Key Points
- Over 90 per cent of BPM customers are discussing AI adoption
- 50 to 60 per cent of 1Point1 proposals now include outcome-based pricing models
- BPM economics shifting from labour arbitrage to intelligence arbitrage
Generative AI is beginning to alter the economics of the business process management (BPM) industry, pushing companies away from traditional headcount-led models towards hybrid operations where technology handles high-volume, predictable work while humans remain central to judgement, trust and accountability, a top executive at 1Point1 Solutions said.
Nitin Mahajan, CEO – India at 1Point1 Solutions, told TechObserver.in’s Mohd Ujaley in an interview that more than 90 per cent of customers are discussing AI and over 50 per cent want to adopt it in some form, with a growing share of new engagements carrying an AI component.
EVENT
Infosec Reimagined
Infosec Reimagined 2026 is the premier information security summit where top leaders—CISOs, CROs, CIOs, CTOs and risk executives—converge to redefine cyber resilience.
EVENT
Digital Senate
Digital Senate is a premier conference uniting government leaders, technologists and innovators to share ideas, success stories and strategies on digital governance, public sector transformation, cybersecurity and emerging technologies in India.
EVENT
CIO Prism
CIO Prism unites forward-thinking technology leaders to exchange transformative insights, shape digital strategies, and foster innovation, empowering enterprises to excel in an era of rapid technological change.
EVENT
National DefTech Summit
Featuring keynotes, expert panels, live tech demos and strategic networking, the summit will drive actionable insights for defence sector.
EVENT
Future-Ready Defence
A Leadership Dialogue on sovereign, trusted data infrastructure, AI readiness and mission resilience for Defence Forces.
The bigger shift, Mahajan said, is in how BPM services are being commercialised, with clients increasingly looking at outcomes such as customer retention, speed of resolution, collections, recovery and fraud prevention rather than simply the number of people deployed.
“The economics is shifting from labour arbitrage to intelligence arbitrage,” he said, adding that differentiation in an industry where companies may have access to similar AI models will increasingly come from workflow design, AI orchestration, domain expertise and the ability to operationalise the technology against measurable business outcomes.
Edited excerpts:
Generative AI adoption has accelerated significantly. How do you assess its adoption in BPM and how is 1Point1 approaching this shift?
GenAI, a category of artificial intelligence that can create text, images and other content, is the talk of the town today and there has been a good amount of traction in adoption over the last six to 12 months. We as an organisation identified this some time ago and were able to build around it. That is where our core focus on hybrid intelligence comes from.
If I look at the industry, AI adoption is often equated with chatbots or simply layering GenAI on existing workflows. We take it a little differently. For us, an AI-led business is one where intelligence is embedded into how work is executed, measured and then commercialised.
Advertisement
Today, a significant and growing share of our engagements runs on a hybrid model. The industry is already talking extensively about this and almost all BPM players have some form of AI embedded into their operations. Most BPM companies have experience in running or managing processes, but differentiation also comes from the platform being used. In our case specifically, we have been able to leverage these capabilities within our own platform without key hand-offs.
In terms of overall acceptance, almost every customer is talking about it. I would say more than 90 per cent of customers are discussing it, more than 50 per cent want it and, in some form or another, almost everything new that has happened over the last six months to a year has some flavour of AI.
BPM has traditionally been a headcount-driven business. As AI brings intellectual capital into the equation, do you see the industry’s commercial model changing?
Absolutely. Historically, BPM economics was driven more by effort. More agents meant more revenue. That has now been fundamentally challenged by this new model.
The future model will increasingly be outcome-driven rather than headcount-led. Clients will start paying for business results rather than purely for the number of people involved. They will look at outcomes such as customer retention, speed of resolution, collections, recovery, fraud prevention or whatever business problem they are trying to address, rather than looking purely at FTEs (full-time equivalents), the standard measure of staffing levels.
This change is already visible and, in our view, it will strengthen further over the next 12 to 24 months, depending on how organisations are able to adapt internally. The challenge is not only about asking us or other partners to deliver differently. It is also about organisations internally accepting those changes.
At 1Point1, we have already started moving towards this model, with a significant portion of our commercial engagements increasingly linked to these parameters and outcome-based KPIs (key performance indicators). By and large, 50 to 60 per cent of our proposals now carry both an FTE-based as well as an outcome-based model. I think the economics is shifting from labour arbitrage to intelligence arbitrage, where value comes from workflow design, primarily AI orchestration and domain expertise.
As automation expands across BPM operations, which functions do you expect to be automated first and where will humans continue to play a critical role?
First and foremost, people are going to stay. Human intelligence will continue to be needed. Today and perhaps for the next couple of years, even for critical and medium-complexity work, some QC (quality control), and checks will still be required.
The first wave of automation will focus more on volume-based and rule-based actions, similar to some of the work RPA (robotic process automation), which uses software to handle repetitive digital tasks, has historically done. On the customer experience side, tier-one queries such as billing updates, order tracking, appointment scheduling, onboarding support and routine service requests will be impacted. In operations, areas such as data validation, QC, document processing, reconciliation and workflow routing will also be affected.
