As Deepwatch cut the ribbon on its new GCC in Bengaluru, the conversation quickly shifted from celebration to blunt realities shaping the future of cybersecurity and jobs. The first signal came when Deepwatch’s Chief Product Officer, Anand Ramanathan, stated without hesitation, “AI is more efficient than humans.” The remark, delivered at an event meant to highlight investment and growth, immediately set the tone for a strikingly honest discussion on automation, talent, and the cyber arms race.
Ramanathan clarified that efficiency did not automatically translate into the replacement of human intelligence, at least not in the current landscape. Cyberattacks, he pointed out, shifted patterns constantly. “Attackers don’t do the same thing every day. One day it’s WhatsApp, another day it’s a completely new avenue. This is the constant cat-and-mouse game we play,” he said, adding that humans still excelled at reacting to unseen scenarios “where we consistently see the best outcomes is when AI works together with human judgment. That combination is far more powerful than either one alone.”
Ramanathan was not blind to the long arc of AI evolution. He acknowledged that autonomous cybersecurity might become real someday, saying, “I look forward to the day when cybersecurity becomes fully autonomous, if it ever happens.” Until then, he believed the most reliable security posture rested on human–AI collaboration, especially when adversaries remained unpredictable.
Open tension between automation and employment
The discussion on talent surfaced almost immediately. Deepwatch had recently laid off close to 60–80 employees, raising the question of whether talent could be reskilled fast enough to keep pace with AI-driven transformation. John DiLullo, Chief Executive Officer, Deepwatch, did not attempt to disguise the seriousness of the moment, instead he said, “Lower-skill roles are becoming harder to deploy. The people you have may not always be the people you need.”
DiLullo also stressed that Deepwatch remained deeply committed to employee training and skill development, but the labour market itself was undergoing an irreversible transition. “The old days of Tier-1 support, ‘Is the power on?’ are gone. Where we deploy our cyber experts today is much further up the chain,” he stated. He warned that this shift affected multiple industries, not just cybersecurity. “Globally, people will have to pick up new skills very quickly and adapt very quickly. There is no way around it,” he added.
Why Bengaluru?
Against this global backdrop, Deepwatch’s investment in India gained more nuance. Senior leaders described the Bengaluru facility as a key engineering and technology hub in the company’s global expansion plan. The centre aimed to accelerate product innovation and development velocity with deep integration between engineering and threat research, supported by a follow-the-sun operational model for 24×7 cybersecurity.
DiLullo gave a direct insight into why Bengaluru won over competing cities. He said, “There’s a culture here that aligns with a young, fast-moving company. People are willing to take risks, build something new, and join a seven-year-old company instead of a 100-year-old one.” He noted that the city’s unique blend of AI talent, cybersecurity expertise, and cloud engineering capabilities was a blessing. “If there is a place to build the future of cybersecurity, this is the place to do it,” he shared.
India at the centre of NEXA and agentic AI development
Deepwatch planned to use the GCC to advance its NEXA agentic AI ecosystem, where multiple AI agents collaborated with human analysts to improve detection and response accuracy. Ramanathan confirmed that many of these capabilities were being built in Bengaluru. “Having product, engineering, and domain expertise together in this centre means we’re building AI that is grounded in real-world threat behaviour. That is where the breakthroughs happen,” he said.
Prasad Channabasappa, VP Engineering and Managing Director, Deepwatch India, reinforced the strategic intent. “This centre is not an execution engine; it is a co-creation hub. Threat analysts sitting next to engineers means we build what customers actually need, not what we assume they need.” He expected Bengaluru to become the primary source of platform innovation for the company over time.
Measuring GCC success, not by headcount but by cyber outcomes
While many GCCs across industries experienced pressure to justify their ROI, DiLullo outlined Deepwatch’s definition of success clearly. “Sales will follow. What matters today is whether customers are safer, whether we respond faster, whether we can do more for them with less effort and less cost,” he said.
He also added that sustained customer satisfaction and service levels were the ultimate barometers. “If my NPS goes up, my CSAT goes up, my ticket count goes down, and we go two quarters without violating an SLA, I don’t need a single other metric to tell me whether we are innovating,” DiLullo shared.
GenAI: Encouraged, but controlled
The leaders claimed that Deepwatch’s internal approach to GenAI balanced productivity with responsibility. They shared that employees were encouraged to use AI to optimise productivity, but the company enforced safeguards to avoid “shadow AI” risks. “We don’t discourage GenAI usage; we want people to be fluent in these tools,” mentioned DiLullo. “But our machines are locked down and company data doesn’t go into public models. We have our own corporate ChatGPT instance for that,” he added. He also shared that when employees achieved dramatically higher productivity through AI, it was celebrated rather than policed.
The company’s future success metrics also reflected the strategic shift. For DiLullo, the GCC was deemed successful not by its headcount or real-estate footprint, but by how effectively it strengthened customer protection. “If we can automate cybersecurity, respond faster, deliver stronger detections, and do it at a lower cost, that’s the trifecta. Most say you can only get two of those. I want all three, and I believe India can deliver it.” He cited recent quarters with zero SLA violations as early proof that the model worked.
A shift from scaling through workforce to scaling through intelligence
The inauguration of the Bengaluru GCC marked a defining pivot for Deepwatch, from scaling through workforce to scaling through intelligence. While layoffs and the acceleration of AI may have come with uncomfortable headlines, the company’s leadership remained unequivocal that the transformation was not optional. The cybersecurity battleground was changing, they argued, and organisations that did not evolve fast enough, talent included, were left behind.
While Deepwatch was unapologetically investing in AI-driven automation, it was also betting heavily on human-in-the-loop expertise. Innovation in cybersecurity, NEXA development, threat research, and 24×7 MDR all required human judgment and contextual thinking.
This duality reflected the future of work in cybersecurity, whether AI took over tasks that were repetitive, manual, error-prone, and time-consuming, or humans moved upward toward analytical, strategic, and complex decision-making.
However, that transition was not painless. The skills gap was widening, and those unwilling or unable to reskill felt the displacement most sharply. Companies, meanwhile, raced to balance automation efficiency with human value.
As Deepwatch began its India journey, the Bengaluru GCC is not just a new office; it is also a test case for whether AI and humans could advance cybersecurity together, rather than at the expense of one another.