Rise of India’s chief AI officers, firms navigate AI leadership role overlaps
BENGALURU: As the technology landscape in India evolves swiftly, there is a discernible increase in the appointment of chief AI officers (CAIO) to supervise AI initiatives and strategy. The advent of such roles highlights the importance of embedding AI within core operations and an increased focus on AI-driven transformation. Firms are presently navigating the transition towards reducing friction and overlaps among leadership positions within the CDO, CTO, and CIO offices.
Recently, LinkedIn announced the appointment of Deepak Agarwal as their new chief AI officer. In the previous year, Yotta Data Services introduced Anil Pawar as their chief AI officer, entrusting him with the responsibility of directing strategic initiatives in the AI cloud business unit, with a particular focus on leveraging AI, cloud, and platform technologies to deliver significant value to customers. Jindal Steel and Power brought in former BharatPe chief data officer Ritesh Mohan Srivastava as their CAIO. In another recent move, Motilal Oswal Financial Service selected Siddharth Sureka for the CAIO position, while asset management entity Mirae Asset Global Investments appointed Nishant Pradhan as their chief AI officer.
SAP Labs India named Sudhakar Singh as chief AI security officer, with a remit to lead trustworthy AI initiatives for SAP Business AI. Singh’s focus will be on cybersecurity, data privacy, AI regulations, and compliance within the SAP Business AI portfolio. AI unicorn Fractal Analytics appointed Ajoy Singh as its chief AI officer. Singh commented, “While there is a CEO and board-level recognition about the transformative power of AI, it is also true that the field of AI is rapidly changing and there is a talent gap across levels, especially at senior levels. We are seeing more and more companies creating AI leadership roles like CAIO or Head of AI. The role of CAIO is still evolving and there are some overlaps with roles of CDO, CIO, CTO.”
According to Singh, the primary responsibility of the CAIO includes setting the AI roadmap in line with business strategy, developing a pipeline of use cases, defining architectural decisions regarding foundation models, GenAI platforms and tools, and collaborating with the CDO/CIO to create a data foundation for AI/GenAI. CAIOs are also crucial in AI governance and responsible AI. Singh added, “In Fractal’s context, the CAIO is focused on bringing all the elements of the role to create impact in Fractal’s client organisation.”
Phil Fersht, CEO of US-based IT advisory HfS Research, observed that most Indian heritage service providers are treating AI as another technology implementation, rather than a more extensive and meaningful business transformation. He noted, “The core issue is the providers are too grounded in the walls of the CIO’s office and are struggling to develop the capabilities to support C-Suite leaders that are hugely impacted by AI, such as the CFO and CMO. Creating more fancy job titles only works if these executives can broaden their engagement beyond the legacy IT business.”
Jayant Saran, partner at Deloitte India, noted that although chief information officers and chief information security officers are both linked to IT, their main responsibilities vary substantially. “Similarly, regarding AI, the position of an AI officer is likely to become distinct. This mirrors the historical progression where cybersecurity, initially supervised by the chief information officer, evolved into a distinct role with the CISO previously being part of the CIO’s organisational structure. Currently, whilst there is substantial discussion about responsible AI and trustworthy AI frameworks, these responsibilities primarily fall under the Chief AI Officer’s purview, encompassing areas of experimentation, innovation, and ensuring the reliability and responsibility of AI platforms.”
Anurag Malik, partner and leader – people consulting at EY India, said, “My sense is that it’s still fairly early-stage in most organisations. The idea starts with identifying sharp accountability for AI — whether you’re calling it a chief AI officer or placing it under the chief data officer. But there’s another very interesting dimension we’re seeing around AI, especially when it comes to roles. A lot of organisations today are asking: Can I cluster my entire workforce into four AI personas? These personas are based on the role people are expected to play when it comes to AI.”
Malik has classified these roles as AI Ambassadors, who are the most senior executives, often at the CXO level, sponsoring AI initiatives and steering strategic direction.
The second category is AI champions. “Can I identify a few people in every functional area who are champions for AI implementation? For instance, Who’s my AI champion for Finance? Who are the AI champions for supply chain? These aren’t necessarily data scientists, but they understand both AI and the function well enough to identify relevant use cases and drive implementation locally. Think of them as translators between business needs and AI potential,” said Malik.
