Frankenstein and the Future of the BPO Industry: What AI Is Really Asking Us to Build
Frankenstein's mistake was not creating something powerful. It was failing to take responsibility for what he created. That is the lesson I see for businesses today.
I recently watched Frankenstein on Netflix, and surprisingly, it made me think about the future of the BPO and service industry.
Not because of the monster.
Because of the creator.
The tragedy of Frankenstein is not simply that he created something extraordinary. It is that he created something powerful and then failed to understand how to nurture, guide and take responsibility for what he had built.
That story feels remarkably relevant to where we are with Artificial Intelligence today.
We are building something incredibly powerful.
The real question is whether we are prepared to build the business around it.
AI is not the threat. Our inability to adapt is.
For many organisations in the BPO and service industry, AI can initially look like a threat.
If AI can automate work, what happens to revenue?
If fewer people are required to handle transactions, what happens to the traditional staffing model?
If clients can achieve more with fewer FTEs, how do service providers continue to grow?
These are legitimate questions.
But I think we may be looking at the problem from the wrong direction.
AI is not simply something that will take away the business models we have today.
It can also be the technology that helps us build the next business models.
The opportunity is enormous, but only if we stop trying to protect yesterday's model and start designing for tomorrow.
1. Value over time: We need to rethink how we charge for work
One of the biggest changes I expect to see is the movement away from traditional pricing models based primarily on attendance, hours or FTEs.
For decades, the economics of much of the BPO industry have been closely tied to how much human capacity a client needs.
But what happens when technology allows the same outcome to be delivered with significantly less human effort?
The model has to evolve.
I believe we should be preparing for a future where resolution-based pricing and other outcome-oriented commercial models become much more important.
Imagine being rewarded for solving a customer's problem rather than simply handling a transaction.
The focus shifts from:
How many people are working?
to:
What value are we creating?
That is a fundamental change.
And it is also an opportunity.
Providers that can confidently price around outcomes will be in a much stronger position than those trying to defend volume-based models forever.
2. Lead the disruption instead of waiting for it
There is a natural tendency in large organisations to wait.
Wait for clients to ask.
Wait for competitors to move.
Wait for technology to mature.
Wait until the business case becomes obvious.
I think that is risky.
The organisations that benefit most from AI will likely be those willing to disrupt themselves before someone else does it for them.
That means looking honestly at our own processes and asking:
What can we automate internally?
Where are we carrying unnecessary costs?
Which activities create little value?
Which client-facing processes can be redesigned?
Where can AI improve the experience rather than simply reduce headcount?
Internal automation can improve margins.
Client-facing automation can improve the value we create.
Neither should automatically be viewed as revenue loss.
The better mindset is:
We are not removing value. We are upgrading the value we deliver.
3. The human element becomes more valuable, not less
There is an interesting contradiction in an AI-driven world.
As machines become better at routine interactions, human interaction becomes more valuable.
AI can process information quickly.
It can summarize.
It can classify.
It can automate repetitive tasks.
It can handle large volumes of routine work.
But empathy is different.
Judgment is different.
Trust is different.
Understanding an emotionally difficult customer is different.
Solving an unusual problem that does not fit neatly into a model is different.
That is where I believe our people can become even more important.
Instead of asking employees to spend their days handling repetitive tasks, we should be moving them toward work that requires high EQ, empathy, creativity and complex problem-solving.
The future should not be about having fewer valuable people.
It should be about having people doing more valuable work.
4. From doers to orchestrators
This may be one of the biggest workforce changes AI will create.
For years, many service roles have been designed around doing the work directly.
Handling the ticket.
Answering the query.
Processing the transaction.
Completing the task.
As AI takes on more execution, our people will increasingly need to become orchestrators of technology.
That means understanding how AI works, guiding it, monitoring it and stepping in when situations fall outside predefined boundaries.
An employee's role may evolve from:
I perform the task.
to:
I make sure the technology performs the task correctly.
That is not a demotion.
I see it as a promotion of the workforce.
But it requires a very different approach to training.
We cannot simply train a small group of specialists and expect the rest of the organisation to remain unchanged.
We need to start preparing everyone.
5. Trust can become a product
As AI becomes more deeply integrated into business processes, another major opportunity will emerge.
Trust.
Businesses will need confidence that AI systems are reliable, secure, compliant and operating within defined boundaries.
That creates an opportunity for the BPO and service industry to go beyond traditional delivery.
AI governance, quality assurance, risk management, monitoring and human oversight can potentially become part of the service proposition itself.
In other words, we may eventually be able to sell not just AI-powered work, but trusted AI-powered work.
That distinction could become extremely important.
Technology may become increasingly accessible.
Trust will not.
6. Mastery will matter more than generalisation
AI has changed the economics of general knowledge.
A lot of information that once required years of experience to access can now be researched, summarized or explained almost instantly.
That does not make expertise irrelevant.
It makes deep expertise more valuable.
The professionals who will continue to stand out will not necessarily be those who know a little about everything.
They will be people who understand a particular industry, process, customer type or operational problem at a level that AI alone cannot easily replicate.
For WFM, for example, knowing how to generate a forecast is not enough.
Understanding why demand behaves the way it does, how different operational variables interact, how customers behave, how business decisions affect staffing and when a model is wrong is much harder to replace.
That is where domain mastery matters.
Go deeper.
What does this mean for the BPO industry?
I think we are approaching a significant turning point.
The old model was largely built around people delivering predefined services at scale.
The emerging model could be built around a combination of:
People + AI + automation + domain expertise + measurable outcomes.
That could fundamentally change how service providers compete.
The question will no longer simply be:
How many people can you provide?
It may become:
What business outcome can you deliver, how intelligently can you deliver it, and how confidently can you stand behind that outcome?
That is a much more interesting industry.
And what does it mean for leaders?
Leadership becomes incredibly important during this transition.
It is easy to fear disruption when the existing business model is still generating revenue.
But protecting a model simply because it works today can be one of the biggest risks for tomorrow.
Leaders need to create environments where teams can experiment, fail responsibly, learn quickly and rethink how work gets done.
They also need to make some uncomfortable decisions.
What work should disappear?
What capabilities should we build?
What skills should our people develop?
How should we change our commercial model?
How much human intervention should remain?
What does trust and governance look like?
These are not technology questions.
They are leadership and business strategy questions.
The Frankenstein lesson
This is the part of the movie analogy that stays with me.
Frankenstein's mistake was not creating something powerful.
His mistake was failing to take responsibility for what he created.
That is the lesson I see for businesses today.
We should not be afraid of creating powerful AI systems.
We should be afraid of creating them without knowing what we want them to accomplish, how we will govern them, how our people will work with them and what our business looks like once they become part of the operating model.
AI gives us an opportunity to rethink the industry from the ground up.
We can defend the old model.
Or we can build the next one.
My take
I do not believe the future of the BPO and service industry is about humans versus AI.
It is about what happens when we deliberately combine the strengths of both.
AI can take on scale, speed and repetitive execution.
People can bring empathy, judgment, creativity, context and accountability.
The organisations that figure out how to combine those capabilities will have a significant advantage.
But that will require us to stop asking:
How do we protect our current business from AI?
And start asking:
What could our business become because AI exists?
That is a much more powerful question.
Because we are not simply building the next piece of technology.
We are building the next version of the industry.
And this time, we need to make sure we know how to nurture what we create.
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Adapted and expanded from my post on LinkedIn.