Intro/Outro (00:01):

Welcome to Digital Transformers. The show that connects you with what you need to build, manage, and operate your digital supply chain. Join your host in a timely discussion on new and future business models with industry leading executives. The show will reveal global customer expectations, real world of employment challenges, and the value of advanced business technologies like artificial intelligence, blockchain, and robotic process engineering. And, now we bring you Digital Transformers.

Kevin L. Jackson (00:43):

Hello, everybody. This is Kevin L. Jackson, host of Digital Transformers, and welcome to 2022. On the Chinese Zodiac, 2022 is a year of the tiger, which signifies a time for making big changes, a year of risk taking and adventure. I’ve personally seen that businesses are finding enthusiasm again for both their professional and personal lives. Everyone is fired up and that includes the entire digital transformers team. In 2022, we welcome back our inaugural sponsor, Total Network Services, who has kicked off the year with a recent feature in smart industry magazine online on how their blockchain enabled network device security service is helping manufacturers meet the internet of things security challenge. We’re also excited to announce our newest sponsor, AT&T Business, who will be regularly featured on a video podcast this year. We are also proud to work this year with the Middle East and North Africa Cloud Alliance, better known as MENACA. This organization is a nonprofit vendor neutral industry association with a focus on strengthening local cloud markets by leveraging a unique community of major players within the Middle East and North African regional technology ecosystem.

Kevin L. Jackson (02:21):

This January 2022 video podcast features the advanced technology convergence panel from their recent road show in Qatar. The panelists discussed any other things, blockchain, artificial intelligence, machine learning, automation, and innovation at scale. Please listen to Dr. Mahmoud Barraj of the Middle East Artificial Intelligence Foundation; Lee Allcorn, Temenos Director of Software as a Service Middle East and Africa; Samer Mahmoud, Senior Manager Solutions Architecture at Amazon Web Services; and me, Kevin L. Jackson, as we discussed disruptive ideas and groundbreaking insights into the Middle East Regional and Qatari cloud ecosystem. Thank you for kicking off your new year with Digital Transformers.

Lee Allcorn (03:24):

My name is Lee Allcorn. I’m the moderator of today’s panel, where we’re going to talk about the role of cloud with these emerging technologies. And I have some fantastic, fantastic panelists to join me today. So, gentleman, we can go around to just briefly introduce ourselves, to maximize our time and I go around. And, Samer, would you like to start, just like to say hello to everyone and introduce yourself?

Samer Mahmoud (03:45):

Sure. Thank you, Lee. Hello, everyone. So, my name is Samer Mahmoud. I’m based out of UAE, Dubai. I work for AWS. I’m leading the Solution Architecture Team for product sector, working closely with our customer and product sector in the region.

Lee Allcorn (03:58):

Brilliant. Thank you, Samer. And, Kevin, good morning, I think.

Kevin L. Jackson (04:04):

Yes. Good morning. Good early morning. How are you doing today? Kevin Jackson. I am the host of Digital Transformers on Supply Chain Now. Also, I’m technologist and a consultant, helping organizations leverage all cloud computing and all the technologies that are built on top of cloud. Thank you for having me.

Lee Allcorn (04:26):

Brilliant. Thank you, Kevin. And, bit closer to home, Dr. Mahmoud.

Dr. Mahmoud Barraj (04:30):

Thank you so much. My name is Mahmoud Barraj, founder of the AI Foundation Middle East. So, what we do is we are an AI research company by heart. We have business leaders is across different verticals, map applications, and applications of AI to help them basically develop and validate winning AI strategies. Thank you for having me.

Lee Allcorn (04:51):

Thank you, Dr. Mahmoud, and I really look forward to your insight. And, just to finish up with myself. So, as well as moderating panels, which seems to be a bit of full-term role lately, my role is I run cloud for Temenos. We just do banking software, so I run the cloud part of Temenos here in the Middle East.

