Autonomous Enterprise

SAP SE

Autonomous Enterprise is SAP’s podcast on how Business AI is reshaping enterprise operations. Through direct conversations with leaders, customers, and experts, the series explores how companies turn data into decisions, automation, and measurable business outcomes.

  1. 6h ago

    Autonomous Enterprise in Latin America | Adriana Aroulho, SAP

    Why 80% accuracy is not enough in enterprise AI. SAP Latin America President Adriana Aroulho on complexity, talent, and partners. Latin America is one of the fastest-growing technology markets in the world, and the autonomous enterprise is not a distant vision for the region. It is the next stage of business transformation. But making AI work at enterprise scale requires more than deploying a capable model. It requires business context: the actual processes, policies, rules, and operational reality of each company. In this episode, Adriana Aroulho, President of SAP for Latin America and the Caribbean, joins hosts Julia Kloppenburg and Benedikt Gieger to explain why the region's regulatory complexity, from Brazil's tax reform to cross-border trade agreements, makes it one of the world's most compelling proving grounds for business AI and intelligent agents. Adriana maps the three-step adoption path she sees across the region — modernising the digital core, establishing trusted data and governance, then scaling to cross-functional AI — and makes the case that autonomous enterprise is not a large-enterprise-only play. She also addresses the talent gap, the role of regional partners in co-creating industry-specific agents, and the question every leader is asking: do you need to complete every maturity step before you can move? Her answer is clear: the foundations cannot be skipped, especially the data piece. But companies do not have to wait until everything is perfect to start generating value. Episode Chapters00:00 – Introduction: SAP Autonomous Enterprise Podcast00:51 – Guest welcome: Adriana Aroulho, SAP Latin America02:02 – Why now: converging trends driving LatAm transformation05:02 – Where AI agents deliver the most immediate value06:33 – Cloud adoption paths: from installed base to business AI09:20 – Is autonomous enterprise universal across company sizes?12:14 – The talent and skills gap: a global, not just regional, challenge15:43 – Partner ecosystem: local complexity and co-creating agents19:07 – Leapfrog versus sequential maturity: can steps be skipped?20:46 – One thing every leader must get right: business context24:20 – Closing and thanks Listen and SubscribeSubscribe on SpotifyListen on your preferred platform

    Autonomous Enterprise in Latin America | Adriana Aroulho, SAP

  2. Oct 12

    What does it take to bridge OT and IT in a live refinery? HMEL's Kushagra Verma explains.

    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 Chapters00:00 — Introduction: SAP Autonomous Enterprise Podcast00:30 — Guest introduction: Kushagra Verma, 16 years at HMEL01:56 — OT-IT integration: one-way data flow and the diode technology under evaluation05:14 — Who are the primary internal customers of HMEL's digital transformation07:53 — AI for sulfur threshold management and HMEL's patent filing08:23 — Fully automated plant logistics: how the truck-loading system works10:34 — Partnership architecture: SAP as hub, Amazon and Aveva for specialist functions11:08 — Jewel AI launch: 30 use cases live in less than 30 days14:29 — Clean Core: the honest reality of 10,000 custom objects17:02 — Advice for a mid-sized refiner starting the autonomous enterprise journey21:54 — One thing a leader must get right: people with the right vision and autonomy to execute23:13 — Outro Listen and SubscribeSubscribe on SpotifyListen on your preferred platform

    What does it take to bridge OT and IT in a live refinery? HMEL's Kushagra Verma explains.

  3. Oct 5

    APAC AI adoption isn't one journey. Yee-Ching Wang on trust, governance, and what it takes to reach the autonomous enterprise.

    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 Chapters00:00 – Introduction: SAP Autonomous Enterprise Podcast01:19 – APAC as a transformation landscape: diversity across markets05:06 – Customer engagement framework: success plans and integrated toolchain10:01 – Overcoming transformation barriers and the role of AI14:01 – Customer success stories: Fujitsu and a manufacturing example26:36 – The first 90 days of AI adoption: people, decisions, blockers30:23 – Closing advice: start with the business problem34:36 – Outro Listen and SubscribeSubscribe on SpotifyListen on your preferred platform

    APAC AI adoption isn't one journey. Yee-Ching Wang on trust, governance, and what it takes to reach the autonomous enterprise.

  4. Sep 28

    AI agents already negotiate bids, suggest awards and buy in production. The hard line: humans still hold every strategic decision.

