The Most Influential Cloud & AI Growth Leaders to Watch in 2025

1. WWW.THECIOTIMES.COM | 2025 CIOTIMES EMPOWERING ENTREPRENEURIAL EXCELLENCE 2025-2026 Architect of Growth at the Intersection of AI, Cloud, and Partnerships

4. The Most Influential Cloud & AI Growth Leaders to Watch in 2025 n an era defined by rapid digital transformation, the leaders shaping the cloud and AI landscape are not just I technologists; they are visionaries driving exponential growth, innovation, and industry disruption. Among them is Kunal, a trailblazer whose strategic foresight and hands-on expertise have positioned him at the forefront of this dynamic ecosystem. Kunal's journey is a testament to the power of combining technical acumen with business insight. From architecting scalable cloud solutions to pioneering AI-driven frameworks, he has consistently demonstrated an ability to translate complex technology into tangible business outcomes. His work has empowered enterprises to optimize operations, enhance customer experiences, and harness data-driven insights that fuel decision-making at every level. What sets Kunal apart is not just his technical brilliance but his forward-looking perspective. He anticipates market trends, identifies growth opportunities, and fosters innovation cultures that turn ambitious ideas into reality. Whether it's mentoring emerging talent, leading cross- functional teams, or speaking at industry forums, he exemplifies the leadership qualities that define today's most influential figures in technology. As we look toward 2025, the impact of cloud computing and AI on global business will only intensify. Leaders like Kunal are not merely participants in this evolution; they are catalysts, shaping the future of industries and redefining what's possible in the digital age. For organizations seeking guidance and inspiration, his journey offers a blueprint for leveraging technology to drive sustainable growth, innovation, and transformative change. In a world where technology evolves at breakneck speed, following the path of visionaries like Kunal is essential for those eager to stay ahead of the curve and witness the future being written today.

6. Kunal Kapoor

7. 20 The Productivity Paradox Will AI Growth Truly Transform Workforce Efficiency? 24 Edge Meets Cloud Redefining Real-Time Intelligence for Enterprises

11. C O V E R S T O R Y Architect of Growth at the Intersection of AI, Cloud, and Partnerships

12. ew leaders can claim to have pioneered AI equipping him to bridge the worlds of innovation and adoption when it was nascent, built billion-dollar business strategy. F ecosystems, and shaped the way Fortune 500 That foundation proved critical at IBM, where he joined companies embrace digital reinvention. Kunal Kapoor has the early Watson team. His mission: bring AI out of the done all three. Today, as a growth leader in AI and Cloud, lab and into boardrooms. “It wasn't about algorithms,” he he is redefining how enterprises scale, how ecosystems recalls. “It was about showing executives how AI could thrive, and how technology translates into measurable drive efficiency, new revenue streams, and industry outcomes. reinvention.” Kunal shares, “AI is no longer the future of work — it's the Scaling Ecosystems at Microsoft new operating model for enterprises.” The real inflection point came at Microsoft. There, Kunal As a growth leader at the forefront of AI and Cloud, he has built and scaled partnerships that delivered growth at consistently turned emerging technologies into business unprecedented scale. His most visible success: expanding outcomes, scaling partnerships, driving $500M+ alliances, the ServiceNow-Microsoft alliance from a $45M practice and shaping the future of autonomous enterprises. to over $500M global powerhouse business in just 18 The Microsoft veteran's impact goes beyond financial months. outcomes. He is recognized for enabling responsible AI adoption, ecosystem innovation, and new ways of working This wasn't just about sales. It was about building a global that prepare enterprises for the future. operating model. Over the last two decades, he has consistently turned Ÿ Clarity of the North Star — everyone from sellers to engineers knew the shared goals. emerging technologies into business outcomes — scaling Ÿ End-to-end orchestration — growth came when partnerships, driving $500M+ alliances, and shaping the product, sales, and leadership executed in sync. future of autonomous enterprises. Beyond revenue, his Ÿ Negotiation through value — framing partnerships impact is recognized in responsible AI adoption, around customer impact, not corporate politics. ecosystem innovation, and GenAI partnerships that prepare enterprises for the next decade. The outcome: it became one of Microsoft's top three He adds,” Cloud isn't infrastructure anymore, it's the global partnerships, CEO-sponsored and product-aligned, growth engine for global industries.” reshaping how enterprises adopt AI and cloud at scale. But his influence extended far beyond ServiceNow. Kunal From Curiosity to Commercial Impact also: Kunal's journey began in 2002, when he came to the U.S. Ÿ Pioneered GenAI partnerships with Azure OpenAI and as a first-generation immigrant to pursue computer embedded Copilot across enterprise workflows. science, fueled by curiosity and resilience. He was Ÿ Explored transformative alliances, such as BlackRock's determined in his belief that technology can be a catalyst Aladdin on Azure, planting seeds that became a $30B for transformation. AI infrastructure fund. Ÿ Built multi-partner plays with Accenture, KPMG, and Early consulting work across insurance, healthcare, and Wipro, aligning consulting giants to Microsoft's AI finance gave him a front-row seat to how technology roadmap. reshapes business models and unlocks EBITDA impact through efficiency and modernization. As Kunal often tells his teams, “Partnerships aren't PowerPoints — they're operating systems.” At Lord Abbett, he launched one of the firm's first AI/ML risk models; an experience that sparked his passion for Driving the Agentic AI Era at Genpact emerging technologies. Determined to sharpen his commercial skills, he pursued an MBA at Columbia, Today, as a senior Partner at Genpact, Kunal leads high-