Lee Allcorn (05:09):

And so, let’s get going with today’s panels. I know how these sessions work. There’s going to be lots of conversation. I know we’re going to have, you know, a lot of interaction. We’re pretty [inaudible] but I’m going to straight into it. And, Kevin, [inaudible], okay. So, it’s the first time we’ve actually interacted, Kevin. So, I’m really, really look good to what you’re going to come across with. So, now we’re talking here about cloud and, but specifically how some of these new technologies can work with cloud and clearly in the context of Qatar, right?

Lee Allcorn (05:35):

So, I want to keep everything in the context as we can as local as we can to Qatar. So, one of the things, when you adopt any technology and you put it in the cloud is you’re sort of giving up control a lot of the time, right? You’re giving up control of how things are running and how things are operating. You know, how do customers keep some sort of control? And, I think that’s particularly, you know, concerning when we talk about things like AI technologies, you know. So, what’s your thoughts on this? And, you know, how do you think, you know, customers can deal with this challenge?

Kevin L. Jackson (06:03):

Well, first I’d like to challenge you on that you don’t give up control. In fact, it’s important for you to realize that you still have the responsibility. So, the first step is to do proper due diligence before you trust your data or any of your business processes to a cloud service provider. And, in my experience, this is the really – the first step, lack of proper due diligence in just about every security incident trail of events. This is what you see in failed cloud deployment. The root cause of the era normally lack of proper formal training on cloud technology, service models, and economic models. Consuming a cloud service is very, very different from a traditional IT organization’s role of buying and implementing technology. You are consuming technology services. So, it’s a false assumption that the cloud service provider will shoulder all of the responsibilities for meeting your requirements, policies, and expectations.

Kevin L. Jackson (07:22):

The only responsibility that the CSP has is to deliver their services in accordance with the published service level agreement. You know, people don’t like hearing this, but your requirements mean just about nothing to the cloud service provider, really. I mean, they have built the infrastructure. They have designed the service to target a specific customer set. If you happen to be in that customer set, great. If you are not, it’s your fault. So, failure to ensure that the published SLA is sufficient to meet your organization’s IT policies and operational requirements is your responsibility. That’s where you keep control. So, failure to ensure that all the required data security and privacy controls are available and that your organization has the proper processes in place to continually monitor the effectiveness of those controls is your responsibility. And, that’s how you maintain control.

Lee Allcorn (08:39):

You know what, Kevin, I couldn’t agree with that more. In fact, and we didn’t rehearse that answer. And if I was to write a script what I would like you to have said there, that be new. And, I spent my life working on contracts with clients for banking software, right, which is the most regulated strictest piece of, I think, of any, maybe other than military’s pretty much strict to get in the IT business. And, it is all about clients understanding what that service is and what they don’t, you know, what they give up is in the contract. So, literally, you can have said that any better. So, yeah. Thank you.

Lee Allcorn (09:15):

The piece I’ll add is that most decent cloud providers give a level of contractual protection around governance, right? So, what you can change, what you can’t change, what you can do. And, I think that’s a bit to, really, focus on because even if you’re not sure if you’ve got the service right, or what can you adapt as you learn yourself as you go on, you know, what’s in that [inaudible] because there’s some sort of contractual change in the earth, so brilliant. Absolutely, brilliant.

Lee Allcorn (09:36):

So, Dr. Mahmoud, I’m going to pick on you now, if I may, sort of extending from that. But I am saying Dr. Mahmoud – is it – do I address you as doctor? Or do you like just Mahmoud?

Dr. Mahmoud Barraj (09:48):

Mahmoud is better. Mahmoud is better.

Lee Allcorn (09:49):

Okay. Mahmoud. I like the doctor title. [Inaudible] Mahmoud for familiarity. So, now, if we’re talking about technologies like AI and blockchain, ML, who, as in function-wise, should be evaluating these from a crowd perspective? Is it just an IT decision to look at these? You know, what’s your view on who in customers should be looking at these technologies?