    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 Chapters00:00 Welcome to the SAP Autonomous Enterprise Podcast00:30 Guest introduction: autonomous spend and the five domains02:43 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 point12:49 Trust, auditability and human intercepts14:56 The state of agent development17:00 The honest first step: governance and dataListen and SubscribeSubscribe on SpotifyListen on your preferred platform

    AI agents already negotiate bids, suggest awards and buy in production. The hard line: humans still hold every strategic decision.

  5. Sep 21

    AI Partner Strategy: From Implementation to Outcomes | Mark Wheeler, NTT DATA

    Is your SAP partner truly ready to deliver the autonomous enterprise, or are they repackaging traditional implementation work with an AI label? Mark Wheeler, Global Head of Product Engineering and AI Customer Success Delivery Operations at NTT DATA Business Solutions, gives a candid answer. He describes a three-strand delivery framework, called Cloud ERP Elevated, that separates partners who are genuinely industrialising AI delivery from those who are not. And he names the three reasons AI transformation fails: misaligned business economics, underestimated technical feasibility, and users who were never brought on the journey. Wheeler shares concrete outcomes from NTT DATA customer engagements: 90% touchless supply confirmations for a manufacturing customer and 98% straight-through processing for unstructured sales orders at a UK chemicals company. He explains why human-centered design still matters even as AI capability accelerates, and closes with the single question he asks every CIO before any tactical decision: what is your platform strategy? The answer, he argues, shapes everything that follows for an autonomous enterprise. Episode Chapters00:00 – Introduction: SAP Autonomous Enterprise Podcast00:54 – Guest introduction: Mark Wheeler, NTT DATA Business Solutions01:33 – Is the partner ecosystem ready to deliver the autonomous enterprise?03:10 – Cloud ERP Elevated: three strands of AI delivery (ready, template, custom AI)06:17 – Customer outcomes: Leinmuller and Synthema use cases with concrete results09:56 – Why AI transformations fail: economics, feasibility, and user adoption14:24 – How to identify where to start and which use cases are ready to scale16:29 – Partner business model transformation: from billable days to outcome delivery19:51 – Human-centered design in an AI-first world: the SAP App House alliance22:49 – Final question: the one thing a leader must get right for autonomous enterprise25:02 – Outro LinksSubscribe on SpotifyListen on your preferred platform

    AI Partner Strategy: From Implementation to Outcomes | Mark Wheeler, NTT DATA

  6. Sep 14

    AI Without Business Context Is Just Noise | Alexander Kläger, SAP

    Why do most enterprise AI initiatives stay stuck? SAP's MEE president on closing the knowing-doing gap. Most companies say they are already doing AI. But when you look closer, what you find is a patchwork: several tools running in parallel, rising technical complexity, and integration dead ends that stall real progress. Alexander Kläger, President of Middle and Eastern Europe at SAP SE, has sat across from hundreds of senior executives this year. His verdict is unambiguous: decision-makers are past the hype. They want outcomes, and they want them delivered on the right foundation, not bolted on top of one they are already questioning. In this episode, Alexander explains why the fear he hears most behind closed doors is not "will AI replace my people?" but rather "are we making the right bet?" He describes how the autonomous enterprise closes the gap between knowing and doing, why business context is the actual differentiator between generic AI and AI that acts inside real processes, and why the next 12 to 18 months represent a learning window that cannot be bought back later. He also shares what finally unlocks Mittelstand CEOs and why MEE has every reason to lead this transformation, not simply follow it. Episode Chapters00:00 – Introduction: SAP Autonomous Enterprise Podcast00:29 – Meet Alexander Kläger: President, SAP Middle and Eastern Europe00:56 – AI patchwork: what executives are actually doing versus what they say02:08 – Beyond the hype: decision-makers want results, not participation03:34 – Behind closed doors: the fear executives will not say out loud04:49 – The autonomous enterprise in the boardroom: closing the knowing-doing gap06:18 – The 12-to-18-month window: what you cannot purchase back07:34 – What unlocks a Mittelstand CEO09:19 – Why SAP's business context argument lands with executives who have tried generic AI10:39 – Five years from now: winners will rethink, not just retrofit11:52 – Outro LinksListen on SpotifySubscribe via PodLink

