Business Process Outsourcing is a $300 billion industry built on a promise that feels increasingly absurd at a time when AI can diagnose cancer or drive autonomous vehicles: that the most efficient way to handle your back-office operations is to have humans in another country manually key invoice data.
If this sounds like the setup to a particularly brutal economics joke, that’s because it is. BPOs represent perhaps the most spectacular example of technological arrested development in modern business. They’re the proverbial fax machine that somehow persisted into the age of quantum computing—an economic anachronism, the dinosaurs that somehow survived the meteor strike of automation.
But their days are numbered.
The Fundamental Truth of BPOs: Labor Arbitrage as a Business Model
Let’s start with what BPOs actually do, stripped of the consultative veneer and digital transformation branding. BPOs take over your manual, repetitive processes through geographic labor arbitrage. Full stop.
The major players—Cognizant ($19.8B revenue), Infosys ($19.1B), Wipro ($10.8B), and others—have built empires on a simple value proposition: “Your back-office work is too expensive to do in-house, so we’ll do it cheaper elsewhere.”
The growth metrics are impressive, to be sure. The BPO market topped $300 billion in 2024 and is forecasted to reach $525 billion by 2030, growing at about 9.4% annually. Industry giants like Accenture boast about operating in 200+ cities across 50 countries. Genpact proudly maintains over 100,000 employees.
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Yet there’s an absurdity at the heart of this model that becomes more glaring with each AI breakthrough. In an era where AI agents can not only run — but build — entire software applications, enterprises still rely on offshore BPO employees to manually key in invoice data, reconcile accounts, and process payroll exceptions.
It would astonish most to learn just how many people are involved in accounts payable processes at major enterprises, how many manual exceptions are handled daily, and how much poor master data quality drives these inefficiencies. The uncomfortable reality is that BPOs exist largely because of—and profit from—these inefficiencies, not in spite of them.
This isn’t just inefficient—it’s intellectually indefensible.
BPOs Are The Brute Force of the Unholy Trinity
How did we get here? The answer requires a brief historical detour.
As outlined in “AI Will Shatter The Back-Office Industrial Complex ,” the enterprise back office sits at the center of what I call the “Unholy Trinity”: ERP vendors, the Big Four accounting firms, and BPO providers. Each vertex exists in perfect symbiosis with the others, creating a system so deeply entrenched it makes the military-industrial complex look like a weekend hobby project.
ERPs, as we explored in “Inescapable ERP Complexity is a Business Model, Not a Bug ,” create byzantine systems that require armies of developers fluent in arcane frameworks and languages. The implementation complexity creates pockets of manual, repetitive work that are too expensive to automate but too mission-critical to eliminate.
Enter the BPOs, providing the brute force solution to this complexity: humans as integration middleware.
Need to get data from one system to another without a proper API? Have a human copy-paste it. Need to validate complex regulatory compliance? Have a human check boxes on a form. Need to reconcile inconsistencies between ERP modules? Have a human with a desktop procedure do it.
A core challenge in these environments is simply collecting and integrating data. For something seemingly straightforward like transportation cost analysis, the data might be scattered across three different systems: internal fleet data, third-party vendor systems, and spot market auction platforms. It’s not uncommon for employees to spend half their time just aggregating this data before any actual analysis can begin.
Over time, this relationship evolved into something more insidious. BPOs deliberately manufacture stickiness through three clever mechanisms:
- Knowledge absorption: They siphon institutional knowledge out of your organization and encode it in proprietary desktop procedures
- Procedural opacity: These procedures become increasingly complex over time, with that complexity intentionally hidden from customers to create leverage
- Custom infrastructure: They build custom systems to support these workflows, ensuring maximum pain for any customer attempting to leave
The result is a perfect self-reinforcing cycle: More complexity → more labor → more revenue → more complexity.
The True Cost of BPOs
The immediate appeal of BPOs is straightforward: cost reduction through labor arbitrage. “Your AP clerk costs $75,000 fully loaded in Chicago? We can provide one for $22,000 in Manila.” This simple math drives initial outsourcing decisions, but it masks the true costs.
Let’s break down what you’re really paying:
Hard costs:
- Direct labor costs (with 20-30% markup)
- Management overhead (your internal team managing the BPO relationship)
- Integration costs (connecting your systems to their workflows)
- Change request fees (modifying processes when your business needs evolve)
Soft costs:
- Institutional knowledge trapped in BPO procedures
- Disempowerment of internal teams
- Process opacity
- Reduced innovation and adaptability
- Customer and supplier experience degradation
The most pernicious aspect is how these costs compound over time. The longer a process remains outsourced, the more dependent you become on the BPO’s knowledge and systems. What started as a simple labor cost arbitrage becomes an intellectual property hostage situation.
Take post-payment audits as an illuminating example. Companies often pay their vendors on tight timelines due to regulatory requirements (especially in industries like alcohol and tobacco). Later, they conduct audits to verify they paid the correct amounts. An entire cottage industry exists to detect and recover these overpayments for a percentage of the recovery.
The economic incentive for these recovery specialists is perverse: they have no reason to fix the underlying process problems. If they did, they would eliminate their own revenue stream. Instead, they happily collect millions in recovery fees year after year without addressing the root causes that created the errors in the first place.
Yet enterprises continue with this model despite the drawbacks. Why? Three primary reasons:
- Sunk cost fallacy: “We’ve already invested so much in this relationship.”
- Path dependency: “Bringing it back in-house would be too disruptive.”
