Didem Ün Ateş
Most large organisations have approved an AI strategy. Far fewer have built the governance and delivery architecture that holds once the technology reaches real operations. In that gap, pilots multiply while boards sign off on decisions they have no reliable way to evaluate.
Didem Ün Ateş, founder of LotusAI, helps boards and investment teams turn an approved AI strategy into governed delivery, drawing on AI leadership roles at Microsoft, Accenture and Schneider Electric and advisory work at the Goldman Sachs Value Accelerator.
Full Profile
Why organisations work with Didem Ün Ateş
- She ran responsible AI inside Microsoft, Accenture and Schneider Electric as the executive accountable for it, which gives her a precise view of where enterprise AI governance breaks down in practice.
- As Senior Operating Advisor and AI/Generative AI Council member at the Goldman Sachs Value Accelerator, she works across more than 300 portfolio companies, which gives boards an investor’s read on where AI strategy creates value and where it creates exposure.
- Her LotusAI engagements come with a tested method. One generative AI opportunity scan covered 15 functions of a Fortune 500 company through 60 co-creation workshops in six weeks, producing 200 prioritised use cases and a sized three-year investment case.
- As a certified algorithm auditor and a World Economic Forum AI Governance Alliance Fellow, she connects a board’s AI decisions to the governance standards being set at regulatory and multilateral level.
- She trained as an engineer at the University of Pennsylvania and took an MBA at Columbia Business School, so she can hold a technical architecture argument and an investment case in the same conversation.
Biography highlights
- Founder and Chief Executive of LotusAI Ltd, and Senior Operating Advisor and AI/Generative AI Council member at the Goldman Sachs Value Accelerator, working with the firm and over 300 portfolio companies
- Former Vice President, AI Strategy & Innovation at Schneider Electric, responsible for the company’s AI and generative AI strategy, innovation roadmap, ecosystem partnerships and responsible AI programme
- Former Head of Applied Strategy, Data & AI in Microsoft’s Customer and Partner Solutions CDO office, and former Managing Director of Data & AI, Europe at Accenture; earlier roles at Capgemini, EY and Motorola
- Board member of the Edge AI Foundation, the Wharton AI Studio, the Columbia Business School Women’s Circle and the Hg Foundation Tech Advisory Board, which also includes technology leaders from ING, Google, McKinsey and Accenture
- Certified algorithm auditor and executive coach, World Economic Forum AI Governance Alliance Fellow, Forbes Technology Council member, University of Pennsylvania and Columbia Business School alumna
- CEO of the Year Awards UK 2025 in AI Advisory, Responsible AI Innovation & Growth in Business Award 2025, New Technology Consultancy of the Year 2025, TechWomen100 Champion and Trailblazer 50 honouree
Biography
Most enterprise AI strategies stall at the same point, somewhere between an approved roadmap and accountable delivery. Didem Ün Ateş has worked both sides of that line inside companies where failure is expensive. At Schneider Electric, as VP of AI Strategy & Innovation, she owned the generative AI strategy, the innovation roadmap, the ecosystem partnerships and the responsible AI programme.
Before that she led Applied Strategy for Data & AI in Microsoft’s Customer and Partner Solutions CDO office. She helped take the company’s Data and AI business from incubation to multibillion-dollar scale between 2016 and 2021, then moved to Accenture as Managing Director of Data & AI for Europe.
LotusAI applies that operational depth to investors and the companies they own. As Senior Operating Advisor and AI/Generative AI Council member at the Goldman Sachs Value Accelerator, she works across more than 300 portfolio companies on AI value creation and governance. One LotusAI engagement scanned 15 functions of a Fortune 500 company through 60 co-creation workshops in six weeks. It produced 200 prioritised generative AI use cases and a sized three-year investment case.
She is a certified algorithm auditor and a World Economic Forum AI Governance Alliance Fellow, and has co-chaired WEF sessions on AI and sustainability. She sits on the Hg Foundation Tech Advisory Board alongside technology leaders from ING, Google, McKinsey and Accenture, and on the boards of the Edge AI Foundation and the Wharton AI Studio. She holds an engineering degree from the University of Pennsylvania and an MBA from Columbia Business School. Recent recognition includes CEO of the Year Awards UK 2025 in AI Advisory and the Responsible AI Innovation & Growth in Business Award 2025.
Key speaking topics
- Enterprise AI strategy and sustainable AI transformation
- Responsible AI and AI governance
- Generative and agentic AI adoption at scale
- AI for private equity, private credit and financial services
- Talent transformation for an AI-driven workforce
- Edge AI
- AI risk and regulatory readiness
Ideal for
- Boards and C-suite teams (CEO, CTO, CDO, CAIO) setting or pressure-testing an enterprise AI strategy
- Chief Data and AI Officers building governance for generative and agentic AI
- Private equity and investment teams assessing AI value creation and risk across a portfolio
- CHROs and talent leaders planning workforce capability for AI-driven roles
Audience outcomes
- Criteria for deciding which AI use cases to fund first, and which to stop
- The specific points where enterprise AI governance usually fails, drawn from Microsoft, Accenture and Schneider Electric
- What investors now expect an AI business case to prove before they back it
- Vocabulary for board-level discussion of AI risk and value creation
- A view of which roles and skills change first as agentic AI reaches the workforce
Talks
Moves the AI and agentic AI conversation from a technical one to a board one, so senior executives can lead decisions they are accountable for but did not engineer.
Key takeaways:
- How to separate genuine AI value levers from hype, and what questions boards should put to their technology leaders
- The talent and cultural conditions that decide whether an AI strategy delivers or stalls in execution
- How to embed AI governance into enterprise strategy at the design stage, ahead of regulatory pressure
For investment firms and their portfolio companies, AI adoption now has to clear two bars at once: accelerating returns, and surviving the governance and reputational scrutiny that LPs and regulators have started applying.
Key takeaways:
- How to assess AI readiness and value potential across a portfolio of companies at very different maturity levels
- The governance and compliance considerations that separate responsible AI adoption from regulatory exposure in financial services
- How to connect AI strategy to value creation metrics that hold up under investor scrutiny
How organisations can design and deploy responsible and inclusive AI that generates commercial value alongside measurable societal outcomes.
Key takeaways:
- How to integrate AI and agentic AI into operations without losing control of the governance and compliance posture
- A model for taking responsible AI from policy statement to operating practice across different organisational contexts
- How inclusive AI design connects to workforce evolution, investment strategy and long-term portfolio value