AIM x Snowflake Innovator Session: The Future of Work 2026

As AI moves from pilots to production, enterprises are discovering that the real challenge is no longer model capability, but how deeply intelligence can be embedded into everyday work. 

The next phase is about re-designing workflows so AI can act, decide, and learn inside the core of the organisation.

In that context, Snowflake and AIM will host a webinar titled The Future of Work 2026: Empowering People with AI for Better Business Results on January 16, from 4:00 PM to 5:00 PM IST.

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The session will examine how organisations are shifting from isolated tools such as chatbots to enterprise-grade AI agents that operate across data platforms, applications, and business processes. 

Rather than assisting with single tasks, these systems are being built to coordinate end-to-end workflows. This includes embedding automation directly into production environments under enterprise governance.

The webinar will feature Monika Kapoor, executive director and head of data and analytics at AstraZeneca, who leads enterprise AI strategy in a highly regulated, science-driven environment.

It will also include Sudhakaran Selvaraj, delivery head for data engineering and data science at Ecolab, bringing a practitioner’s perspective on building and operating large-scale analytics platforms in production.

Joining them is Sridevi Vadapalli, chief data scientist at Daimler Truck Innovation Center India, who brings over two decades of experience scaling data science and AI programmes across manufacturing, BFSI, retail, and automotive, with a focus on production-grade AI, governance, and ethical deployment.

Aimed at technology leaders, data practitioners, and business decision-makers, the session will offer a grounded view on how to move from AI experiments to AI-driven organisations. 

It will conclude with an interactive Q&A on integration challenges, governance trade-offs, and measuring real business value at scale.

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Why You Should Attend

As AI moves into customer support, approvals, reporting, and operational decision-making, leaders must decide which workflows are ready to run without constant human approval. 

The discussion will focus on how teams define “safe autonomy,” where AI can act independently within strict guardrails enforced through governed data platforms.

The conversation will also address where automation breaks first in practice. 

In many deployments, failures stem less from models than from weak data quality, brittle orchestration, and unclear business semantics. 

Speakers will explore how semantic layers reduce errors in AI-generated queries, and how enterprises choose between in-line and asynchronous execution based on latency, cost, and reliability constraints.

Beyond architecture, the webinar will focus on business impact and ROI. 

While early efforts emphasise reducing task time, mature programs are judged by outcomes such as faster cycle times, better decision quality, revenue uplift, and risk reduction. 

The session will examine how companies isolate AI-driven gains from broader digitisation and what realistic payback periods are when workflows are fundamentally redesigned around AI.

As AI agents access multi-domain data and influence decisions, enterprises need auditability without slowing execution and controls that prevent data leakage. The discussion will cover practical approaches to auditing agent behaviour, enforcing access boundaries, and defining where human override must remain mandatory.

Moreover, as AI agents scale, some roles will shrink while others expand, particularly in AI oversight, workflow design, and data stewardship. 

Speakers will address the level of AI literacy non-technical operators will need by 2026, and how organisations can avoid losing institutional knowledge through over-automation.

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