- Institutional amnesia: “We’ve outsourced this so long, we don’t remember how to do it ourselves.”
Perhaps most telling is the BPO industry’s primary success metric: headcount growth. Think about that. In 2025, when every other industry measures success by efficiency gains and automation, BPOs celebrate adding more humans to processes.
Industry standard contracts typically include “committed productivity” clauses—agreements to reduce headcount by perhaps 10% year-over-year through efficiency improvements. But these modest targets have historically been difficult to achieve without technology enablement. The true growth strategy for BPOs has been to expand into new functions or processes even as they marginally improve existing ones, ensuring net headcount growth.
It’s like measuring a software company’s success by how many lines of code its developers write.
The Coming Conflict Between BPOs and AI
BPOs face an existential threat from AI, and it’s not the one they’re preparing for.
The fundamental business model mismatch is stark: BPOs charge on a time-and-materials basis with a 20-30% markup. Their entire economic engine depends on maintaining human labor as the atomic unit of value. More hours worked equals more revenue.
This creates a perfect misalignment with AI’s core promise: increasing productivity by automating routine cognitive tasks.
BPOs know this, of course. That’s why every major player has announced ambitious AI initiatives. Wipro trumpets a “140% increase in AI adoption.” Infosys boasts about its “100+ gen AI agents.” Accenture claims “$1.2B in gen AI bookings.”
But these initiatives won’t save them for a simple reason: their incentive structure remains fundamentally opposed to full automation.
Here’s an example that perfectly captures this contradiction. Consider a BPO that implements an AI-powered invoice processing system reducing processing time by 40%. The natural question follows: doesn’t this mean they’ll make 40% less revenue on these contracts?
The standard response is revealing: “We’re redeploying those resources to higher-value activities.”
Translation: “We’re desperately trying to find new ways to bill for human time before our customers realize they don’t need us anymore.”
The problem for BPOs isn’t just that AI can automate button-pushing. It’s that AI breaks the economic logic of their entire industry by:
- Eliminating the labor arbitrage advantage: AI doesn’t care if it runs in Chicago or Chennai
- Automating decision-making: Not just repetitive tasks but contextual judgment calls
- Democratizing specialized knowledge: Making expertise available without human intermediaries
- Driving the marginal cost of process customization toward zero: Making it economically viable to automate even niche workflows
When you examine the process pyramid of BPO activities, the potential for disruption is staggering. For basic processes at the bottom of the pyramid, industry experts privately acknowledge automation potential of 40-50%—with some processes approaching 80%.
Consider invoice processing, which currently employs vast numbers of people globally. The traditional approach involves receiving an invoice, validating it, checking for purchase order matches, and handling numerous manual exceptions (rate/quantity mismatches, duplicates, etc.). In an agentic AI world, this entire workflow can be transformed with AI-led extraction, validation, and classification, triggering exceptions only when truly needed. The result could be 80% touchless invoicing—a revolution for a process that currently employs hundreds of thousands of people worldwide.
BPOs’ supposed AI initiatives are like a horse-and-buggy manufacturer’s attempt to compete with automobiles by breeding slightly faster horses. The paradigm shift is too fundamental.
From BPO Outsourcing to AI Insourcing
The coming transformation isn’t just a matter of automating existing processes. It’s about a complete reimagining of what back-office operations can be.
The transition from manually keyed invoice processing to AI-powered solutions isn’t just “the same thing but faster.” It’s a fundamentally different approach that transforms static records into intelligent assets—what I call the agentic back-office.
Imagine back-office entities that don’t just sit waiting for human intervention but actively pursue goals:
- Invoices that can validate themselves against purchase orders and contracts
- Accounts receivable balances that can determine the optimal collection strategy
- Expense reports that can contextualize policy exceptions and make judgment calls
This isn’t automation as BPOs understand it — a macro that follows predefined steps. Rather, it’s autonomous operation by entities that understand context, learn from patterns, and make decisions.
There’s a crucial distinction here: Traditional generative AI might create content, make predictions, and generate reports. But agentic AI takes this further by actually making decisions. It examines content and determines whether something is acceptable or requires attention. This capability is fundamentally different from what BPOs currently offer.
And thus, the revolution won’t come from within the BPO industry. It can’t. Their incentives are too misaligned, their operations too wedded to human labor as a value unit. It will come from outside, from companies built around AI as the fundamental building block rather than human effort.
Just as fintech disrupted traditional banking not by digitizing existing processes but by reimagining what financial services could be, AI-native companies will reinvent back-office operations from first principles.
The shift from the labor-intensive BPO model to AI-driven operations will happen gradually, then suddenly. The economics are simply too compelling, the advantages too overwhelming.
What Comes Next?
Industry insiders recognize the divergent futures ahead for different types of BPOs. Pure customer service providers face particularly acute challenges as their work is most vulnerable to automation, and the stories like those shared by Klarna are the writing on the wall.
For more transactionally-oriented BPOs, growth will become harder to achieve, but margins could actually improve. You can already see in the last two years the ever so slight re-inflection upwards of revenue per employee in our charts above.
The fact of the matter is that BPOs have survived far longer than their fundamental business model should have allowed, protected by the complexity moat of enterprise operations. But AI is draining that moat rapidly.
The $300 billion question is: when will your organization recognize that the future doesn’t include humans manually keying data in Manila, but intelligent systems that handle routine cognitive work autonomously?
The BPOs are living on borrowed time. The loan is coming due.
CoPlane is building the intelligent finance operations platform that can eliminate the need for BPO labor entirely. Want to learn more? Drop us a line.