AI specialists originate from diverse technology backgrounds, necessitating additional training to specialise in artificial intelligence deployment. These individuals undergo focused re-skilling or upskilling programmes to build expertise in AI implementation. General AI practitioners possess fundamental knowledge of AI concepts. Their training enables them to collaborate effectively with AI systems, even if they are not creating AI models themselves. Malik explained, “The goal of defining these personas is twofold: to break AI implementation out of silos, and to create a culture where everyone—from leadership to the shop floor—has a role to play in AI adoption. It also helps with reskilling. Instead of a one-size-fits-all training approach, you tailor capability building based on the persona.”
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SAP Labs India named Sudhakar Singh as chief AI security officer, with a remit to lead trustworthy AI initiatives for SAP Business AI. Singh’s focus will be on cybersecurity, data privacy, AI regulations, and compliance within the SAP Business AI portfolio. AI unicorn Fractal Analytics appointed Ajoy Singh as its chief AI officer. Singh commented, “While there is a CEO and board-level recognition about the transformative power of AI, it is also true that the field of AI is rapidly changing and there is a talent gap across levels, especially at senior levels. We are seeing more and more companies creating AI leadership roles like CAIO or Head of AI. The role of CAIO is still evolving and there are some overlaps with roles of CDO, CIO, CTO.”
According to Singh, the primary responsibility of the CAIO includes setting the AI roadmap in line with business strategy, developing a pipeline of use cases, defining architectural decisions regarding foundation models, GenAI platforms and tools, and collaborating with the CDO/CIO to create a data foundation for AI/GenAI. CAIOs are also crucial in AI governance and responsible AI. Singh added, “In Fractal’s context, the CAIO is focused on bringing all the elements of the role to create impact in Fractal’s client organisation.”
Phil Fersht, CEO of US-based IT advisory HfS Research, observed that most Indian heritage service providers are treating AI as another technology implementation, rather than a more extensive and meaningful business transformation. He noted, “The core issue is the providers are too grounded in the walls of the CIO’s office and are struggling to develop the capabilities to support C-Suite leaders that are hugely impacted by AI, such as the CFO and CMO. Creating more fancy job titles only works if these executives can broaden their engagement beyond the legacy IT business.”
Jayant Saran, partner at Deloitte India, noted that although chief information officers and chief information security officers are both linked to IT, their main responsibilities vary substantially. “Similarly, regarding AI, the position of an AI officer is likely to become distinct. This mirrors the historical progression where cybersecurity, initially supervised by the chief information officer, evolved into a distinct role with the CISO previously being part of the CIO’s organisational structure. Currently, whilst there is substantial discussion about responsible AI and trustworthy AI frameworks, these responsibilities primarily fall under the Chief AI Officer’s purview, encompassing areas of experimentation, innovation, and ensuring the reliability and responsibility of AI platforms.”
Anurag Malik, partner and leader – people consulting at EY India, said, “My sense is that it’s still fairly early-stage in most organisations. The idea starts with identifying sharp accountability for AI — whether you’re calling it a chief AI officer or placing it under the chief data officer. But there’s another very interesting dimension we’re seeing around AI, especially when it comes to roles. A lot of organisations today are asking: Can I cluster my entire workforce into four AI personas? These personas are based on the role people are expected to play when it comes to AI.”
The second category is AI champions. “Can I identify a few people in every functional area who are champions for AI implementation? For instance, Who’s my AI champion for Finance? Who are the AI champions for supply chain? These aren’t necessarily data scientists, but they understand both AI and the function well enough to identify relevant use cases and drive implementation locally. Think of them as translators between business needs and AI potential,” said Malik.
AI specialists originate from diverse technology backgrounds, necessitating additional training to specialise in artificial intelligence deployment. These individuals undergo focused re-skilling or upskilling programmes to build expertise in AI implementation. General AI practitioners possess fundamental knowledge of AI concepts. Their training enables them to collaborate effectively with AI systems, even if they are not creating AI models themselves. Malik explained, “The goal of defining these personas is twofold: to break AI implementation out of silos, and to create a culture where everyone—from leadership to the shop floor—has a role to play in AI adoption. It also helps with reskilling. Instead of a one-size-fits-all training approach, you tailor capability building based on the persona.”
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