Qlik, unveiled research of 4,200 C-Suite executives and AI decision-makers globally. An independent study conducted in November 2024, examined AI adoption challenges and opportunities, including attitudes toward ‘buy-to-build’ deployment strategies. It covered 19 markets and focused on key sectors such as IT, financial services, manufacturing, retail, and healthcare.
In India, 57% of executives view AI as essential for achieving strategic goals and boosting profitability. However, many organisations struggle to transition from planning to execution due to challenges such as skills gaps, governance issues, trust deficits, and resource constraints. Alarmingly, 20% of businesses report having 51 to over 100 AI projects stalled at the planning stage, while 12% have scrapped or halted projects entirely. To address these hurdles, Indian companies are increasingly adopting ready-made AI solutions to expedite implementation and achieve measurable ROI.
Key Barriers Hindering AI Adoption: Skills, Trust, and Governance
The research highlights critical gaps preventing AI adoption in India. It reports that 31% of Indian businesses lack the talent required to develop AI, 18% face difficulties in rolling out developed solutions and 26% of AI decision-makers cited insufficient access to trusted data as additional obstacle. Furthermore, 28% of respondents cited data governance challenges as a major roadblock, while 25% pointed to budget constraints as a critical hurdle.
The study reveals that 41% of senior managers and 38% of less senior employees lack confidence in AI, while 16% of businesses report concerns about customer trust in AI-driven systems. Notably, 57% of respondents indicated that these trust issues have led to reduced AI investments.
‘Ready-Made’ AI Solutions and Training: A Path Forward
To overcome these barriers, 78% of Indian AI leaders see value in leveraging ‘ready-made’ AI solutions as a starting point to accelerate deployment and ROI. Building trust is another critical focus, with organisations looking to promote AI benefits internally and externally.
Upskilling and Government Support for AI Development
Upskilling is also seen as pivotal to addressing the skills gap, while securing government support is also crucial to overcoming barriers to AI adoption in India. 79% of AI decision makers believe India has the potential to lead the world in AI skills in the next five years. To achieve this, 80% believe their industries need to be better at nurturing and upskilling staff for AI, and 78% advocate for increased government funding and AI training programs.
Unlocking AI’s Potential with Agentic AI
“Business leaders know the value of AI, but they face a multitude of barriers that prevent them from moving from proof of concept to deployment of the technology. The first step to creating an AI strategy is to diagnose where the potential blockades are—be it skills, resource or data governance issues. By creating a multifaceted picture of the organisation’s challenges, you start to build trust and win management buy-in to help you succeed,” said James Fisher, Chief Strategy Officer at Qlik.
“India has the talent and ambition to play a key role in the global AI landscape. To make this happen, we need to focus on developing AI skills, building trust in AI, and helping businesses address challenges around governance and resources. AI is already making an impact across industries, but to fully realise its potential, organisations must tackle issues of trust, data governance, and skills shortages. Our findings emphasise the importance of collaboration between businesses, governments, and educational institutions to strengthen AI capabilities and build trust in these technologies,” said Varun Babbar, Managing Director, India at Qlik.
The survey included insights from 250 senior managers and board-level executives in India who are directly involved in overseeing AI projects at large enterprises with 500 to 4,999 employees. These participants represented diverse industries, including IT and telecommunications (16%), financial services (12%), manufacturing (11%), retail (7%), construction and engineering (7%), as well as healthcare and pharmaceuticals (6%), providing a comprehensive view of AI adoption across key sectors.