Excellence Foresight with Nancy Nouaimeh

Innovating the Future – AI and Standards with Dr. Sid Ahmed Benraouane

• Nancy Nouaimeh • Season 3 • Episode 3

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Dive into the transformative world of artificial intelligence (AI) through an engaging and insightful discussion with Dr. Sid Ahmed Benraouane. As we immerse ourselves in this episode, you'll discover the true potential of AI—not merely as a tool of automation but as a catalyst for enhancing human capabilities within organizations. From improved decision-making to fostering creativity, AI is revolutionizing the way we approach work and leadership.

 Dr. Sid Ahmed Benraouane is a globally recognized expert in digital transformation, innovation management, and technology policy. With over two decades of experience, he has played a pivotal role in shaping international standards for innovation and AI. He leads the United States ISO Working Group on the Innovation Management System Standard and serves on the ISO/SC 42 Joint Committee, focusing on AI trustworthiness. Dr. Benraouane advises government leaders across the MENA region on innovation strategies and digital transformation and is a sought-after speaker at prestigious global forums such as the World Government Summit. He holds a Ph.D. from the University of Minnesota, is a Certified Chief Innovation Officer, and serves as a Board Member of the Global Innovation Management Institute.

He shares invaluable insights on the establishment of AI Centers of Excellence, designed to drive innovation while ensuring compliance with new governance standards. With a focus on responsible AI adoption, we discuss the critical need for organizations to build a framework that prioritizes ethical practices. The importance of training and capacity building for employees who engage with AI technologies is emphasized, as organizations strive to create a workforce that leverages AI effectively.

Furthermore, we explore the balancing act leaders face in maintaining operational excellence while embracing the rapid changes brought about by AI. Learn about the concept of ambidextrousness and how it can help organizations sustain progress in both innovation and traditional excellence.

Don’t miss your chance to gain knowledge from this fascinating episode and engage with the future of work. Subscribe, share, and leave a review to join us on this enlightening journey!

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Nancy Nouaimeh:

Welcome to the second episode of season three of the Excellence Foresight Podcast. As an organizational excellence and culture transformation expert, I'm always exploring the forces shaping the future of work, leadership and innovation, and today we're diving into one of the most transformative forces of our time artificial intelligence. Ai is no longer just a tool. It's a game changer, accelerating excellence across industries. It has been revolutionizing creativity, scientific discovery and decision making. Organizations are establishing what we call AI centers of excellence to drive innovation, while cutting edge algorithms are reshaping everything from weather forecasting to nuclear safety. Even the creative world has been redefined, with AI empowering brands to compete on a global scale like never before. But here's a big question how do we harness AI's immense power while ensuring it amplifies human potential, rather than replacing it? To explore this, I'm thrilled to welcome a very special guest here today, someone at the forefront of AI's transformation Dr Sid Ahmed Bin Rawan. He's here with us today to share his insights and expertise. So, dr Sid, welcome to Excellence Foresight.

Sid Ahmed Benraouane:

Thank you so much, Nancy, for the invitation, and I'm so happy to be with you.

Nancy Nouaimeh:

Thank you for accepting my invitation to be on the podcast, and today is going to be about innovating the future, ai and standards, so let's start by giving our audience a glimpse into your journey.

Sid Ahmed Benraouane:

Well, let me first of all start by saying that my journey into innovation AI has been quite long. I believe I started in late 2005 when I started teaching a course at the University of Minnesota Carson School of Management on innovation. At that time, I was asked by the department to lead an MBA course that focused on innovation, and part of the class was to take students to different parts of the world to explore what are these countries and what are those companies in these countries doing. So we started looking first of all closer to home. When I was in the US, closer to home was obviously the Silicon Valley, so we would spend about two weeks in the Silicon Valley in the Bay Area, looking at some of the best practices of innovation and what makes innovation for those companies. And then traveling overseas, coming to the region, to the UAE, and to Dubai, abu Dhabi and Oman to start to look at what these emerging economies are doing to help them innovate, to help them set or create the ecosystem for innovation.

Sid Ahmed Benraouane:

And then, more recently I think I believe in 2015, I was invited to join the ISO Standard Committee, which is the committee that creates a standard for innovation and standard for almost everything, but specifically I was focusing on innovation.

