies is here. As a result, everyone has started to question existing business paradigms and reevaluate their strategies.

While AI will automate many tasks, it will take a combination of human input with trained AI algorithms – and its resulting efficiency and quality – to solve the most complex problems facing humanity today.


Artificial intelligence (AI) and machine learning (ML) are ubiquitous terms, but what do they really mean?

AI is intelligence demonstrated by machines, unlike the natural intelligence exhibited by humans. It is conditioned by the use of neural networks, which replicate thought processes based on provided data. This is similar to the way the human brain operates. AI differs from natural intelligence in that it does not exhibit consciousness.

Although research in AI started after the Second World War, recent advancements in computing technology and performance gains have made it practical and affordable. In its current stage, AI technologies are still considered to be in their infancy but can perform at par or better than humans at well-defined tasks. This sort of AI is called weak AI. A good example of this is Deep Blue from IBM, which was the first computer to beat humans in the game of chess in the late 1990s (Kasparov vs. Deep Blue)**. As proficient as it was at chess, Deep Blue was unable to perform any other task, a hallmark of weak AI.

Artificial general intelligence (AGI) or strong AI is a type of AI that can learn any type of task that humans can learn. It is what we tend to think of as AI – a completely independent and intelligent being. Many scientists believe that we are still decades away from getting to that level of advancement and some experts believe we will never be able to create that type of intelligence.

Ray Kurtzweil, lead futurologist at Google, theorizes that AGI may eventually develop into a superintelligence by 2045.

Superintelligence significantly surpasses the capabilities of human beings and might pose a threat to humanity – just like the HAL 9000 computer from the Stanley Kubrick’s “2001: A Space Odyssey”. Most scientists agree that even if this is possible, it will take decades more to get there, though some argue, it might arrive even within years. In recent article in The Independent, Elon Musk claimed that Superintelligence might be achievable by 2025***.

As of today, we are still teaching AI to drive cars or translate text, which humans are able to do with ease. Nevertheless, AI technology has already started to change and disrupt many industries. The speed of that change will continue to accelerate. Experts continue to debate whether superintelligence will develop consciousness. The ethics of AI is currently a big, multidisciplinary effort spanning across areas like philosophy, ethics, computer science and law.

Machine Learning – is the process of training AI models with small amounts of data to speed up the process of learning. AI requires vast amounts of structured and annotated data that exemplify desired behaviors in order to work. Machine learning helps to significantly reduce the amount of data that is needed by using algorithms to deduce all possible or relevant conclusions.


AI has the ability to help humans solve many problems. Its most common applications include:

  • Data tagging (identifying objects on images and audio),
  • Quality assurance,
  • Auto summarization,
  • Machine Translation,
  • Speech recognition,
  • Natural Language Generation.

Machine translation is one of the most common types of AI. It helps companies bridge language barriers and translate content faster and for a fraction of the cost. Legal companies in the U.S. frequently use Machine Translation to help with multilingual eDiscovery processes. Machine Translation is used to “convert” large amounts of documents into one common language so the material can be easily analyzed. The ability to translate these documents effortlessly, at scale, and in a cost-efficient manner allows legal professionals to understand the gist of the content and make better decisions about their cases. This is becoming increasingly important in times of cross-border ecommerce and highly intertwined global economy.

Machine Translation also allows translators and companies to reduce translation costs while handling more content, serving many more markets, and decreasing the amount of time it takes to bring marketing collateral to market. This is a great illustration of how AI is driving change in multiple industries. It is enhancing productivity and its throughput is allowing humans to focus on more value added activities. The rise in marketing activities – along with an increased need for content creation and translation – has fueled the growth of companies like Lionbridge and the localization and translation industry as a whole.

Natural-language generation (NLG) is a technology that helps generate text when it is given just a few initial words. A great example of this is applying it to product specifications to generate a fulltext product description that can be used for e-commerce experiences.

Auto-summarization, or the process of generating a summary from long documents, helps readers understand text faster by distilling the essence of the content without the involvement of humans. This technology helps people analyze text faster and make better decisions based on data that matters.

AI is also gaining ground in Life Sciences. It is heavily used for the analysis of patient data in order to come up with diagnoses. IBM’s Watson is a great example of this. Watson is being trained on data from leading U.S. health institutions to automate and increase accuracy of diagnoses. In addition, Google’s DeepMind team has recently created an AI that helps recognize breast cancer from X-ray images with estimated 99% accuracy. Less false positives, and faster turnaround times gives doctors more time with their patients. Many pharmaceutical companies are also looking to use AI to speed up testing for active compounds that would become the basis of future medicines****.


Robotic process automation (RPA) is the use of software (ro)bots or AI digital workers to automate mundane processes. It can handle tasks like opening email and attachments, moving files and folders, copying and pasting text, and filling out forms. In the past, people primarily used it for well defined and predictable processes.

However, recent developments in the technology have made it possible to automate more processes. Because of this, RPA may be regarded as a risk to the BPO industry. In Deloitte’s recent “Global RPA survey,” the CEOs of surveyed companies estimated that about 20% of the work in their enterprises could be automated by RPA tools and that this development would more likely hit BPOs*****. Interestingly, the same study claims that 61% of the companies surveyed were able to reduce costs as a result of RPA, which enabled them to re-allocate resources to other, higher-value tasks. Therefore, many companies and BPOs are embracing RPA and AI in their business practices. As of 2020, 72% of companies are expected to experiment with and deploy RPA.

RPA is coming, no matter what, and it will change the way companies operate. The good news is that most companies do not expect to reduce their workforce. Instead, they expect to assign their teams more rewarding tasks. Ultimately, they will be able to unlock unprecedented levels of efficiency. Companies that do not embrace these trends soon will fall behind.


AI will disrupt the BPO industry in many ways by:

  • helping companies automate simple and mundane tasks,
  • augmenting human workers and allowing them to focus on higher value tasks,
  • providing managers with insights into complex decision-making processes,
  • changing how companies work and increasing their business velocity,
  • increasing work efficiency and reducing costs.

Using AI in your business practices will most likely turn out to be transformative. It will help you release the full potential of your workforce, help you shift their focus to activities that provide more value, and allow them to spend more time with your customers. The successful deployment of AI technologies requires a wellthought-out strategy and needs to include three important elements: AI technology, data, and humans. Combining these three elements is essential for success.

The BPO industry can benefit significantly from using AI and increasing value-added activities to their enterprise. It also creates an opportunity to transition from low value-added services to higher level services that are sought by the high-tech sector. AI will be beneficial in many ways, but if ignored, it has the potential of making the company lagging or even obsolete on the marketplaces of the future.

Author: Kajetan Malinowski, Senior Product Director, Lionbridge

Innovative product and business leader. Experienced in digital transformation, operationalizing, productizing and scaling new business models. Focused on taking latest Natural Language Processing and Artificial Intelligence technology and translating it into successful products.



*** Elon Musk claims AI will overtake humans‚in less than five years’ | The Independent | The Independent

**** improving-breast-cancer-screening