AI Adoption in India: A Gradual Journey Towards Transformation
Artificial Intelligence (AI) adoption in India is gathering momentum, albeit at a measured pace. A new report from Lenovo, titled “CIO Playbook 2025: It’s Time for AI-nomics,” sheds light on the current landscape and the disparities in organizational maturity and readiness across the country. This report is founded on an extensive global IDC study that surveyed over 2,900 respondents, including more than 900 from 12 Asia Pacific (AP) markets. The findings delineate the position of Indian enterprises on the AI advancement curve, the factors driving change, and the crucial gaps that remain.
One of the most striking revelations from the study is the notable shift towards next-generation tools, particularly Generative AI, which is expected to account for 43% of India’s total AI expenditure by 2025. This statistic underscores a significant transformation in enterprise priorities as they allocate resources more strategically in line with AI advancements.
Spending Increases Amidst ROI Barriers
India is projected to escalate its AI investments roughly 2.7 times by next year, aligning closely with the Asia Pacific region’s average growth of 3.3 times. However, a closer inspection reveals that many organizations are still grappling with the foundational stages of their AI integration. Approximately 49% of Indian enterprises are either in the process of evaluating AI technologies or planning to introduce them within the next 12 months.
The primary hurdle stifling this growth is the quest for a meaningful Return on Investment (ROI). Unlike conventional technology deployments, which may offer immediate returns, AI necessitates a sustained strategy that balances experimental use cases with scalable, quantifiable results. Despite an anticipated 3.6 times return on AI investments, organizations face mounting pressure to demonstrably showcase the value of their investments while navigating significant challenges such as data quality issues, talent shortages, and infrastructural constraints.
Governance, Risk, and Compliance in Focus
Another critical insight from the Lenovo report is the ascent of Governance, Risk, and Compliance (GRC) as a leading priority among CIOs across the Asia Pacific. Impressively, GRC has leaped 12 positions to become the number one concern for IT leadership, reflecting increasing apprehensions regarding the ethical and responsible use of AI technologies.
However, the progress of GRC implementation in India has lagged considerably. Only 19% of CIOs report having fully enacted AI governance policies, a figure alarmingly lower than what is necessary. This inadequacy is particularly concerning given the mounting regulatory scrutiny, data privacy issues, and concerns regarding AI bias that permeate various sectors.
In the AI context, GRC frameworks encompass vital aspects such as explainability, model transparency, and human oversight—capabilities that remain underdeveloped in many Indian firms.
Regional Variances in AI Application
The practical deployment of AI technology is diversifying across industries, with notable regional distinctions. While IT operations stand out as the leading AI use case in the larger Asia Pacific region, Indian businesses have gravitated towards leveraging AI predominantly in sales, followed by marketing and software development.
This preference implies a customer-oriented approach within Indian enterprises, where AI is being harnessed to enhance personalization, bolster campaign performance, and streamline product delivery. Given the burgeoning potential for Generative AI applications in these areas, there is an increasing focus on capabilities such as content generation, predictive analytics, and modeling customer behaviors.
Preference for Hybrid and On-Premise Architectures
Despite the swift transition towards cloud technologies, a significant preference for on-premise and hybrid infrastructures continues to dominate the AI workload landscape in the Asia Pacific. Approximately 65% of organizations in the region, including 63% in India, prioritize these models over public cloud solutions. The rationale behind this inclination is clear—factors such as low latency, enhanced data control, and the need for regulatory compliance are driving these preferences, particularly in the finance, healthcare, and critical infrastructure sectors.
The Dawn of AI-Powered Productivity Solutions
While AI is permeating backend systems and enterprise platforms, a parallel revolution is unfolding on the frontend with the emergence of AI-powered PCs that harness intelligent features to enhance productivity. The report indicates that 43% of organizations in Asia Pacific are already witnessing productivity benefits from such devices, with over half of surveyed businesses in India planning to adopt these technologies in the near future. Although deployment remains in its infancy, expectations are rising, especially within hybrid work contexts where intelligent devices facilitate task automation and collaborative efforts.
Addressing the Skills Gap: The Rise of Partnerships
A recurring theme in this study is the noticeable deficiency in internal AI capabilities. To bridge this gap, 29% of Indian CIOs report that they are currently utilizing professional AI services, with an additional 54% planning to do so. These strategic partnerships will be essential for navigating the complexities of AI solution design and implementation. Such collaborations allow internal teams to focus on strategic deployments while external experts manage the intricate aspects of infrastructure, modeling, and deployment.
The study indicates a gradual shift towards a more outcome-focused approach in AI adoption, where organizations prioritize measurable business impacts over experimental initiatives. This will encompass targeted pilot programs, methods for tracking ROI, and expedited scaling through well-established frameworks.
Generative AI: Paving the Way for Future Investments
Generative AI continues to drive extensive discussions in the enterprise space, significantly influencing strategies. Investment in Generative AI is on the rise, even as funding for traditional AI tools remains steady. A hybrid approach that melds Generative AI with conventional models is also becoming increasingly popular.
In both India and the broader Asia Pacific region, Generative AI is being utilized for various applications, including code generation, DevOps optimization, content creation for marketing, and enhancing knowledge management in customer support and training. These use cases often yield immediate ROI by leveraging extensive datasets and existing workflow structures, yet as the technology matures, enterprises are likely to explore more intricate applications.
Building a Robust AI Foundation
The report concludes with a definitive message: "go slow to go fast." For organizations to realize the full potential of AI, investments in foundational aspects are critical. These include enhancing data management capabilities, building scalable infrastructures, implementing robust upskilling programs in data science and AI, and establishing comprehensive governance frameworks.
Approximately 34% of organizations in the Asia Pacific are set to improve their data management practices in the coming year, highlighting a growing recognition of this necessity. The lessons learned from rushed Generative AI implementations, where inferior data quality often curtailed success, emphasize the importance of sound data governance and science.
The Path Forward: Towards Smarter, Sustainable AI
India’s journey with AI is undoubtedly accelerating, yet the message conveyed by Lenovo’s CIO Playbook is clear: strategic discipline is paramount. While Generative AI continues to stir excitement, the genuine value will derive from responsible innovation, deliberate scaling, and constructing a forward-thinking AI foundation that aligns governance with growth.
As new regulations, evolving technologies, and rising customer expectations emerge, Indian enterprises find themselves on the brink of a pivotal moment. The decisions made over the next year will profoundly impact not only how much is invested in AI but also how effectively it is utilized, paving the way for a future where intelligent technologies lead to smarter and more sustainable solutions.