Sid Ahmed Benraouane:

So I started working on with the committee that produced ISO 56002, which is innovation management, and then I moved to other committees and I was focused at with the committee that is working on innovation management and IP innovation assessment, and then all the way to the committee that works on AI and standardization. I think the defining moment for me was obviously the breakthrough that AI started to achieve, starting in 2015 and 2016, with all the work that Google has been doing and other leading company was doing in the Silicon Valley. So I knew that artificial intelligence in particular, digital transformation in general policy on technology, are important change factors that companies and organizations have to start thinking about, and that's how I started working on the standardization of AI. I wrote a book with late James Harrington on ISO 56002, which was the innovation management standard, and I just published my third book on the AI standard 42001, which has been just published, I believe about a year ago, to help the readers again understand and make sense of those standards.

Nancy Nouaimeh:

Dr Sedda, amazing journey and I think experience of writing books is very important, I think, to develop your own expertise but also to share that expertise with others. And your work with ISO standards and I think feeds into what we really need now is in standardizing the practices around AI, and I would like maybe to jump a little bit and talk to AI and ISO standards. So you've worked on the 42001. And what are the key objectives of that standard and how does it help organization to work with artificial intelligence and what are the things that we need to pay attention to when we work with artificial intelligence?

Sid Ahmed Benraouane:

Yes, very good question, but let me actually take one step back just to give you the background of this standard. First of all, iso is working on many, many standards that relate to artificial intelligence. I think currently we are working on more than 30 standards. Some of them have been already published, some of them are under development and some of them are on our roadmap for developing in the next couple of years. I am a delegate member. I am part of the working group that focuses on foundational standard, group number one within ISO, and this group focuses specifically on the foundational standard that would give companies, business leaders and managers the critical component that would allow them to create an ecosystem for artificial intelligence. Let me just give you a couple of standard names before I get to 42001. For instance, we have been working on a standard called 420028, which focuses on the trustworthiness of artificial intelligence, which simply means how do you create AI systems that produces product and services that you can trust and with which you can work and you can believe in? There is another standard, the 24-0-2-7, which focuses mainly on bias in AI system. How do you create AI system that are free of biases and a system that helps you in the decision making, on creating decisions without any issues of misinformation, bias or otherwise. There's another standard that is called also ISO 38507. This is called the governance of IT and it focuses specifically on artificial intelligence, which is how you can create again an AI system and how you can create a governance system that looks at the implementation and the development of AI applications. Two other standards are important before I get to the main one 23894, which focuses on risk management, and 24368, which focuses on ethical and social concerns and the impact of these systems on the organization.

Sid Ahmed Benraouane:

Now back to your question. 42001 is a critical standard, it's a game-changer standard. It's the only standard that we have so far in the world. That is a required standard and it's the only standard against which you can be certified. Of course, we have the EU AI Act, which is again a law of the land, and it requires many, many things. Among them is the implementation of conformity assessment for different AI systems. And then we have also different AI systems, and then we have also in the US, we have the NIST, the N-I-S-T agency, which is the National Institute for Science and Technology, and they have also produced their own standard, and there is actually one main standard, which is called the Risk Management Framework 1.0. Now, this standard is not a required standard, so this is mostly guidelines and most of companies, most of federal agencies, state agencies, local agencies in the US they tend to take it and to use it At the global level.

Sid Ahmed Benraouane:

The only standard that we have is the 42001. And it is critical because it does two things. Number one it defines what we mean by governance. Many, many managers I meet they always ask the same questions what do we mean by AI governance? How do I create an AI system that is in compliance with different rules and procedures of governance and what are the things that I need to do within my own organizations to be able to be certified against this standard? And that's the second thing that the standard does. If you run this, if you implement this standard and if you bring someone who can certify you against this standard, that means your organization is using AI system, is good, is within the ethical framework that we are hoping for and is in compliant with the requirement of AI, of 42001, responsible use of AI.

