With the rapid development of artificial intelligence technology, the traditional outsourcing industry is facing unprecedented changes. This article will explore how AI is disrupting the $300 billion outsourcing market, from AI customer service to AI collection to the automation of back-end operations, AI is gradually replacing traditional human outsourcing work. The article will also analyze the transformation dilemmas and opportunities of the outsourcing industry under the impact of AI, and how AI startups can emerge in this change.
AI subverts outsourcing and is becoming the consensus of the AI industry.
Vinod Khosla, one of OpenAI’s earliest investors and one of Silicon Valley’s most famous venture capitalists, once said that by around 2030, a large number of jobs will disappear and the outsourcing industry (BPO) will be completely replaced.
Manny Medina, founder of AI unicorn Outreach, even believes:
As long as a certain field is highly dependent on BPO (Business Process Outsourcing), it means that AI Agent has a huge room for entry.
In other words, where there is outsourcing, there are opportunities for AI entrepreneurship.
This is not true at all. Nowadays, a number of AI startups have emerged around outsourcing service scenarios, such as AI customer service Decacon , Salient using AI to collect, Outset using AI to do questionnaires, and using AI to reshape the Owl.co of insurance claims.
There are various signs that the outsourcing industry in the AI era is undergoing a round of profound changes. In this change, the only thing that is certain is that the traditional human-driven outsourcing business has completely ended.
01 Where there is outsourcing, there are opportunities for AI entrepreneurship
Outsourcing is often engaged in repetitive and transactional work, such as data entry, call center operations, revenue cycle management, invoice reconciliation, etc.
Don’t look at these things as inconspicuous, but the outsourcing market is much larger than you think.
To achieve these three challenges, product managers will only continue to appreciate
Good product managers are very scarce, and product managers who understand users, business, and data are still in demand when they go out of the Internet. On the contrary, if you only do simple communication, inefficient execution, and shallow thinking, I am afraid that you will not be able to go through the torrent of the next 3-5 years.
View details >
Outsourcing companies like Cognizant, Infosys, and Wipro all generate between $10 billion and $20 billion a year. Roughly estimated, the global outsourcing industry market size will exceed $300 billion in 2024.
It is such an industry that exceeds $3,000 and is becoming the first to be completely disrupted by AI. This has even become a consensus in the AI industry.
Daniel Priestly, a well-known British entrepreneur, believes that millions of workers around the world engaged in business process outsourcing (BPO), especially in India and the Philippines, may lose their livelihoods due to AI automation. He cited data that the global BPO industry employs about 9 million people, of which 70% of jobs can be replaced by AI, affecting millions of people.
What’s even more frightening is that such predictions are becoming a reality.
Not long ago, Duolingo CEO Luis von Ahn publicly posted a memo to employees on LinkedIn, announcing that the company will phase out the use of outsourcing to do the work that AI can handle.
Coincidentally, global payment giant Klarna announced the recruitment of new customer service staff to establish a flexible customer service system like Uber. The purpose of this is to replace thousands of outsourced agents.
The reason why Klarna is replacing outsourcing is simple: AI is here. According to Klarna CEO Nordstrom:
“AI robots still account for two-thirds of the total customer service consultations, and the customer service response time is 82% shorter than before the AI was launched, and the number of duplicate questions is also reduced by 25%.”
But Nordstrom also explained why he built his own customer service team, saying, “In an era where automation is prevalent, truly high-quality human interaction is invaluable. That’s why we double down on human service: empathy, professionalism and genuine communication. ”
In other words, in this AI-induced efficiency change, customer service positions are still there, but they are outsourced.
The Philippines is the world’s second-largest BPO market after India, with 1.84 million BPO employees. In June last year, Philippine Labor Secretary Bienvenido Laguesma told local media that some workers had lost their jobs due to artificial intelligence. Industry estimates that artificial intelligence could cause 300,000 Filipinos to lose their jobs in the next five years.
In the view of Manny Medina, CEO of AI unicorn Outreach, outsourcing has even become an opportunity for AI entrepreneurship.
Manny Medina believes:
As long as a field is highly dependent on BPO (Business Process Outsourcing), it means that AI Agents have a huge amount of room to enter.
And Medina’s claim has become a reality.
02 From AI customer service to AI collection, AI transformation outsourcing is in progress
At present, a number of AI startups have been born, covering narrow application scenarios with high friction, relying on a lot of manual operations, and often relying on BPO (business process outsourcing) services, and have achieved certain results.
Crow Jun has compiled some successful business cases of AI in the field of traditional outsourcing and shared them with you:
AI customer service field:
1) Decagon data transparency and build customer service agents based on usage scenarios
Founded in 2023, Decagon has grown rapidly since its inception.
Its AI agents are based on state-of-the-art models from companies like OpenAI, Anthropic, and Cohere, and are trained on internal data such as how-to guides, manuals, and past customer service conversations. Employees score and review AI-generated responses to improve the system. Decagon also allows businesses to have a clear view of the decision-making process as well as data usage.
In February, Decagon partnered with AI audio generation leader ElevenLabs to create voice agents to engage in more natural, human-like conversations with customers.
Decagon has helped several businesses save on customer service outsourcing costs.
Credit card provider Bilt has reduced its customer support team from hundreds to 65 with Decagons. Fitness giant ClassPass used Decagon’s AI agents to conduct 2.5 million conversations with customers, reducing customer support costs by 95%.
To date, Decagon has signed contracts worth more than $10 million. The company is negotiating a new $100 million funding round, led by a16z and Accel, with a post-investment valuation of $1.5 billion.