15. growth businesses across AI, Cloud, and SaaS; with a BlackRock's Aladdin on Azure required crystal-clear special focus on Agentic AI. His teams are embedding alignment on the growth thesis before execution. autonomous agents into Source-to-Pay, Finance, HR, IT Ÿ End-to-end orchestration — spanning executive and Supply Chain, delivering outcomes at scale. sponsorship, engineering, product alignment, and co- created solutions. Breakthroughs such as the Ÿ AI agents that cut reconciliation work by 60%. integration of Microsoft Copilot with ServiceNow's Now Assist happened only because product roadmaps Ÿ Cloud-native workflows that shorten cycle times by were aligned, not just sales plays. In the same way, 40%. embedding autonomous agents with Genpact clients today requires orchestrating between SaaS providers, Ÿ Agentic task managers and Copilot / Agentforce GenAI platforms, and domain expertise across IT, integrations that free employees to focus on higher- finance, and supply chain. value work. Ÿ Ÿ Negotiation through value creation — reframing “The real promise of Agentic AI isn't generating text,” he partnerships around unlocking true customer impact notes. “It's generating outcomes CFOs can take to the rather than dividing revenue. In alliances like board.” Databricks–NVIDIA, the value story centers on reducing the cost of AI training and inference for Innovation Across Ecosystems enterprises. With Genpact, the focus has been on demonstrating how Agentic AI translates into Beyond Microsoft and ServiceNow, Kunal has advised efficiency gains or financial outcomes in the form of and driven ecosystem partnerships comprising software client savings. By grounding negotiations in sales with: measurable client outcomes, speed and scale follow naturally. Ÿ Databricks and NVIDIA, shaping joint narratives Navigating global complexity further required discipline around AI/ML platforms and accelerated computing. Ÿ HighRadius, Xelix, and Blackline, bringing GenAI into and trust. From structuring joint GTM models in North finance transformation at scale. America to enabling co-sell across Europe and APAC, Ÿ Salesforce and AWS ecosystems, aligning AI-native every market presented its own nuances. Transparency, workflows with industry-specific GBS transformation. consistent communication, and equipping local teams with both tools and flexibility proved essential. This breadth underscores his ability to grow not just one alliance, but an entire portfolio of AI, SaaS, and Cloud Integrating Technology Right ecosystems. Asked about how businesses can best leverage AI and Scaling these partnership-focused sales and alliances Cloud, Kunal highlights three imperatives: data, requires far more than signing agreements; it means scalability, and responsible adoption. AI and Cloud, he designing and executing a global operating model capable stresses, are not IT projects but business strategies. of delivering at scale. The principles that proved most valuable throughout his career include: “The winners of the Agentic Decade will treat AI as a collaborator, not a tool.” Ÿ Clarity of the North Star — establishing a shared vision and defining precisely what will be taken to Agentic AI exemplifies this promise. It streamlines market together. Success comes when every seller and workflows, embeds intelligence into processes, and frees delivery team understands how joint offerings translate humans to focus on higher-value tasks. Cloud platforms into outcomes and targets. For example, in scaling the then provide agility — enabling enterprises to innovate Microsoft–ServiceNow partnership, this meant quickly, test faster, and scale globally without friction. aligning Azure, GenAI services, and workflow platforms globally. Similarly, initiatives like

