Didem Ün Ateş is a globally recognised authority in artificial intelligence and digital transformation. With senior leadership experience at Microsoft, Accenture and Schneider Electric, she has built a career at the forefront of responsible innovation — where emerging technology meets human values and corporate ethics.
As a leading artificial intelligence speaker, Didem is widely respected for her strategic insight into how AI can enhance business performance while protecting trust and transparency. Her work spans data strategy, inclusion, and ethical AI governance, empowering organisations to harness technology for measurable impact.
In this exclusive interview with the Cyber Security Speakers Agency, Didem shares her perspective on the responsible evolution of AI, the crucial role of diversity in shaping innovation, and how businesses can prepare for the next wave of technological disruption.
Q: You've been a long-time advocate for diversity and inclusion in technology. From your experience, how does a diverse workforce directly shape innovation and responsible AI practices within organisations?
Didem Ün Ateş: "In a massive way, it’s truly important. First of all, having a diverse, more inclusive workforce enables better products and better solutions, so it’s good for the business. It’s not just for responsible AI or accessibility.
"The other area is, obviously, it allows for diverse thinking, problem-solving, and creativity across the board. It really strengthens the team as a whole rather than just a couple of points here and there.
"And I think, finally, this diverse thinking – I mean, I would say soft skills are becoming so much more important than ever with the prevalence of technologies like AI and generative AI.
"In other words, team spirit, leadership, collaboration skills – all of these soft skills are scientifically proven to be a bit more common with diverse thinking and inclusive teams. So that’s why I think it has multiple benefits to the business."
Q: As generative AI becomes embedded in daily operations, what are the most common challenges you see businesses facing during adoption – and how can they overcome them?
Didem Ün Ateş: "Yeah, I mean, this is a great question and it’s quite fresh in my mind, as I’ve had multiple clients at Accenture and many large data and AI engagements at Microsoft, and most recently at Schneider Electric as VP of AI Strategy and Innovation.
"I think there are some more technical and more tactical challenges, such as data. This is a big one – a very important one. If the data is in silos, that’s where we need to start first. It does have to be modernised. It has to be on one platform, or as few platforms as possible, so that’s a very important piece.
"But then there are also other, less technical, shall we say more tricky, things like culture. All of these technologies – I feel the easy part is the technology. Scaling the technology, I’m not belittling it; it’s still very significant work. But everything starts with humans and culture, and changing that culture.
"Sometimes, for instance, if people are not willing to share data or collaborate, that will be tough. Then there are other things, like especially we see across generative AI, traceability and reproducibility can be a bit challenging when users are not able to follow the transparency of these models or when they are not very clear.
"Then for business decision-makers like boards, CEOs, and executive committees, something that comes up quite a bit as a challenge is the trade-offs and investment needs. These technologies are so powerful, and the ROIs are really so high, that sometimes it’s very difficult to decide which ones to pick, which ones to invest in, and which ones, unfortunately, to wait on.
"And finally, probably most importantly, lack of skills and lack of talent. I mean, it’s a bit like gold dust right now. When I was recently looking for responsible AI experts, there are so few of them around the world.
"Even if you look globally, there’s just a handful, and the regulations keep changing, the risks keep increasing – not to mention, of course, generally finding AI and generative AI talent. So I think the most important challenge is actually the skills that we need to develop."
Q: Responsible AI has become a boardroom priority. What foundational steps should leaders take to ensure their AI programmes are both ethical and sustainable long-term?
Didem Ün Ateş: "The first one would be executive sponsorship – the fact that senior leaders are absolutely aware of the opportunities and risks related to responsible AI.
"The second thing would be agreeing on the company’s responsible AI principles. Some companies have already established and publicised these, like Microsoft, Accenture, or BCG, etc. It’s okay to simply adapt or adopt these, but a discussion – at least a committee-style discussion – is absolutely important because every company’s strategy and culture are different. Maybe those five or six principles need to differ from what’s in the market or what’s commonplace.
"Then we would need to have a team that is very diverse and inclusive, because different perspectives have to be represented in this virtual team, as we call it. It shouldn’t be too big or too small, but it should be full of responsible AI experts as well as technical and non-technical talents, ethicists, or others – both social sciences and STEM-type profiles.
"The fourth step I would recommend, as in any other business topic or function, is to have a plan to make responsible AI part of the scorecard – the business scorecard. Treat it like a function, like HR or finance, and have that annual plan with milestones, metrics, and key performance indicators, so there is absolutely solid progress across whatever is decided.
"Then, I would say the next step would be processes, tools, impact assessments, and frameworks. There are many of these outside, so again, it would be a matter of scanning and adopting the ones that are relevant to one’s business. It’s very important to have this systematic approach.
"And finally, across the board, we keep training because the regulations are changing, the technology is changing, and employees need awareness – and sometimes more hands-on learning – about how to implement and operationalise responsible AI."
Q: You've led global AI, data, and metaverse initiatives for some of the world's most innovative companies. Which emerging technologies excite you most right now, and why?
Didem Ün Ateş: "I’m excited about almost all cutting-edge, bleeding-edge technology, but I’m sure I’m biased. First of all, generative AI – I do think it’s a game-changer.
"I’m really shocked when some people, quite senior and technology-aware people, even debate, "Oh, is this a hype or something?" I must say I’m quite surprised. Billions would not have been invested, and industries wouldn't have been disrupted or transformed within months, not even a year, if this technology was not powerful and impactful.
"So, generative AI, I think, is just beginning – that’s absolutely very exciting. A subset of generative AI is called generative design, which is in its even more embryonic stage. Think of this like generative AI for designing products – it could be the interior design of a room, designing furniture, or designing a printed circuit board. Again, this is a very exciting technology.
"But then, if we step away from generative AI and its umbrella, I think quantum computing – we shouldn't forget about that. It’s also very powerful. And again, most recently, I'm sure our audiences are aware that biology, healthcare, and life sciences are seeing incredible advances in technology – for instance, synthetic biology or human brain and machine interface. These are very, very exciting spaces right now."
Benzinga Disclaimer: This article is from an unpaid external contributor. It does not represent Benzinga’s reporting and has not been edited for content or accuracy.
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