Sid Ahmed Benraouane:

Now, nancy, when we talk about governance, I want to just end with this note Governance is a very complex system. We talk usually about internal complexities, and when we talk about internal complexity, we're talking about use cases of AI, new AI models, used AI that are coming from different vendors and from different procurement processes. And then you've got also the external complexities, which has to do again with the customer demand, the rising in regulations and we'll talk about that in a few moments that the EU Act has already started implementing some of its most critical clauses and laws, specifically with respect to training, with respect to penalties, in the next month. And then, of course, you have also this notion of change in the concept of risk. There's always a new research that comes up and adds a new definition or a new twist on the concept of risk management. So this is why it's important to have a framework that organizes your work, that organizes your effort to help you streamline all the things that you do within your company so you are in alignment with laws and regulations and international standards.

Nancy Nouaimeh:

This is excellent, dr Said. I think there's a lot. I mean, you rightly said it's an ecosystem and we need to look at the internal, external factors and, for the people who knows ISO standard, I think the same spirit is there in the ISO standard related to the artificial intelligence that are important for organizations to follow. I think there's a lot of when organizations want really to go that route, they need to really dig deeper into what are the risks, the consequences and be able to manage that in a responsible way. I think that's really that's what stands out from what you explained to us already, so thank you for that.

Nancy Nouaimeh:

I would like now to maybe shift a little bit and talk. My expertise is excellence models and I always like to see how excellence models and the advancement of technology and the other things that we see on a daily basis, how do they integrate well and how do excellence models and the national quality awards that we see in the region you mentioned you work. I mean you're working in Dubai now. You worked in Oman and the GCC region is booming. You worked in Oman and the GCC region is booming, so how can we integrate the effort on AI digital transformation with excellence models? What advantage could that?

Sid Ahmed Benraouane:

give organizations. Well, I think, professionals of the excellence field, they need to be involved with this specific standard but, more broadly, with the conversation about AI. As you know, nancy, ai you said very well at the beginning it's a game changer, it's a revolution. Five years, or even actually less, we are going to see AI getting into every single dimension of the organization. So it will be very hard for the market to imagine a company that claimed to be using excellence model without integrating AI applications, ai systems, integrating AI applications, ai systems and managing them and governing them in the way it's supposed to be.

Sid Ahmed Benraouane:

Even for national quality awards, these awards, they have also to align with this digital revolution, with this AI revolution, because, again, at the end of the day, technology main point is to make things easy for business managers, is to create more efficiencies, is to create more effectiveness within the organization and by introducing technologies, by automating different processes within the organization and by introducing technologies, by automating different processes within the organization, of course your hope and your goal is to achieve business excellence and then, of course, achieve organizational excellence.

Sid Ahmed Benraouane:

I must say that within the UAE and Dubai government, and specifically when we talk about the UAE National Framework for Excellence, which is the Gen 2.1, the government excellence model. They have done actually a very good job in integrating these changes in technology, specifically with respect to digital transformation and AI, into their system. Same thing for the Dubai Government Excellence Program, the DGEP program this program, which has been leading excellence in Dubai government in the last maybe 23 years. They have done also an excellent job in integrating technology, in integrating digital transformation, digital applications and in integrating of how AI impact effectiveness and efficiency, but, more importantly, how you can implement these ISO standards in different processes.

Nancy Nouaimeh:

Absolutely. I mean very well said, because I had the experience also to see the GEM 2.0 in action in organizations and the fact that there's a focus on AI is really making a big difference and it's leading the agenda of AI within the government, in the region and in UAE. So I think there's a lot for organizations to focus on and excellence professionals, like you said, they need to be part of that discussion. They need to understand these standards and be able to integrate into what they're doing. So, when it comes to the application, Dr Said, of AI and we know that we focus a lot on efficiency in organizations, on productivity, when we talk about lean and making organizations lean and we introduce that lean thinking in organizations where do you see the elimination of waste and the maximization of values benefiting from the AI development and implementation? Do you see special applications in this area?

