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Indian companies have now progressed to a stage where they are realizing their digital goals by integrating artificial intelligence into their business operations. These organizations conduct tests across various use cases instead of focusing on just one. By using artificial intelligence, they are optimizing their operations, allowing them to make quicker decisions and explore new business opportunities generated by their AI systems.
Companies must adopt new operational approaches that go beyond traditional software systems to maintain their market presence within the current system of experience-driven competition. AI-based digital transformation enables organizations to replace outdated operational methods with smart operational systems that enhance productivity and deliver additional business intelligence capabilities.
This latest episode of the Analytics Insight podcast features an in-depth discussion between host Priya Dialani and Vikash Sharma, CEO of SparxIT. Vikash shares his insights on enterprise AI, its impact on India’s business ecosystem, and the revolution it has driven in workflows. Below are the excerpts from the conversation:
Adoption of AI in India is special because it enjoys a set of structural advantages that earlier waves of digitization did not. The availability of digital public infrastructure, such as Aadhaar, UPI, and ONDC, results in massive volumes of live data.
Cloud computing technology and the availability of cutting-edge models at affordable prices are democratizing AI experimentation, allowing even small- and medium-sized firms to develop AI tools previously available only to large businesses. Also, India itself has created an ecosystem of AI experts who design and build these solutions.
Earlier, businesses automated their operations using software applications. Automation via software meant transforming business processes into software-enabled ones by digitizing all existing processes. The use of software implied that all activities adhered to predefined regulations, and any deviation from them constituted a system failure.
AI, on the other hand, involves designing self-regulating systems that learn from the environment and make predictions based on past experience.
Deployment of an AI model is just the tip of the iceberg. The reason many businesses fail is that they view AI as a plug-and-play technology that does not require rethinking how work is done. True value can be derived when AI becomes an integral part of the workflow and influences decision-making and outcomes.
It involves pinpointing inefficiencies, optimizing operations, and incorporating AI into business systems. AI will improve people's ability to manage monotonous tasks, freeing them to focus on other aspects of the organization.
In most organizations, the issue is the lack of data systems, which should be prioritized over AI systems. For AI to work effectively, it requires proper structured data. Data engineering ensures that data can be collected, processed, and stored effectively, and data architecture makes sure that data can be used effectively by AI systems.
Without such a foundation, an organization will face two risks: unstable results and erosion of trust in the AI system. In successful companies, it is recognized that the organization's data architecture is a strategic advantage, not just a backend function. It forms a solid foundation for both growth and reliable AI production.
Indian CEOs need to stop seeing AI as a tool for cost reduction and start treating it as an essential investment that will create business growth. Organizations pursuing AI research should focus exclusively on efficiency improvements, as this practice limits their ability to achieve full transformative power. Organizations should use AI to develop new products and services and create innovative business models that will improve customer experiences.
The organization needs leaders who will drive experiments together with cultural values and business operations to achieve success. Organizations must treat data as an essential resource and leverage it to develop AI capabilities for all their teams. Leaders who embrace this mindset will move faster, scale effectively, and position their organizations to compete in an increasingly AI-first global economy.
Listen to the full discussion on the Analytics Insight Podcast.