    AI Without Business Context Is Just Noise | Alexander Kläger, SAP

  7. Sep 7

    AI, Sustainability and the Autonomous Enterprise | Sophia Mendelsohn, SAP SE

    Does AI make us more sustainable, or does it simply accelerate the status quo? In Episode 15, Sophia Mendelsohn, Chief Sustainability and Commercial Officer at SAP SE, brings two decades of sustainability leadership to bear on the question every supply chain executive is quietly asking. Her answer is direct: AI is a mirror. It will only reflect the prompts and training data we give it. If we change the input, we change the outcome. This conversation covers what it actually takes to move from aspiration to autonomous action. Sophia walks through three concrete stages of what AI-powered sustainability software can do: help leaders see what was previously invisible, fill in data gaps transparently, and automate decisions that today require four or five people on a call. She argues that supply chain leaders should stop thinking about sustainability as a compliance burden and start thinking about it as a financial equation, with measurable ROI on every environmental input. She also draws a clear boundary around what AI cannot do: negotiate with suppliers, manage team dynamics, or replace the human work of driving systemic change. Episode Chapters00:00 – Introduction: SAP Autonomous Enterprise Podcast00:30 – Welcome and guest introduction01:05 – AI as a mirror: does it make us more sustainable?03:16 – The elephant in the room: AI's resource footprint05:14 – SAP sustainability portfolio and the three-stage AI framework09:43 – SAP as its own first customer: lessons learned11:31 – Scope 3 emissions: what AI can and cannot do14:44 – From compliance burden to competitive advantage17:51 – Two decades on the front line: one old prompt to delete20:54 – Architecting sustainability into autonomous agents23:34 – Greenwashing, trust, and the coming wave of consumer power26:20 – Closing advice for leaders: start with your data27:21 – Individual call to action: update the prompt28:07 – Outro LinksListen on SpotifySubscribe via PodLink

    AI, Sustainability and the Autonomous Enterprise | Sophia Mendelsohn, SAP SE

  8. Aug 31

    Enterprise AI Competitive Edge: Growth Mindset | Eric van Rossum, SAP

    Enterprise AI competitive advantage isn't about model access. Eric van Rossum (SAP) explains why growth mindset is what wins. When every company can access the same foundational AI models, where does competitive advantage actually come from? Eric van Rossum, CMO Autonomous Suite, Product Marketing and Learning at SAP, has a clear answer: the organisations that win will be those grounded in deep process knowledge, proprietary business data, and enterprise-grade governance. But his more provocative argument is that the technology itself is not the constraint. The bottleneck is human and organisational. In a market where AI adoption is compressing from years to weeks and months, the one skill that separates those who adapt from those who don't is not a technical skill. It is growth mindset: the willingness to stay permanently on the learning curve, to be comfortable being consciously incompetent, and to keep adapting faster than the tools do. Eric walks through SAP's three-part competitive differentiation - process domain knowledge, proprietary enterprise data, and governance - and explains why these create a durable layer above commoditised frontier models. He introduces the competency pyramid as a practical framework for navigating the AI adoption curve and argues that every AI project should start with the business outcome and work backwards, not the other way around. He shares how his teams moved from distributed experimentation into governance-led standardisation, and estimates that 30 to 40 percent of a product marketer's execution work is already shifting to AI, freeing capacity for strategic positioning. When every company can access the same foundational AI models, where does competitive advantage actually come from? Eric van Rossum, CMO Autonomous Suite at SAP, explains why the bottleneck in enterprise AI is human and organizational, not technical, and why growth mindset is the defining leadership competency of this era. Episode Timestamps and Chapters: 00:00 - Introduction and guest welcome00:48 - AI and the future of work: will AI replace jobs?03:28 - Growth mindset: the defining enterprise AI skill07:12 - From executor to orchestrator: the shift already happening08:24 - Organisational bottleneck: why the hard part is not technical11:38 - SAP's three-part competitive edge: process knowledge, data, and governance18:19 - Closing the POC-to-production gap: start with the business outcome21:45 - How Eric's teams use AI daily: from distributed experimentation to governance28:08 - One thing every leader must get right to reach the autonomous enterprise30:51 - Key takeaway and outro Links and Resources: Listen on SpotifySubscribe via PodLink

    Enterprise AI Competitive Edge: Growth Mindset | Eric van Rossum, SAP
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Autonomous Enterprise is SAP’s podcast on how Business AI is reshaping enterprise operations. Through direct conversations with leaders, customers, and experts, the series explores how companies turn data into decisions, automation, and measurable business outcomes.

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