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As artificial intelligence continues to reshape modern business, revenue operations (RevOps) is emerging as a central force in redefining go-to-market (GTM) strategies. Companies adapting to AI-enhanced sales and customer engagement must evolve their GTM approaches to remain nimble, insights-driven, and aligned with the new realities of an AI-powered market.
To better understand this transformation, we spoke with Roshin Unnikrishnan, Senior Director of Growth and Revenue Operations at Cisco. A recognized leader in RevOps, GTM strategy, and management consulting, Unnikrishnan has spent over a decade driving growth and operational excellence across North America, Europe, and Asia. His leadership has been pivotal in Cisco’s transition to a recurring revenue model, the redesign of a 17,000+ member sales coverage strategy, and the integration of major acquisitions—including Splunk’s $28 billion merger—into Cisco’s GTM approach. A former Engagement Manager at McKinsey & Company, he also contributed to groundbreaking research on automation and the future of work. Beyond his corporate influence, he is a member of the Forbes Business Council, where he shares insights on revenue growth and operational strategy.
“AI is doing more than enhancing productivity—it’s fundamentally changing how we build and scale revenue models,” says Unnikrishnan. “Organizations that thrive will be those that elevate RevOps into a core growth strategy.”
Where RevOps was once seen as a support function focused on pipeline management and sales efficiency, today it’s evolving into a strategic pillar for growth. AI is enabling hyper-personalized customer experiences, allowing companies to tailor each interaction based on predictive data. According to McKinsey, firms using AI-enhanced GTM strategies are achieving 10–20% improvements in sales productivity by leveraging real-time behavioral insights and targeted engagement.
“AI is revolutionizing how sales teams operate,” Unnikrishnan explains. “We’re moving away from intuition-led selling toward a model where every action is informed by predictive analytics. This isn’t just incremental improvement—it’s a structural change in how companies deliver value, engage prospects, and compete on price.”
AI’s impact goes deeper than the customer experience—it’s also driving strategic realignment within revenue operations. From automated lead scoring to intelligent pricing models and proactive customer retention strategies, AI is helping organizations anticipate demand and respond in real time. Harvard Business Review recently reported that AI-driven sales enablement tools are boosting conversion rates by as much as 50%, emphasizing the competitive advantage of embedding AI within GTM operations.
To succeed in the AI-first landscape, companies must not only adopt new tools but also rearchitect their GTM structures. Unnikrishnan has played a key role in Cisco’s shift to a data-first sales model, including the overhaul of its global sales coverage strategy. His leadership in optimizing a 17,000+ person salesforce highlights the critical need for teams to operate from unified, AI-informed insights.
“In today’s GTM landscape, rigidity is a liability,” he says. “Organizations must design their sales and marketing teams to act on live insights, not fixed workflows. The winners will be those who break down silos and build cross-functional teams around shared intelligence.”
When it comes to integrating acquisitions into this new GTM paradigm, an additional layer of complexity arises. The $28 billion Splunk acquisition by Cisco stands as a testament to the urgency to align differences in revenue models, tech stacks, and customer engagement styles. "Integrating a major acquisition like Splunk means aligning not just platforms, but philosophies," says Unnikrishnan. "Achieving synergy at scale requires a unified GTM framework powered by automation and intelligent data pipelines."
The AI-led GTM transformation, which Unnikrishnan consistently asserts in his thought leadership, also appears in his latest feature on Benzinga. His take on this is that AI is not just optimizing existing sales motions but redoing the very architecture of revenue. Revenue intelligence trumps process automation if any organization is to take the lead in a transforming business environment.
However, as AI becomes deeply embedded in GTM operations, it also raises new concerns around data stewardship. Unnikrishnan cautions that companies must prioritize strong data governance to ensure the accuracy and fairness of AI-driven decisions. “The quality of AI output depends entirely on the data that feeds it,” he says. “Without disciplined data management, companies risk making flawed decisions that could compromise growth.”
Looking ahead, Unnikrishnan envisions a future where revenue operations play a decisive role in shaping business performance. For Unnikrishnan, now a judge at the Globee Awards for Business Excellence, "In the AI era, companies winning will be those treating RevOps as revenue-making powerhouses, not just operational cost centers. This includes investing much more in AI-powered intelligence, integrating sales and marketing processes completely, and continuously optimizing GTM motion with real-time data."