16. The Agentic Decade Looking ahead, Kunal believes the next decade will be defined by Agentic AI — a shift as transformative as SaaS in the 2000s and Cloud in the 2010s. Ÿ Self-optimizing processes — IT, HR, Supply Chain, Finance, and Procurement that continuously adapt. Ÿ Radical productivity gains — not 10% lifts, but 3x - 5x leaps. Ÿ Democratized innovation — AI agents enabling every employee to become a “citizen innovator”. “The winners will be those who treat AI not as a tool, but as a collaborator.” Valuing Partnerships As an advisor to private equity-backed SaaS firms, Kunal spotlights the most common pitfall. For him, it is treating partnerships as transactions rather than growth, overseeing them as a chance for triumphant expansions. He points out the thoughts of SaaS firms. They think once they sign a Lessons from Big Wins deal with Microsoft or AWS, the revenue will flow effortlessly. In reality, his principle is “partnerships are Behind the $500M+ enterprise deals, and global programs living systems, they need joint value propositions, co-sell are principles Kunal carries forward: motions, and constant nurturing.” Ÿ Trust is built in hallways, not just boardrooms. Relationships drive outcomes. Another pitfall he brings to notice is the over-reliance on a Ÿ Technology alone doesn't win. Business cases that single channel. Mid-cap or PE-backed firms often bet too deliver EBITDA lift and resilience earn executive heavily on direct sales or one hyperscaler. He guides them conviction. to build balanced GTM portfolios across ISVs, GSIs, Ÿ Scaling requires orchestration. From engineering MSPs, and CSPs so growth is both accelerated and de- alignment to revenue-sharing, success comes when the risked. system works as one. Concluding on this, he emphasizes the measurement of the Growth Synergy right metrics. It's not just about partner-sourced revenue, but partner-influenced pipeline, joint product adoption, and Kunal's philosophy is about balancing near-term revenue ecosystem stickiness. with long-term transformation. At Microsoft, that meant initiatives like BlackRock's Aladdin on Azure; planting the Innovation Across the Globe seeds that later grew into a $30B joint AI infrastructure fund. At Genpact, it means driving SaaS and AI adoption Kunal is principled about the team being clear to show today while co-creating the foundations for the outperformance. The team should be aware of their work's autonomous enterprise of tomorrow. impact on the client outcomes. At Genpact, his approach to success extends beyond EBITDA impact to include “When you anchor every motion in client outcomes, productivity gains and cost efficiencies that strengthen growth follows naturally. That's how you drive both client agility and resilience. By ensuring teams see their quarterly performance and multi-year transformation.” efforts translate directly into measurable business

17. outcomes, he fosters a deeper sense of purpose and alignment. In this quote, he adds curiosity and being a cultural fit. If ADVICE FOR someone embodies those traits, the rest can be taught. That philosophy has guided his hiring and team-building THE NEXT GENERATION across every role. He believes scaling innovation requires both structure and freedom. His approach has been to provide teams with the guardrails of a clear go-to-market strategy, Kunal's advice to the next defining which products to co-sell and how to engage generation of leaders: clients while allowing space for experimentation and creativity. This balance has enabled the adoption of Agentic AI at scale, moving beyond pilots to deliver Stay curious, not comfortable. measurable productivity outcomes for Fortune 500 clients. Technology will keep changing, curiosity is your edge. At its core, his leadership philosophy centers on building high-performance teams by balancing near-term revenue with long-term innovation, and by driving hard financial Learn to tell stories with data. results while fostering a culture where people can do the The best technologists and best work of their careers. salespeople connect tech to human He shares a reminder statement of his team: “Innovation outcomes. doesn't happen because of titles; it happens because people feel safe to try.” Build your tribe. Success in tech Building Teams, Building Legacies isn't solo — it's ecosystems, partnerships, and communities. Beyond numbers, Kunal is equally passionate about culture. He leads with Buffett's maxim of intelligence, energy, and integrity — adding curiosity and cultural fit Don't fear failure. As he tells his to the mix. His teams are encouraged to experiment daughters: “Perfection doesn't teach boldly within the guardrails of a clear strategy. you; mistakes do.” “Innovation doesn't happen because of titles,” he reminds them. “It happens because people feel safe to try.” For clients, his legacy will be measurable: not just digital transformation, but business reinvention. For people, it will be pathways: ensuring the next generation of leaders — especially from underrepresented backgrounds — thrive in technology. “Growth isn't numbers on a chart. It's shaping industries, building ecosystems, and creating outcomes that matter.”