Dr. Mahmoud Barraj (10:14):

Well, actually this is great question, Lee. That’s basically one of the most recurrent questions that we receive from different clients across different verticals. So, question is like, who shall lead on the evaluation process, who should be part of the team, or is the best team composition and what have you? So, basically, AI has the biggest impact when it’s developed by cross-functional teams with a mix basically of perspectives and skills. So, when you have a business and operational work side by side with technical expertise, you’d find the best results. So, initiatives address, broad organizational priorities other than just isolating business issues. That’s really damaging the full process of the ideal deployment of AI project or initiative. So, just, also it’s worth noting that it, of course, depends on the size of the business, the nature of the business and the scope of the AI initiative at hand.

Dr. Mahmoud Barraj (11:19):

But, in a general sense, the general take, I would suggest basically a team composition of an executive sponsor. And this guy is basically responsible of – it shows that there’s a management by end towards the AI projects to ensure that these initiatives will be successful. And, also this role entails the executive sponsor to ensure that it’s aligned to the organizational objective system architect as well. A data engineer is normally over overlooked. I believe it’s one of the most important role within an AI team composition. They are responsible of keeping the quality of the data in check. I mean, the value output is as good as the input. So, this shows how important the role is. A data scientist, of course, who is responsible of developing or finding patterns within the data and basically generating insights from those systems. And last, and as important I believe, is the business side, the frontline managers or front frontline leaders, which basically they make business sense or economic to the organization and through those AI initiatives.

Dr. Mahmoud Barraj (12:36):

So, in my opinion, this will basically accelerate adoption and reduce resistance for the initiative to kind of succeed.

Lee Allcorn (12:47):

Absolutely, 100% on your page. And, you know, you took that executive sponsor. I’ve made notes here, data scientist, client architect, and the business sponsor. I think you covered it brilliantly there. And, from certainly my experience, if you don’t have those four functions, either the project never gets signed in a contracted form or it does get contracted [inaudible], it never gets adopted. Just to extend, I know I didn’t ask you this beforehand, but just to extend on that a little bit, if a customer doesn’t have those skills, particularly thinking about data science, right. You know, they’ll have a business sponsor, like everyone have an executive sponsor, but data scientists may be quite client architect. They don’t have those skills internally. You might have a bias opinion on this, but can they pull those skills in?

Dr. Mahmoud Barraj (13:25):

That’s the thing. I mean, it depends again on the nature and the size of the organization that we’re talking about. If it’s a large organization, I believe they should have the human capital in order to kind fill this position. If it’s an SME or a small kind of size company, I believe some of those, [inaudible] the executive sponsor could work, could have different hats. If he’s working in tech or he’s working retailer, he can basically – the data engineer could find – because those titles are fairly new and there’s a lot of commonalities across most of the titles or most of the operations, but the composition which I gave is basically directed towards large organizations. When it comes to smaller organizations, you can combine overlap certain task.

Lee Allcorn (14:21):

Yeah. Okay. Brilliant. And, I think often, and also the reality, I think, you know, [inaudible] you may not have all these schools anyway, locally, so that that’s a brilliant answer. So, Samer, so we have the what with Kevin, we’ve had the sort of who with Mahmoud. So, I’m going to go and talk to you about how a little bit, you know. You know, how do you see companies leveraging and adopting AI and, you know, who’s getting first mover advantage and what’s the use case? Can you talk me through your thoughts on there?

Samer Mahmoud (14:48):

Yeah, sure. So, technology in general, we know that technology in general enabled consolidation and it shifts power. We saw this happening multiple times, and once consolidation happen and power shifts, the barrier to entry is very high for competitors, so, whoever started with this. And, AI is not any different. AI is still part of the technology enablers that can lead to consolidation and at the same time to the shifting powers. So, the competition game is not a leapfrog anymore. The moment you have the first mover powered by AI and other technology, it’s very hard to catch up with you. Very quick example. We know this physically happens with libraries, so very less people now go to library to do research. They go to Google or to any search engine to find that information they’re looking for, and it’s happened in the automotive way before also.

