What does it actually take to bridge operational technology and IT inside a running refinery — where the machines that keep crude flowing cannot be touched by a network intrusion? Kushagra Verma, who leads corporate AI transformation at HMEL and has spent 16 years at the company moving from coder to finance to the digital team, brings a practitioner's answer. HMEL runs a 9 MMTPA refinery in Bhatinda, has been on SAP since day one of operations, won the SAP ACE Award for its paperless plant logistics system, and recently launched what the transcript describes as an AI-enabled energy station. This episode covers how the company enforces one-way OT-to-IT data flow, why a network-layer diode technology is being evaluated to air-gap the OT layer entirely, and what it means to build a next-generation refinery command center while SAP remains the single source of truth.

Kushagra walks through HMEL's fully automated truck-loading and product evacuation system — where a vehicle enters, is weighed, loads, triggers a real-time SAP sales invoice, receives statutory transport documents, and exits without a single human touch — and explains why the airplane turnaround analogy fits. He addresses the Clean Core challenge honestly: roughly 10,000 custom objects accumulated over 15 years make a full migration very difficult, so the team is starting with housekeeping, inventorying unused objects, and applying Clean Core only to new standalone implementations. His advice for any mid-sized refiner starting this journey: build a culture that lets people fail fast, expose teams to what peer companies are doing, choose a long-term technology partner whose vision aligns with yours, and treat AI on the IT side as non-negotiable right now.

Episode Chapters
00:00 — Introduction: SAP Autonomous Enterprise Podcast
00:30 — Guest introduction: Kushagra Verma, 16 years at HMEL
01:56 — OT-IT integration: one-way data flow and the diode technology under evaluation
05:14 — Who are the primary internal customers of HMEL's digital transformation
07:53 — AI for sulfur threshold management and HMEL's patent filing
08:23 — Fully automated plant logistics: how the truck-loading system works
10:34 — Partnership architecture: SAP as hub, Amazon and Aveva for specialist functions
11:08 — Jewel AI launch: 30 use cases live in less than 30 days
14:29 — Clean Core: the honest reality of 10,000 custom objects
17:02 — Advice for a mid-sized refiner starting the autonomous enterprise journey
21:54 — One thing a leader must get right: people with the right vision and autonomy to execute
23:13 — Outro

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Across 26 markets in Asia-Pacific, SAP's Customer Engagement and Adoption team is navigating one of the most complex AI transformation landscapes in the world. In this episode, Yee-Ching Wang, SAP Senior Vice President and Head of Customer Engagement and Adoption for Asia-Pacific, joins Julia Kloppenburg and Benedikt Gieger to address the question that every executive in the region is sitting with: if the technology is ready, why isn't adoption keeping up? The answer, Yee-Ching argues, is almost never the technology. It is trust, governance, and the organisation's readiness to change at the pace the business actually requires.

Drawing on customer journeys across regulated industries, large multinationals, and fast-moving mid-market businesses, Yee-Ching walks through how SAP's integrated toolchain and tiered success plans translate vision into measurable operational outcomes. Two case studies anchor the conversation: Fujitsu's global consolidation from more than 4,000 internal systems toward a single-process, AI-enabled operation, and a second example of AI-powered productivity on the manufacturing shop floor. The episode closes with one piece of advice for any leader starting the journey: begin with the business problem, not the technology, identify the handful of processes where AI delivers clear value, prove it, and then scale with confidence.

Episode Chapters
00:00 – Introduction: SAP Autonomous Enterprise Podcast
01:19 – APAC as a transformation landscape: diversity across markets
05:06 – Customer engagement framework: success plans and integrated toolchain
10:01 – Overcoming transformation barriers and the role of AI
14:01 – Customer success stories: Fujitsu and a manufacturing example
26:36 – The first 90 days of AI adoption: people, decisions, blockers
30:23 – Closing advice: start with the business problem
34:36 – Outro

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What does it take for procurement to become genuinely autonomous? In this episode, Fang Chang, General Manager and Chief Product and Technology Officer, describes how AI agents already negotiate bids, suggest awards and navigate catalogs in production, not in demos. He explains where the hard line sits: customers are not ready to let agents make major strategic decisions on an organization's behalf, so humans review and adjust before execution. The conversation covers the data foundation behind reliable agents, why auditability is built into every step, and what a CFO or CPO should get right first when moving from pilot to production this quarter.

The readiness gap varies: some organizations have harmonized their data, others still run a heterogeneous landscape, and closing that gap is a shared responsibility across SAP, the customer and the partner ecosystem. Network effects multiply the value: the larger the supplier network, the more valuable it becomes for every buyer on it. And when trust is the question, the answer is governance plus data. Agents record every step so decisions stay auditable, and they are grounded on the customer's own buying policies, rules of engagement and sustainability goals.

Episode Chapters
00:00 Welcome to the SAP Autonomous Enterprise Podcast
00:30 Guest introduction: autonomous spend and the five domains
02:43 How real is the vision?
06:59 Where is the hard line for agents?
08:34 Data readiness: how big is the gap and who closes it?
10:39 The business network and its tipping point
12:49 Trust, auditability and human intercepts
14:56 The state of agent development
17:00 The honest first step: governance and data

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