Sid Ahmed Benraouane:

Yes, of course, automation itself is a process of waste elimination. When you automate a process, what you have done, you have basically removed the different barriers, whether these barriers are human barriers, cultural barriers or organizational barriers that sometimes impede the seamlessness of the process, of the process. But automation, of course, has to be done in a very, very slick way, in the sense that it has to be thought of, it has some requirements and, more importantly, it has to be implemented within the entire enterprise. So you don't have one department is highly automated and then the other department is probably suffering from lack of automation and more weight. So the value chain, if you will, of the organization has a really, really true understand how you can introduce different AI applications, whether you're thinking about upstream applications or downstream applications, so you're able to create this harmony, if you will, in the process, and by doing so you are making this process more efficient, more effective, and you are allowing people to focus on what matters more and most to the organization.

Sid Ahmed Benraouane:

I think a lot of people talk about automation and now, with AI, we are actually adding one step. So it's not only automation, but also it's automation plus learning and inferring, or making inferences about the future, and that's the added value of AI. So it's not simply making a process automatic, like we used to do with technology in the past and with digital transformation, if you will but with AI we are adding one component, which is a learning component, which is again the machine learning, if you will component. That's the ability of the machine, that's the ability of the algorithm that has automated your process to learn by itself and to develop by itself and to improve by itself. And that's, to me, the most impactable dimension of AI when it comes to eliminating waste and making things leaner and leaner for the organization.

Nancy Nouaimeh:

Wow, I'm just listening to you and I think that's really a great dimension to think of. I mean being able to learn now and being able to make improvements for the future that are generated through the machine learning. And I think we talk a lot about data. I think that will facilitate the role of data and how we can utilize the data to be able to think about what needs to be done in the future. I think that's a great angle to look at. Also AI and how it could help organization become linear and also, I think, excel as they move forward.

Nancy Nouaimeh:

And I think in the first question, when you first described to us the standards, dr Sidhu, you talked about trust and compliance a little bit right. Described to us the standards, dr Sedu, talked about trust and compliance a little bit right. So how can organizations, I think, when they are using AI and developing their AI systems, demonstrate that? I think through certification. That's one of them, but are there other ways to look at compliance and to demonstrate that the AI systems are trustworthy and could generate that trust in the system that they are having in?

Sid Ahmed Benraouane:

addition to certification. Yes, that's probably the most critical dimension of AI systems and AI applications and the entire AI revolution is how can we create a system that we trust? How can we create a system that we trust? And if you are feeding all these generative AI applications all the information that you are given to it, how do you make sure that this information is going to be treated in the way you would want it to be treated? How can we trust the output of different AI systems? How can we trust the recommendation that AI systems provide to us, whether we are buying product or whether we are flying airplanes or we are actually building buildings building buildings? So the trustworthiness is a critical dimension of AI systems and applications and, to this day, we have less robust framework, if you will, for these AI applications to test them against a framework of trustworthiness. Of course, the AI Act, the EU AI Act, has been already published and now actually it's in force. So one dimension we can think of to create compliance and to create trustworthiness is, of course, the legal framework, and the legal framework always will allow, you, will ask you to do certain things and will ask you not to do certain things, for instance, if you are building AI systems that allow you to make some choices or decisions about the labor market, about human resources management which is hiring, firing, selecting, promoting and demoting then that system has to be a trusted system. Otherwise it will be a system that will create more trouble for the organization. So the concept of trust is at the core of responsible use of AI. And you have mentioned we already have the certification which is through and, by the way, the only standard against which you can be certified is 42001. That's why I keep saying that this is probably the most important and it's a game-changing standard. Of course we have, as I said, the regulation, the law, but not only the EU AI Act, because also in the US, for instance, we have many, many laws and regulations that are meant to protect consumers and promote the safety and the health and the well-being of different employees. So if you have an AI system that is against this idea, that in itself could be also problematic. So 42001 is the only standard as of now, but again, we will have in the next, maybe six months. I know, for instance, that the European Committee on Standardization is working on a bunch of other standards to interpret or to put into application and implementation, the EU AI Act, and the goal again is to create, or to help create, this trustworthiness environment. This trustworthiness environment, but in addition to that, of course, awareness, training and capacity building is critical.

Sid Ahmed Benraouane:

I was reading one of the studies published by, I believe, mckinsey, and I think there was one striking number that says about 88% of people in a typical company are engaged with generative AI and only 12% of those that are engaged with AI have a technical background. So, basically, if you take an organization, what you will find you will find that, which is this is the first good news. Actually, you see that people are engaged with AI and that's what you want to have. You want to have people engaged with your technical side, engaged with digital transformation, engaged with technology, but the people who are engaged 12% have technical background and 88%, I believe, have zero technical background, which means these are your average employees. To me, this is good news, but also bad news.