Samer Mahmoud (15:38):

So, shifting powers is very important. If I take this and put in the AI context, it’s – and I take one use case, which is image processing for healthcare. So, processing MRI images or x-ray images, the future where we, it looks like we’re going towards, it’ll be two to three big centers or AI algorithm, what will be able to process the image and provide the feedback to the consumers as a service. So, it’s not [inaudible] these scattered centers where they are doing all of this. Now, if we take one step back and look more into a little bit more details about how this cycle is happening, one of the great practices in recent IT technology is the DevOps. So, DevOps is the ability to update your code and your application way more frequent than what we used to do before. And, in some cases, some organization, they can send updates every 10 seconds or even every 1000 updates a day.

Samer Mahmoud (16:37):

And, definitely they don’t do this for the sake of just doing this. There’s an effect of Flywheel behind that. So, they do the updates so they have a better application. If they have a better application, they have more users. And the moment they have more users, they actually have more data. That’s where the magic happens, is they having and collecting data because the moment they have the data, which is the most important input to AI and machine learning, that’s where they can create this barrier and maximize on this barrier. And once the Flywheel end, it’s keep moving.

Samer Mahmoud (17:11):

So data itself, it doesn’t happens intrinsic value unless you take it and work on it and try to get something out of it. And, the key magic ingredient here is technically your own data. Because many organizations, they can rely on open data, they can rely on buying data, but what gives you the actual advantage is your own data. And that’s how everybody’s trying to go and do.

Lee Allcorn (17:36):

Brilliant. And, I’m going to pick up on a few points you said there. Healthcare, DevOps, and your own data were the three sort of big things I took out what you just said there. I mean, if the healthcare industry doesn’t adopt it first than known, well, I really do believe that, and it’s outside of my field of expertise, but that’s where the need is. Often healthcare has the desire and the money to fund these things in many case. DevOps, because it is a simple, easy way to start and learn for all industries, for sure. And, I love your point on data. It’s definitely on my personal expertise, but, you know, building these models on your own data surely has to give you leaps and frogs and bounds of advantage. So, thanks, Samer, that’s very useful.

Lee Allcorn (18:15):

So, I’m going to go from one extreme to the other. Kevin, I’m going to come back to you and you’re on mute, Kevin, by the way. Kevin, I’m going to go from one extreme to the other now. So, [inaudible] first mood advantage and probably makes it easier to get going. That’s where it might be a bit harder. Let’s talk about what really regulated industries, you know governments, banking. Can these guys really adopt cloud for emerging technologies in Qatar? You know, what’s your view there? I’d love to hear that.

Kevin L. Jackson (18:41):

Well, absolutely, yes. Highly regulated in industries can certainly adopt cloud technologies but, you know, senior management must absolutely must complete two crucial enabling task. The first, and I’m taking a risk here of repeating myself, but senior executives must be properly trained and they need to be educated on how to evaluate, select, and manage cloud services. This process is not limited to the IT team to be cost effective and to have secure cloud operations no matter to industry. This, you have to have it managed and understood by every critical business process because going to the cloud or cloud strategy will affect every one of your processes. This includes acquisition, legal, governance, project management, budgetary management, and revenue recognition, where everybody’s really important. And, second, industry regulators and stakeholders must be made fully aware of the significant differences between traditional enterprise, IT service model, and an enterprise cloud IT service consumption model. The organization must ensure that they are fully briefed on their differences. I’m talking about the regulators and the stakeholders within your industry vertical, and they need to have agreed to modify or even in some cases, eliminate regulations or laws, because the previous laws and regulations were designed with a different world view. And this also establishes some different expectations that may conflict with the cloud IT service model. So, these two aspects need to be addressed by senior management. Once senior management has the understanding of the policy holders, the regulators, and other important stakeholders in the ecosystems, then go to cloud.

