In an exclusive conversation with CIO&Leader, Prasanna Ranade, Sr. Director, Enterprise & Govt Sales – India at Nutanix discusses India’s AI-readiness, highlighting the growing talent gap despite aggressive GenAI adoption. He emphasizes the need for urgent upskilling, curriculum reform, and cross-sector collaboration to meet evolving industry demands.
As AI and Generative AI reshape business operations across sectors, the demand for skilled professionals is surging—revealing a widening talent gap in both India and globally. Ranade at Nutanix, shares insights on how organizations are navigating this shift through upskilling, strategic hiring, and infrastructure readiness.
CIO&Leader: What does the global and Indian AI talent gap look like today?
Prasanna Ranade: The AI talent gap is a pressing global concern, and India reflects this trend sharply. While 86% of Indian organizations have a GenAI strategy and 66% are actively implementing it—higher than the global average—only 72% say they possess the necessary skills to support GenAI and cloud-native applications. This leaves a significant 28% struggling with partial readiness. Moreover, 85% of respondents believe their current IT infrastructure requires moderate to major upgrades to fully support modern AI workloads, underscoring the dual challenge of skills and systems.
Globally, organizations are also grappling with a shortage of AI professionals across data science, machine learning engineering, AI operations, and ethics/governance roles. The challenge is compounded by the complexity of building GenAI environments from scratch and integrating them into legacy infrastructures. As the demand for scalable, secure, and production-ready AI systems rises, the skills gap threatens to hinder innovation and delay ROI. Bridging this gap requires urgent action in upskilling, curriculum modernization, and building strategic industry-academic partnerships.
CIO&Leader: What’s driving the sudden surge in demand for AI talent across sectors?
Prasanna Ranade: The rapid surge in AI talent demand is driven by the accelerated enterprise adoption of GenAI across sectors, as businesses seek to leverage the technology for gains in productivity, automation, and innovation. In India, 66% of organizations are actively implementing GenAI strategies—outpacing global benchmarks. Key motivators include a strong belief in GenAI’s ability to drive productivity (cited by 70% of respondents) and innovation (63%). Enterprises are no longer experimenting with AI—they’re operationalizing it at scale, requiring skilled professionals who can build, deploy, and manage these systems.
Another major factor is the growing optimism around GenAI’s return on investment. While 40% of Indian organizations expect limited ROI in the first year, 75% expect substantial returns within 1–3 years. This long-term view is fueling sustained hiring and investment in AI capabilities. Furthermore, evolving business priorities—such as enhancing customer support, improving fraud detection, and automating employee onboarding—are creating new demand vectors. AI talent is now critical not just to IT teams but also to business units, creating a cross-functional surge in recruitment.
CIO&Leader: Which industries are leading the demand for AI-skilled professionals?
Prasanna Ranade: Cybersecurity, customer service, and enterprise IT are leading the demand for AI talent, particularly in India. A remarkable 80% of Indian organizations are deploying GenAI for cybersecurity, fraud detection, and loss prevention—requiring expertise in machine learning, anomaly detection, and risk modeling. Simultaneously, 76% are using GenAI to enhance customer experience via chatbots and automated service systems, driving demand for natural language processing and conversational AI specialists.
Beyond these, IT and cloud-native sectors are seeing major transformations, with GenAI being the most containerized workload. The financial services sector is leveraging AI for predictive analytics, regulatory compliance, and workflow automation. Retail, healthcare, and logistics are emerging adopters, using AI for personalization, diagnostics, and supply chain optimization, respectively. Each of these industries also needs experts in AI security, ethics, and infrastructure scaling—especially as integration challenges and privacy concerns remain top barriers. This cross-sectoral momentum is making AI talent one of the most valuable and sought-after assets in today’s business landscape.
CIO&Leader: How are companies balancing upskilling internal teams vs hiring new AI talent?
Prasanna Ranade: Indian companies are adopting a dual approach—upskilling internal teams while also hiring externally—to meet the rising demand for GenAI expertise. With 66% of organizations actively implementing GenAI strategies, there’s a pressing need for professionals who can manage cloud-native applications and containers. However, only 72% feel confident in their current capabilities, highlighting a clear need to strengthen internal skill sets. As a result, many firms are investing in structured training programs focused on GenAI deployment, containerization, and IT modernization.