20. THE PRODUCTIVITY PARADOX Will AI Growth Truly Transform Workforce Efficiency? 20 I September 2025 theciotimes.com

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22. rtificial intelligence (AI) has become one of the In most cases, AI augments rather than substitutes human defining technologies of our time. Its promise is labor. For example, radiologists use AI systems to detect A immense: from automating routine processes to anomalies in scans more quickly, but human expertise enabling advanced decision-making, AI is expected to remains essential for final diagnosis and treatment reshape how enterprises function and how people work. planning. Yet despite its rapid growth, a puzzling reality persists: productivity gains have not always matched the scale of When AI is deployed as a partner rather than a investment. This gap between expectation and outcome is replacement, the result is not just faster work but smarter often referred to as the productivity paradox of AI. work. However, achieving this synergy requires training, trust, and thoughtful change management elements that The Promise of AI many organizations are still developing. At its core, AI offers three major benefits to the workforce: Organizational Transformation speed, scale, and accuracy. Machines can process vast amounts of data in seconds, automate repetitive tasks with Another reason for the paradox is that AI growth demands near-perfect precision, and generate insights that humans structural transformation. Automating one task in isolation might overlook. In theory, this should create enormous may save minutes, but embedding AI into end-to-end efficiency gains. processes can redefine entire workflows. Consider a law firm adopting AI to review contracts. The real productivity Customer service chatbots reduce call-center loads, gains do not come from faster document analysis alone, predictive analytics streamline supply chains, and but from reimagining how cases are prepared, how client intelligent document processing eliminates manual interactions are managed, and how legal research is paperwork. With these advances, one might expect conducted. productivity statistics to show a sharp upward trend. Yet, in many economies, productivity growth has remained Organizations that view AI as a tactical add-on may see modest, raising questions about whether AI is living up to incremental efficiency. Those who treat it as a catalyst for its promise. business model innovation are more likely to unlock transformative gains. This distinction is why AI growth Understanding the Paradox sometimes appears uneven; leaders who embrace systemic change reap benefits, while others remain trapped in the The paradox is not that AI fails, but that its benefits take paradox. longer to materialize. Historically, transformative technologies from electricity to the internet have often Workforce Challenges required decades before their full impact appeared in productivity data. This lag reflects the time it takes for The workforce itself also influences outcomes. Upskilling organizations to adapt processes, redesign systems, and employees to work effectively with AI is essential. cultivate the right skills. Without the right digital literacy, workers may underutilize or even resist AI tools, blunting their impact. Moreover, AI is no exception. While the technology itself may be trust plays a significant role. If employees view AI as a powerful, realizing its potential requires cultural shifts, threat to their jobs rather than an enabler of better redefined workflows, and significant investment in human performance, adoption will be slow and uneven. capital. Simply installing AI tools without rethinking how work is organized often leads to limited returns. Forward-looking organizations invest not only in technology but also in cultivating a culture of learning and Human-AI Collaboration collaboration. By empowering employees to leverage AI, they turn potential resistance into enthusiasm, bridging the A critical element of resolving the paradox lies in how gap between growth in AI capabilities and realized humans and AI collaborate. The misconception that AI productivity. will directly replace human workers oversimplifies reality. 22 I September 2025 theciotimes.com

23. implemented strategically. Measuring Productivity Differently The transition, however, is uneven. Enterprises that treat It is also worth asking whether traditional productivity AI as a quick-fix technology will continue to struggle metrics fully capture AI's contributions. Standard measures with modest returns. Those who recognize AI as part of a often focus on output per hour, which may miss qualitative broader transformation requiring cultural change, skills gains such as improved decision-making, enhanced development, and process redesign will be positioned to innovation, or reduced risk. For example, AI may not realize its full potential. immediately increase the number of financial reports a firm produces, but it can improve the accuracy of those Conclusion reports and the quality of strategic decisions based on them. The productivity paradox of AI does not reflect a failure of the technology, but a lag in adaptation. History shows As AI redefines work, productivity itself may need that revolutionary technologies take time to permeate redefinition. The question is not only how much work is industries, and AI is no different. Over the next decade, done but how intelligently it is performed. as enterprises mature in their adoption and integration, AI is likely to become a true engine of workforce The Road Ahead efficiency. Will AI growth ultimately resolve the productivity The real question is not whether AI can transform paradox? Evidence suggests yes, but gradually. As productivity, but whether organizations are willing to organizations integrate AI more deeply, reengineer rethink work itself to unlock that transformation. For workflows, and upskill their workforces, productivity enterprises ready to adapt, AI's growth will indeed gains will become more visible. Early adopters in sectors redefine efficiency not as a promise, but as a measurable like logistics, healthcare, and financial services are already reality. demonstrating how AI can reshape efficiency when theciotimes.com September 2025 I 23