Lee Allcorn (21:19):

Yeah. Absolutely. I love that the two themes there, one of let’s get educated especially we’re a bunch of old timers on this call. We are all in a similar situation, but we think we know everything, but we probably don’t. Right? So, we get to, you know, be humble enough to learn. And the point you pick that’s really close to my own heart is regulators. Regulators really need to try and say yes instead of saying no first. You know, how can we say yes to doing things as opposed to a speaker conservative is saying no, and hope it goes away in the future. Right? Let’s really try and work things up. And, I think that’s down to us on this call, it’s down to our clients to help the regulators, get them on that journey. So, thank you, Kevin. That’s really good [inaudible].

Kevin L. Jackson (21:59):

Absolutely. It’s important to have a conversation with the regulators, and this is a two-way dialogue.

Lee Allcorn (22:13):

Hundred percent. And so, I’m going to extend that conversation again. I like this is just flowing beautifully and I didn’t plan for this, but, you know, Mahmoud. And now, sort of bringing that down close to home, Qatar, and you know, where can you see the biggest actual use cases? We talked about a bit like industry with healthcare, and we’ve talked about some of the barriers, maybe some of the regulators, but in all practicality that you’re going to have on this call will be people from all sorts of industries, all sorts of sides. And where would you go, hey, here are the big use cases, right? There are the use cases we should be going after. What would you say?

Dr. Mahmoud Barraj (22:47):

So, basically yes, true – I mean, the idea of AI is still in its infancy globally. And, like Kevin was saying, it’s very much – everyone needs to be educated on this front, whether it’s business leaders or executives, board members. Everyone should kind of educate themselves when comes to AI. Because it’s basically revolutionizing every discipline that we know whether it’s healthcare, education, sports, media, I mean. And, for Qatar, it’s basically you’d find AI applications across more sectors. And, probably, we find from customer support chatbots to industrial robots. So, it’s across the board. More specifically, when it comes to AI domain I see more, for 2022, AI domains, like machine learning, natural language processing, computer vision, image processing, like we said healthcare, government, sports, education media, [inaudible], they’re implementing major use cases, cyber security, as well is a hefty one in Qatar.

Dr. Mahmoud Barraj (24:05):

So, on an education level, you find like several use cases, including like recently Carnegie Mellon University in Qatar, they have a branch here in Qatar. So, they’re utilizing at artificial intelligence and the fleet of autonomous robots to better explore and basically graph the marine environment around Qatar. [Inaudible] Corporation’s speaking about healthcare. They’re doing [inaudible] on this front as well a lot of things in the pipeline when it comes to radiology, pathology  and the list goes on and on. Aspetar Hospital, which is basically for sports and athletes hospital, they’re using prevention cases, Aspire Sports Academy as well. [Inaudible] use cases like to not understand utilizing machine learning to help athletes basically understand the right posture at the right moment when they are playing. And, recently, just recently, FIFA is basically testing an AI supported offsite technology for the Arab during the Arab World Cup, now it’s happening here in Qatar.

Dr. Mahmoud Barraj (25:12):

So, it sends like an instant message to the referee and the referee makes a decision whether it’s a correct goal by the AI system or not. So, it’s still investing phase. But I see it being realized very soon. Al Jazeera, the media giant as well, I mean, they’re utilizing in certain areas of their own businesses. [Inaudible], like for example, content moderation, just to make sure they are compliant with the international standards.

Dr. Mahmoud Barraj (25:44):

So, I mean, the list goes on and on and, but particularly answering your question, those are the key industries. I still insist that most like retail also, they’re embracing, probably in a slower momentum, but their attention is there. And, I see them embracing as well very soon.

Lee Allcorn (26:04):

That’s surprised me. I’m going to – so that surprised me about the retail statement there. And, I wonder if that’s a local nuance. I mean, I’m not a retail expert, but it feels like as a consumer, I guess, that if anything retail’s one of the faster adopters, but, and I’m going to pick on you Mahmoud a little bit here. So, if you were to advise, and maybe Samer and Kevin chip in after, but if you were advising the government of Qatar, you know, to the 2022 focus or encourage and these three things around AI and ML have the biggest impact next year, what would those three things be?

