When headcount stops being the metric, GCC growth stories are shaped by productivity
AI has already begun to upend that equation. Today, the conversation inside many technology companies is no longer centred on how many engineers they can hire, but on how effectively those engineers can work alongside AI. Productivity, rather than workforce size, is emerging as the metric that matters.
“No company is 100 per cent sure yet as to how this is all going to play out,” says Adler, Chief Technology and Product Officer, N-able.
What the company is seeing already, however, is difficult to ignore. Software development cycles are shrinking, product teams are delivering features faster, and AI is beginning to alter long-held assumptions about how technology organisations scale. “Our ability to deliver features end-to-end, that cycle time is shrinking by large multiples,” Adler says.
The observation captures a pivotal moment not only for N-able but for the wider software industry. As AI becomes embedded into engineering workflows, technology companies are being forced to rethink everything from talent strategy and product development to leadership structures and performance measurement.
For N-able, the challenge extends beyond its own operations. The company, which provides cybersecurity and business resilience solutions to more than 500,000 organisations globally through MSPs, is simultaneously trying to understand how SMBs will adopt AI and what role cybersecurity players will play in that transition.
“How can I use AI and get it in the hands of SMBs so they can use this really advanced technology?” Adler asks and this question sits at the centre of the company’s next chapter and increasingly, at the centre of the cybersecurity industry’s future.
Why Bengaluru?
The opening of N-able’s Bengaluru centre this June is part of that larger story. The company operates multiple technology and innovation centres globally, but India represents a strategic investment at a time when cybersecurity, AI and product engineering capabilities are becoming critical differentiators.
Yet Adler is quick to point out that the decision was not driven by the traditional logic that once defined GCCs. “We actually thought long and hard about where we wanted to invest,” he says.
The leadership team evaluated multiple cities before arriving at Bengaluru. What stood out was not merely the depth of technical talent but the concentration of professionals with experience building products for global markets.
“Bengaluru is known for its rich product expertise and IT expertise across the board,” Adler says. “We felt like that would be a great opportunity.”
The city’s ecosystem, he argues, offers something many technology companies increasingly seek which include the engineers, product managers and AI specialists who have worked inside large-scale global product organisations.
Equally important was the city’s trajectory. “Bangalore has one of the largest populations of IT talent, but most importantly, it’s still growing,” Adler says. “We invested here because of that growth rate in IT and product talent.”
At a time when technology companies are competing intensely for specialised AI and cybersecurity skills, growth potential matters as much as present-day availability.
The Bengaluru centre currently supports engineering, product management, user experience and security operations functions, with plans for further expansion as N-able deepens its investment in India.
The evolution beyond delivery
The story of cost optimisation gradually became one of capability building. More recently, the focus has shifted again towards product ownership, innovation and IP creation.
Kiran Rooge, India Site Lead and Head of Engineering, believes the Bengaluru centre is at the beginning of that journey. “We are focusing on being part of the core teams and core products,” he says.
The emphasis is notable. Rather than operating as a parallel organisation, the India team is embedded within global product initiatives, contributing to key areas including endpoint management, AI capabilities, threat detection and security operations.
Rooge sees ownership emerging organically rather than through executive mandates. “It is not something you plan. It’s something which evolves over time,” he says. “As our employees go deeper into products, understand the depth, understand the technology and understand the business, this will all eventually result in owning something bigger.”
The philosophy reflects a broader shift visible across India’s technology ecosystem, where global companies increasingly view Indian engineering teams as strategic contributors rather than execution engines.
For N-able, the immediate focus remains integration, capability building and participation in core product development.
The larger responsibilities may follow naturally.
Building an AI-first organisation
For many companies, AI initiatives are still confined to pilot projects or isolated productivity experiments. N-able executives shared that they are attempting something broader.
Adler describes his responsibilities today as extending across three interconnected fronts. The first involves embedding AI across the business itself from internal systems and support functions to go-to-market operations. “How are we internally using AI to build a better and more efficient business?” he says.
The second involves product delivery. Technology leaders have spent years attempting to accelerate software development without sacrificing quality. AI presents an opportunity to attack both objectives simultaneously.
N-able’s teams, as claimed by their executives, are already seeing changes in how products are designed, developed and delivered. “We want to up our pace of innovation and create better outcomes faster for our customers,” Adler says.
The third challenge may be the most complex: understanding how customers themselves will consume AI. Cybersecurity companies occupy a unique position in the AI transition. They are not only adopters of the technology but also responsible for helping customers navigate its opportunities and risks. For SMBs, many of which lack large internal technology teams, the stakes are particularly high.
N-able executives shared that their objective is to bridge that gap. “We’ve always said, how can we help a SMB consume technology used at the enterprise level?” Adler says. “AI is the latest and probably one of the most important ones.”
Measuring what matters
If AI changes how software is built, it also changes how success is measured. Traditional technology metrics often revolve around workforce growth, team size and output volume. Adler argues that new measures are emerging.
The first is speed. “How much faster can we get the job done from beginning to end?” he points out.
Cycle time, the duration between idea and delivery, has become a critical indicator of whether AI investments are producing tangible results.
The second metric is quality. “We’re actually looking at an increased quality level,” Adler says. “Can we do what we were doing, but at an even better, higher quality level?”
The distinction is important. The goal is not simply to produce more software. It is to produce better software, faster. That aspiration may ultimately define which companies benefit most from the AI transition.
While the technology itself is becoming increasingly accessible, organisational capability remains far more difficult to replicate.
Preparing for the next wave
Cybersecurity has rarely stood still. Cloud computing transformed infrastructure. Remote work reshaped enterprise security. Regulatory requirements altered compliance priorities.
AI now represents the next major inflection point. For N-able, as mentioned by their executives, that shift is influencing product development, talent strategy and customer engagement simultaneously.
The company’s recent investment in Bengaluru reflects that reality. “Opening our Bengaluru office is an important step in how we scale true business resilience by investing in a market with deep technical talent,” says John Pagliuca, Chief Executive Officer, N-able.
He sees India playing a broader role in helping organisations address cyber risk, compliance requirements and operational complexity. Adler frames the opportunity in more technological terms.”With deep expertise under one roof in Bengaluru, we’re fast-tracking the next generation of capabilities from AI-powered innovation to modernised security operations,” he says.
The comments point to a larger industry truth. The next chapter of technology will not be defined solely by where companies hire or how many people they employ. It will be shaped by how effectively they combine human expertise, AI and organisational knowledge to solve increasingly complex problems.
For companies like N-able, that experiment is already underway and its success may ultimately be measured not by headcount, but by what a smaller, smarter and increasingly AI-enabled workforce can achieve.