24. Redefining Real-Time Intelligence for Enterprises 24 I September 2025 theciotimes.com

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26. he digital enterprise is evolving at unprecedented increasingly rely on real-time decision-making. In speed. With every transaction, device interaction, healthcare, for example, connected devices that monitor T and customer engagement, organizations are patient vitals cannot afford delays in transmitting data to generating enormous volumes of data. Traditionally, this cloud hundreds of miles away. Edge ensures life-critical information was sent to centralized cloud platforms for insights are delivered instantly, with the cloud serving as a storage and analysis. While the cloud offers scale, long-term repository for deeper analysis and learning. flexibility, and global accessibility, it is not always designed for the immediacy that modern businesses Cloud and Edge: A Symbiotic Relationship demand. This is where the convergence of edge computing and cloud technologies is redefining real-time intelligence Contrary to popular belief, edge computing does not for enterprises. replace the cloud it enhances it. The edge provides immediacy, while the cloud ensures scalability, global Why Edge Now Matters coordination, and advanced analytics. Together, they form a hybrid model where intelligence is distributed Edge computing shifts processing power closer to the data seamlessly. source, whether that is a sensor on a factory floor, a retail checkout, or a self-driving car. Instead of routing all Enterprises can deploy lightweight AI models at the edge information to distant data centers, edge devices analyze for instant decision-making while leveraging the cloud to and act on data locally. The result is reduced latency, retrain and improve those models with larger datasets. improved responsiveness, and greater efficiency in This interplay creates a continuous feedback loop where scenarios where milliseconds can make a difference. edge devices learn from the cloud, and the cloud refines From predictive maintenance in manufacturing to itself based on edge insights. personalized recommendations in retail, enterprises 26 I September 2025 theciotimes.com

27. Driving Business Agility Challenges to Overcome The convergence of edge and cloud is more than a Despite its promise, the integration of edge and cloud is technical evolution it is a business enabler. Organizations not without hurdles. Enterprises must navigate issues of can respond to dynamic market conditions faster, deliver interoperability, ensuring that devices, platforms, and superior customer experiences, and unlock new revenue networks communicate seamlessly. Bandwidth limitations streams. in certain geographies can also restrict real-time capabilities. Consider logistics companies that monitor shipments in real time. Edge devices track conditions such as Furthermore, organizations must invest in talent that temperature and location, ensuring compliance with safety understands both cloud architecture and edge deployment, standards. At the same time, aggregated cloud data allows a skill set that is still maturing in many markets. companies to optimize supply chain strategies across Overcoming these challenges requires collaboration across regions. The ability to act instantly at the edge while technology providers, regulators, and enterprise leaders. planning strategically in the cloud creates agility that traditional infrastructures cannot match. The Road Ahead Security and Compliance Dimensions The future of enterprise intelligence lies in a continuum, not a binary choice between edge or cloud. As 5G As with any technological shift, security and compliance networks expand and IoT devices proliferate, the demand are central considerations. Edge computing distributes data for distributed intelligence will intensify. Enterprises that processing across multiple points, reducing reliance on a adopt a combined edge-cloud strategy will not only single centralized system. This can enhance resilience but accelerate their digital transformation but also future-proof also introduces complexity in securing multiple endpoints. themselves against emerging disruptions. The cloud remains critical in enforcing governance frameworks, managing encryption, and ensuring In the coming years, we can expect to see more “cloud- regulatory compliance across geographies. By combining native edge solutions” platforms designed to extend cloud cloud-scale security with edge-specific protections, capabilities seamlessly into edge environments. These enterprises can strike a balance between agility and trust. solutions will simplify deployment, enhance security, and Particularly in regulated industries such as finance and deliver a unified management experience. For enterprises, healthcare, this dual model ensures real-time action does this means the ability to innovate faster without being not compromise compliance. constrained by traditional infrastructure models. AI as the Catalyst Conclusion Artificial intelligence is the driving force behind the edge- The convergence of edge and cloud is ushering in a new cloud partnership. AI algorithms deployed at the edge era of real-time intelligence. By bringing computation enable predictive capabilities from anticipating equipment closer to the source while retaining the scale of the cloud, failures to detecting anomalies in financial transactions. enterprises can achieve a powerful balance of speed, Meanwhile, cloud platforms provide the computational agility, and strategic insight. muscle for training these models with vast datasets. In this digital-first economy, success will not be defined This distributed intelligence is reshaping industries. Smart solely by how much data an organization collects, but by cities use edge-enabled cameras to detect traffic patterns in how quickly and intelligently it can act on that data. Edge real time, while cloud platforms analyze broader trends to meets cloud is not just a technology trend it is a improve urban planning. Retailers leverage edge AI to redefinition of how enterprises think, decide, and compete. personalize offers at checkout, while the cloud refines marketing strategies across entire customer segments. theciotimes.com September 2025 I 27