Nancy Nouaimeh:

It's a big gap.

Sid Ahmed Benraouane:

Yeah, good news in the sense that you have created some sort of engagement, and that's very good. But the bad news you don't know what people are doing with those generative AI. You don't know what people are prompting about when they are prompting the different gen AI applications, and that's where you need to focus on training, building awareness, so you make sure that people, when they interact with different AI applications, they know how to interact in a responsible way. So this is what I would say about the trustworthiness, compliance and building this positive, responsible relationship with machines and AI applications.

Nancy Nouaimeh:

Yeah, I think it has to be positive, responsible, I think. Stewardship of AI I like the fact that I mean you've mentioned this gap, because we see a lot of stories in the news news and we read a lot about some of the threats and that comes from AI. So it's important to see that organizations could focus on creating that accountability also and start training, building capabilities to make sure that we do the right thing internally and externally. So the ecosystem has to be strong enough, I think, to support responsible development of AI. So it's good to see the effort that all organizations and institutions are putting on policymakers, because it's important, I think, to have that framework legalized and have really boundaries that organizations need to abide by and follow to make sure that we don't really have major issues there With this.

Nancy Nouaimeh:

I think, dr Sid, we spoke a lot about artificial intelligence, but I know that one of your expertise is on innovation and you've already shared some of your work on that. So just, is there anything you would like maybe to share with our audience here today, something that would be surprising about you as an innovative person? Before we move to the second part of the podcast around innovation?

Sid Ahmed Benraouane:

to tell people about my background is that as an innovator, you do not have to have a specific background. In other words, you don't have to be a technology guy or an HR guy or a business person, or you can be all of that as long as you have critical thinking skills, meaning your mind is working 24 hours. Tend to think about someone who comes from a purely technological background. That is not true. Always, always be open, always, always be creative and you will achieve innovation. As long as you have different lenses, world, living in a multicultural world where you are interacting or looking at different perspectives. All that stuff is enriching to someone who wants to engage with innovation.

Nancy Nouaimeh:

I think diversity is richness, as you rightly said, and being able to having been exposed to different cultures, different environments, worked in different countries on different continents. That really brings, I think, certain richness to one's thinking, and you've mentioned critical thinking and, I think, also system thinking. You demonstrate a lot of system thinking in what you're doing, so these two dimensions are very important, I think, for people to be able to do things in a different way and being able to provide value across and considering all the systems that or the ecosystem we live in. So, just going back a little bit to innovation and excellence, and we see a lot of innovation. I know in the UAE we've had a year of innovation. That will kick a little bit of the work on innovation and the agenda of innovation and organization.

Nancy Nouaimeh:

I think it happened seven, eight years back, so there's a lot of work still to be done on innovation. Organization I think it happened seven eight years back, so there's a lot of work still to be done on innovation. So how can organization, while they are really pursuing excellence and trying to demonstrate that they have sustainable improvement and they are really at a certain level, how can they still innovate and use AI and drive change in this continuously changing ecosystem, while they really keep their leg on the ground and say, okay, we're going to focus on excellence at the same time. So that brings a big challenge, I think, for organizations. What is your advice to people working, I mean to leaders in organizations?

Sid Ahmed Benraouane:

That's a very good question and also it's a big challenge for most of managers and business leaders. How can you sustain everyday work on excellence while you are thinking about the transformation and the change and managing all these things? I think it requires a lot of work. It requires honestly hard work from business leaders and from managers to maintain or to strike the right balance focus on the pursuit of excellence, which is an everyday job, while paying attention and not losing sight of the AI-driven transformation. So two ideas come to mind. Number one is the ability of the organization to manage a change, so change management.