To my mind, two of the most important areas that will be positively impacted are quality monitoring and compliance checks. Historically, because of cost constraints, organisations often limited such monitoring to around 1 per cent or a limited number of interactions. With AI, both the economics and the ability to handle volume will favour moving the balance towards a hybrid model.
Take something such as speech-to-text or our frequency product. Listening to entire calls manually takes considerable time. Technology can do that in less than half the time, but it will still have to be blended with a quality evaluator or coach who can interpret the output and coach people to change based on those findings.
Fundamentally, the volume-intensive work gets done through technology while the qualitative work is done by humans. That is where the human role becomes even more important in areas involving judgement, trust and accountability. Areas such as fraud investigations and financial hardship, particularly in collections, will continue to be driven by humans.
Enterprise AI projects often begin with enthusiasm but organisations become cautious once they encounter deployment challenges. How should companies balance existing processes with AI-led disruption?
If we are talking about an existing layer and an existing way of working, the question is how to strike a balance between the way things were done in the past and AI-driven disruption. That is actually why, while customers are discussing these things and taking proposals around them, they are also conducting self-assessments and internal assessments to determine how much they should open up to fully autonomous actions by bots or AI and how much should remain in a blended form.
A large part of the approach is about taking balanced risks and moving in baby steps. Automate the easier tasks first. For other areas, let GenAI take the decision, have humans review it and then take it forward. Slowly, once confidence is built, those capabilities can be released more openly. That is broadly the shape this transition is taking.
Our philosophy is that AI is not replacing humans. AI is empowering humans. The strongest governance model is one where AI handles the predictable while humans own the consequential. That is how you balance the two and create a win-win situation.
Most large BPM companies will ultimately have access to the same foundation models. If the underlying models become common, where will differentiation come from?
There used to be an old saying that it is not the car but the driver who decides the way. Perhaps that applies to this situation as well. If the models are common, it will not be the input that differentiates companies. It will be how the technology is deployed and that will primarily be driven by our learnings and our exposure, including how the process flows are designed and how the actual impact is measured.
It is not simply about automation in the way traditional automation used to work. It is more about the intelligence being used to leverage these technologies and create an output. That is why we say the biggest challenge is not the technology. It is the operationalisation of that technology. Even when similar models are being used, accuracy remains a challenge in highly regulated or domain-specific environments. GenAI can lack context in those situations. That gap can be bridged only through experience.
How do you assess the India market for 1Point1 and where does it stand within your broader APAC strategy?
We recently completed an acquisition that was integrated through the last week of March. If you have followed our results, they would reflect some of the impact of that integration on our APAC market. Our focus on that market is high and there is dedicated attention around it.
Coming specifically to India, I think we are very strongly placed. We are focused on leveraging ResolX, which is our core platform and enables hybrid capabilities, combining the GenAI capability of the platform with the process capabilities that we have built over the last 17 years. In terms of growth, BFSI continues to be a focus area for us. At the same time, we are expanding into other areas, including utilities, consumer durables, electronics and mobile phones.
By the numbers
- 90%+
- BPM customers discussing AI adoption
- 50-60%
- 1Point1 proposals with outcome-based pricing
- 17 years
- 1Point1 platform development experience
Beyond BFSI and large enterprises, what opportunity do you see in utilities, the public sector and government-facing services?
With power distribution being privatised, I think there is a very good opportunity across India. We are seeing opportunities across both the public and private sectors. Without taking names, there are large Indian public sector entities and back-end service providers that are today discussing how they can positively impact citizens by creating GenAI-based or simpler solution-based architectures that customers or citizens can leverage for their benefit. Ease and simplicity are central to that. We are therefore seeing this segment being actively pursued as well.
As enterprises move from experimenting with AI to deploying it at scale, what will determine whether these projects succeed over the next six to 12 months?
What we see is that a lot of the traction, queries and challenges emerging over the next six to 12 months will not be about what AI can do. They will be about what we want AI to do. The primary issue is that people who are trying to use AI purely as a cost-cutting opportunity may end up facing a different set of challenges.
The projects that succeed will primarily be those that begin with a business outcome rather than a technology objective, where AI is expected to solve a measurable problem rather than simply cut costs. Otherwise, the risk of AI becoming an expensive experiment is pretty high.
Your Questions, Answered
How widespread is AI adoption in the BPM industry?
According to 1Point1 Solutions CEO Nitin Mahajan, more than 90 per cent of BPM customers are discussing AI and over 50 per cent want to adopt it. Almost all new engagements over the past six to 12 months have included some AI component.
How is BPM pricing changing because of AI?
Mahajan said BPM is shifting from headcount-based pricing to outcome-based models. Clients increasingly pay for business results such as customer retention, resolution speed and fraud prevention rather than purely for the number of staff deployed. At 1Point1, 50 to 60 per cent of proposals now include outcome-based pricing.
Which BPM functions will be automated first?
Volume-based and rule-based tasks will be automated first, including billing updates, order tracking, appointment scheduling, data validation and document processing. Quality monitoring and compliance checks will shift to hybrid models. Fraud investigations and tasks requiring judgement will remain human-driven.
What will differentiate BPM companies when they all use similar AI models?
Mahajan said differentiation will come from workflow design, AI orchestration, domain expertise and the ability to operationalise technology against measurable business outcomes. The challenge is not the technology itself but how it is deployed and measured.