2) HappyRobot, redefining logistics management with AI customer service
In the cargo logistics industry, brokers and carriers need to connect with a large amount of supplier and retailer information every day, and conduct targeted matching and dispatch orders. Previously, this simple work was mostly done by manpower.
HappyRobot uses an artificial intelligence voice agent system to provide 24/7 operation agents, providing an intelligent logistics information service platform that handles all calls and emails at one time. Since its launch, it has cooperated with more than 50 freight forwarding operators, including Flexport, Job & Talent, Spot Inc., and Syfan Logistics, with a response efficiency of 100% and an efficiency increase of more than 4 times.
In December last year, HappyRobot closed a $15.6 million Series A funding round led by a16z, valuing it at $89.5 million.
3) Salient, AI collection efficiency increased by 60%
In the past, bank collection work required a lot of manual work, but now such work can be done by AI.
Salient primarily leverages AI voice call technology to automate collection in the auto loan sector. Specifically, Salient uses its AI agents to engage with consumers in real-time through various channels such as voice, text, email, and web chat. These interactions are designed to handle a range of tasks, such as collecting payments, handling due date changes and extensions, managing repayments, and updating insurance information.
Back-end Operations:
1) Outset, AI reinvents questionnaires
Outset is an AI research product.
While traditional survey and questionnaire software requires manual design of questions, collection of data, and analysis of results, Outset’s AI Agent can automate these tasks and adjust questions and answers in real-time based on user feedback, improving the efficiency and accuracy of surveys.
Outset’s AI interviewers are capable of speaking, listening, and reacting in real-time, with follow-up questions that reveal the crucial “why” behind participants’ responses.
What started as a text-based tool has evolved into a powerful multimodal tool. Today, Outset can deploy video and voice interviews across multiple languages, share visual content, test live websites, and distill complex data into actionable insights in minutes.
2) Quandri, which uses AI to automatically renew policies
Quandri has launched an intelligent personal renewal platform that automates workflows from existing broker management systems (BMS) to help improve employee productivity.
Quandri’s core features are twofold: Renewal Reviews, which automatically identify and notify brokers of key insights during the renewal process; and Policy Requoting, which automatically offers multiple competitive offers when premium increases are detected.
Unlike other InsurTech solutions that require brokers to perform tasks manually, the Quandri platform offers a “software as a service” model, leveraging artificial intelligence and robotic process automation (RPA) to automate tasks without broker intervention. Additionally, the platform opens up access to policy data, allowing brokerages to easily identify trends in performance across different insurers, regions, and teams, ultimately enhancing customer service.
3) Owl.co, AI reinvents insurance claims
The value of Owl.co lies in the use of AI to significantly streamline claims processes and decision-making.
Specifically, it achieves this by meticulously analyzing massive amounts of internal and external claims data. This focused approach minimizes the time insurers spend processing each claim, allowing them to dedicate more resources to customer service when it matters most.
Currently, Owl.co customers cover most of the top 20 insurance companies in North America.
Why can AI replace the BPO industry now? There are four main reasons:
1) Software-like speed: Perform tasks efficiently without human intervention, with response times measured in milliseconds.
2) Round-the-clock service: 24×7 hours of uninterrupted operation, no overtime pay, and barrier-free service to global customers across time zones.
3) Multilingual and cultural adaptation: Possess natural language understanding (NLP) capabilities and can easily support multiple languages and cultural scenarios.
4) High scalability and low cost: The deployment and expansion costs are much lower than those of manual outsourcing teams, and they can flexibly cope with peak business periods.
03 The role of outsourcing has changed
In the face of the impact of AI, traditional outsourcing giants such as Wipro, Infosys, and Accenture have announced increased investment in AI.
- Sanjeev Jain, chief operating officer of Wipro, said that AI adoption in existing projects has surged by 140%;
- Infosys announced that it has deployed more than 100 new generative AI assistants in its customer base;
- Accenture, which focuses on consulting and outsourcing services, disclosed that new contracts for generative AI projects reached $1.2 billion;
But the transition to AI for these outsourcing companies is not easy. On the surface, there is a fundamental conflict between native AI products and the BPO business model.
Most outsourcing uses an hourly billing model with a 20-30% increase on the cost of labor, and its business model relies on hiring employees and selling human output to customers. If this model is transformed into a product-first model, it will face more challenges: profit margins will be significantly compressed, existing cash cattle businesses will be stifled, and corporate culture will be forced to transform.
This is a difficult change for any business, not to mention a listed company that is always voted on by investors.
From a deeper logic, the competitive logic of the outsourcing industry is changing: technology is reshaping the logic of the outsourcing industry.
In the past, when software capabilities were limited, the core competencies of traditional outsourcing companies were mainly reflected in deep customer relationships and integration with outdated systems. In the era of AI, technology will become the main force driving the business process of the outsourcing industry.
Specifically, outsourcing has always been a passive service model in the past, and customers only regard outsourcing as a cost center and try their best to reduce costs.
But in the era of AI, outsourcing services are becoming an important part of product services and even driving revenue growth.
For example, for most brands, the call center is the only direct opportunity for the brand to engage with users.
The dialogue between customers and users is also the “golden data” of analyzing users. However, in the past, due to the lack of appropriate technical means, the reasons and logic behind these data were not really excavated.
Now, through AI technology, enterprises can mine intents and sub-intents in every call, conduct competitive analysis, product insights, and feed back all information to product departments. For example, there is a problem with your product because 200,000 complaints are all about the same feature.
In other words, the customer center will no longer be a “cost center” but the best platform for customer demand insights. In this process, outsourcing service providers are no longer an extension of the labor force, but also a technology provider.
Along this logic, outsourcing companies that relied solely on human resources in the past will no longer exist, and the value of outsourcing service providers will also depend on the value of the AI services they integrate.