Sid Ahmed Benraouane:

This is a field that we thought we don't need it anymore. We thought that this is a field that probably was going to die, but the changes and the transformations that the world has gone through in the last 20 years are actually pushing for more people to learn about how to manage change, how to lead change and how to thrive in disruption. So that's the first concept that comes to mind, but the second one is the concept of ambidistrictness. This is a concept that means that you need to understand or to work on two different things at the same time. It's like someone who can play soccer with his right foot but also can play soccer with his left foot. This is something that you don't find quite a lot, but an organization that does a very good job should have this ability to balance both.

Sid Ahmed Benraouane:

This ability to balance both, an ability to lead a change, an ability to pursue excellence. And usually how this translates into organizations is always to have two different units One unit that is focused on research, focused on reflection, focused on innovation, focused on AI-driven change applications, and then the entire organization doing what that organization does to excel in its own objectives. But if you try to push everything at the team at a certain point, you may actually get some negative return, and those negative return will translate into some burnout or some people simply leaving the organization because you are asking too much. So this concept of ambidextrousness helps the organization to create different teams a team that focuses specifically on innovation, research and applications, and a team that is focused, again, on excellence and the implementation of different models. And then the ability to integrate them from time to time or to check with these two teams and their output will help the organization to gain.

Nancy Nouaimeh:

This is a great advice, I think. It's much needed, I think, for organizations to look at yeah, how to integrate things but provide the right, I think, foundation for their people to be able to do things in an easy way. We struggle with change fatigue, I think, since the COVID, and we see it more and more with the advancement in technology and what we're trying to adopt in organizations. This is a very valid point, I think, for leaders to look at make sure that your people can cope with whatever plans you're putting in place. And I want to go now to the young professionals and, as we come close to the end of the episode today, what advice would you give to young professionals looking to build a career in AI and digital transformation?

Sid Ahmed Benraouane:

I think young professionals should be very proud of themselves because they live in a world where AI is everywhere.

Sid Ahmed Benraouane:

They need to not only take those AI applications for granted, in other words, because they use them on their phone and on their social media and at home and in their cars.

Sid Ahmed Benraouane:

They needed to understand how those applications work and what would be the best way to utilize these applications to excel in their career.

Sid Ahmed Benraouane:

So if I am a new graduate now, I would really look at the literature about digital transformation, about what has been written on AI, the new standardization, the new regulations that is coming, but also the new many opportunities in AI, whether it's in the US, in Europe, in the Middle East or in Africa, with those international networks that helps you to learn, develop the skills and, more importantly, understand this technology so you are able to use it. I think people who are graduating now they have a very, very good chance to be able to leverage their own learning, to sell, if you will, their skills as technologists and as someone who understands AI and digital transformation, and I think that's what companies are looking for. Recruiters always are looking for someone who brings or who adds value to the organization. And if you are a new graduate, with whatever field or whatever measure you have, and if you can add to it a layer of understanding of the digital transformation or AI implementation, that will make you and make your skills more and more marketable.

Nancy Nouaimeh:

This is great advice. I'm sure I think your professionals will listen to it and because it's really needed, I think for them and they need to differentiate themselves somehow also, so that's a great point to take into consideration. Dr Sid, I would like to thank you very much. We come to the close of this episode and this was really an enlightening conversation on AI and its role in shaping excellence and the future of organization.

Nancy Nouaimeh:

And, as we've seen today with Dr Sid, who's a globally recognized expert in digital transformation, innovation, management and technology policy, who's also an advisor to government entities in the Middle East, ai isn't just about automation. It's about augmentation, it's about empowering teams, it's about unlocking new possibilities, reducing waste, making organizations linear, also making them future-ready. The key is to embrace AI in a responsible manner and maybe at a strategic level, ensuring it enhances human potential and it drives meaningful progress for organizations. So with this, dr Sid, I would like to thank you very much for sharing your insights and thank you to our listeners for joining us on this journey, dr Sid is there anything else you would like to mention before we close the episode?

Sid Ahmed Benraouane:

No, thank you so much, nancy, for giving me a chance to share my thoughts with your audience. It was an honor for me to be with you and I wish you all the best.

Nancy Nouaimeh:

Thank you so much and to our audience, please stay tuned for our next episode, where we continue exploring the future of excellence. Until then, keep challenging the status quo and striving for excellence. Thank you for listening.

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Nancy Nouaimeh

Host
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Dr. Sid Ahmed Benraouane

Guest