At the same time, the complexity of building GenAI environments from scratch—cited by 39% of India respondents as a key challenge—is prompting companies to look outside for specialized talent. Hiring experts accelerates implementation and bridges immediate gaps, especially in security, infrastructure, and governance. The most effective organizations are blending both strategies: reskilling existing employees for long-term capability and onboarding external talent for speed and technical depth, ensuring sustained innovation and reduced dependency on a limited talent pool.
CIO&Leader: How can small and medium businesses adopt AI despite limited talent access?
Prasanna Ranade: Small and medium enterprises (SMEs) in India face significant constraints in accessing GenAI talent but can still adopt AI through strategic choices. Many SMEs are leveraging cloud-based AI tools and managed services that require minimal in-house technical expertise. This “AI-as-a-service” model allows them to deploy applications like chatbots, fraud detection, and productivity automation at lower cost and risk. Focusing on plug-and-play solutions and partnering with vendors can offset the need for large internal teams.
Moreover, SMEs can prioritize productivity-centric use cases where GenAI offers measurable ROI, as seen in India where 70% of respondents cite productivity as the top GenAI driver. They can also tap into government skilling initiatives or collaborate with educational institutions for tailored training. Rather than competing with large enterprises for scarce talent, SMEs should focus on targeted upskilling of select employees and gradual, modular AI integration. This approach enables sustainable transformation within their operational and budgetary constraints.
CIO&Leader: Are current education systems and skilling programs aligned with AI industry needs?
Prasanna Ranade: India’s education and skilling systems are making progress but still lag the fast-evolving needs of the AI industry. While a growing number of institutions offer AI and data science programs, they often focus more on theoretical knowledge than on the hands-on, applied skills needed to scale GenAI environments or integrate AI into production workflows. This gap is evident as only 72% of organizations feel equipped with the skills needed to support cloud-native applications.
Furthermore, 39% of respondents cite the lack of expertise in building GenAI from scratch as a top challenge, underscoring the limitations of current talent pipelines. To stay aligned with industry demands, curricula must evolve rapidly integrating topics such as AI ethics, infrastructure scaling, cybersecurity, and privacy. Skilling programs need to partner closely with industry to offer real-world project exposure. Without this, the workforce will struggle to meet the immediate and future requirements of India’s rapidly digitizing economy.
CIO&Leader: What policies are needed to close the AI skill gap and make India a global hub?
Prasanna Ranade: To close the AI skill gap and establish India as a global hub, policies must modernize education and promote industry-academia collaboration. Curricula in engineering and technical institutions should include hands-on training in GenAI, cloud-native tools, and AI security. Skilling programs must be practical, modular, and co-designed with industry to ensure graduates are job ready. Government collaboration with private players can accelerate this transformation.
Additionally, targeted incentives for companies investing in AI infrastructure and talent development will be crucial. Special focus on Tier 2 and 3 cities through subsidized training, AI labs, and online platforms can broaden access. Support for open innovation ecosystems, regulatory sandboxes, and funding for startups working on AI solutions will further catalyse growth. Combined with a long-term policy outlook and ROI-driven AI investments, these measures can help India bridge its skill gap and emerge as a leading global talent hub for artificial intelligence.
CIO&Leader: What’s your advice for professionals and students looking to build a career in AI? what are some open sources to upskill for young people?
Prasanna Ranade: Start by building strong fundamentals in mathematics, programming (Python is essential), and data science concepts such as statistics, linear algebra, and algorithms. From there, progress to applied areas like Generative AI (GenAI), machine learning, cloud-native tools (like Kubernetes), and deploying models into production. Hands-on learning is key—seek internships, contribute to research, or build personal AI projects to demonstrate practical understanding.
Beyond technical skills, stay informed about AI ethics, data privacy regulations (such as India’s DPDP Act), and the responsible use of large language models. Join developer communities, attend webinars, and participate in AI-focused hackathons or open-source projects to grow your network and stay current. Most importantly, view AI as a cross-disciplinary field—opportunities are growing not only in tech, but also in finance, healthcare, manufacturing, and education. A balanced, future-ready skillset will position you strongly in the rapidly evolving AI landscape.