CORE Media, in association with Tata Communications, convened an exclusive closed-door session in Kolkata on 'Enterprise AI Reimagined: From Pilots to Performance.'
The session featured Anoop Mathur, Founder, CORE Media, in conversation with Manaswi Netala, Associate Director – Market Innovation, Tata Communications. It brought together a select group of enterprise technology leaders to examine how organizations can move beyond isolated AI experiments to enterprise-scale execution.
Enterprises have moved well beyond asking whether AI works. The more pressing question today is whether AI can consistently deliver measurable business outcomes at scale. This formed the cornerstone of the discussion, where technology leaders explored why AI adoption must now transition from experimentation to enterprise-wide execution.
The discussion acknowledged that while organizations have invested significantly in AI pilots, copilots and automation initiatives, many continue to struggle with translating isolated successes into sustained business impact. Participants agreed that the challenge is no longer building AI models—it is integrating AI into the fabric of enterprise operations.
One of the central themes was the "last mile" problem in enterprise AI. While AI excels at generating insights and recommendations, enterprises often face difficulties in converting those insights into automated, business-critical actions. Bridging the gap between intelligence and execution emerged as one of the defining priorities for the next phase of enterprise transformation.
The conversation also highlighted the growing importance of orchestration. As organizations adopt multiple AI models, cloud platforms and enterprise applications, fragmented deployments can create operational complexity and inconsistent outcomes. Leaders emphasized that the future lies in orchestrating AI across data, applications, workflows and infrastructure rather than relying on disconnected point solutions.
Participants noted that AI performance is directly linked to the quality, accessibility and governance of enterprise data. Fragmented data estates, regulatory requirements, security concerns and data sovereignty continue to limit organizations from scaling AI with confidence. Building trusted data foundations was seen as a prerequisite for realizing enterprise-wide AI value.
The roundtable also explored whether enterprises require an AI Operating System instead of deploying multiple standalone AI tools. As AI becomes embedded across every business function, leaders discussed the need for a unified platform that can govern AI workloads, orchestrate workflows, manage models and provide visibility across the enterprise while integrating seamlessly with existing technology investments.
Beyond technology, the discussion shifted to business outcomes. Participants agreed that AI success should no longer be measured by the number of pilots launched, but by tangible improvements in operational efficiency, customer experience, service delivery and business agility. Organizations are increasingly seeking AI that can autonomously execute tasks, resolve issues, optimize operations and accelerate decision-making while maintaining governance and human oversight.
Real-world examples demonstrated how AI is beginning to transform customer support, intelligent network operations and digital experiences. However, participants also acknowledged persistent challenges, including integrating AI with legacy environments, ensuring responsible governance, overcoming organizational silos and demonstrating clear return on investment.
The consensus was clear: the next era of enterprise AI will not be defined by more powerful models alone, but by an organization's ability to connect data, infrastructure, applications and governance into a cohesive AI ecosystem. Enterprises that successfully move from isolated pilots to orchestrated, enterprise-wide execution will be best positioned to unlock sustainable business value in the years ahead.