Dr. Mahmoud Barraj (26:38):

Healthcare. Again, because I mean the AI applications and applications on healthcare is – although, I mean, like I said, a medical hospital they’re doing really big advancements on this front, but I believe there’s also a lot of space to fill. Sports as well. I mean, the world cup is coming. There is a lot on ground operations that can be automated utilizing AI for their own good. This will ensure optimization of the resources. Education. I mean, we also – I came across one of my clients. We had a discussion. They are also testing. This is just in a testing phase. They’re testing like early a detection kind of AI software to identify possibility of mental disorders for kids at an early stage. So, again, this is a testing phase. I mean, if this pulls off, this is an amazing, I think. Because, you know, when it comes to mental disorder or ADHD or autism, if you early, if you catch, or if you manage to understand or locate the student’s struggling, you can help them early on in the position or devise a solution for him at an early stage. So, yeah, that’s basically –

Lee Allcorn (28:04):

Education, sports, healthcare. Kevin, you want to chip in?

Kevin L. Jackson (28:08):

Yeah, sure. I’m going to say something that people may not really realize and this is an entertainment. You may not know that as you are consuming content, there’s AI evaluating you as a consumer and maybe actually changing what’s being delivered to you based upon your needs, your wants, or what they want you to think and what they want you to want. So, entertainment is actually leveraging AI in a big way.

Kevin L. Jackson (28:45):

The other area is in smart manufacturing and smart factories. Computer vision is being used with AI and the internet of things in order to improve efficiency, reduced waste, and reduced cost. This is really changing the economic model in the manufacturing industry. And, once again, that’s something that’s sort of behind the scenes that you may not realize.

Kevin L. Jackson (29:16):

And, the third thing that’s sort of CPS is AI that’s being used in data processing. Okay. Trying to determine what data is important, what data is not important based upon the goals of the organization, and then picking that data, processing it and delivering it. One of the important aspects ethically is really the biased, data biased, and biased in the AI process itself. This is a big issue.

Lee Allcorn (29:56):

Yeah. It is. And I, you know, that entertainment point I’m going to pick on specifically because media – well, Qatar and media got a very successful industry in media that’s born locally, but running globally. So, I think that one really resonates for sure. Samer, any extra comments for you on that topic?

Samer Mahmoud (30:13):

Just a quick comment. So, probably we spoke about this, Lee, and I’m a big fan of AI in healthcare. So, because simply we know many of the diseases that human being faces are very easy to deal with if they have been detected early and that’s exactly what AI can help with and save a lot of pain for our love one.

Samer Mahmoud (30:35):

Another one I will actually second Kevin on is the manufacturing and AI. So, we know that many of the manufacturing has happened using robots, part of the automation and the 4.0 industry revolution and manufacturing, but what AI is giving the robots now. So, most of the robots in the manufacturing industry and the production lines what we call are blind robots. They only follow what exactly they are programed to do. They don’t make decisions by themselves. AI is making them smart, and not only blind, they can even take extra steps and do extra stuff by being empowered to make decisions on the production line. So, definitely two key areas.

Samer Mahmoud (31:13):

And the last one, probably I second also Mahmoud on that, which is very important, is education. So, the same way works for entertainment. So, what data is being collected to provide you with the next best movie to watch, it’s same works in education. So, there’s a lot of content in education. A lot of data get collected from the students and propose what next would be best for the student.

Lee Allcorn (31:37):

Excellent. Thanks. And, I hope the audience, we can’t see the audience, but I hope those scribbling notes because you all came up with very good use cases. And actually there’s a lot of overlap there between, and so I’m hoping that Qatar audience go “That was me, that was my use case.” I’m going to, yeah, follow up. It’s very good.

Lee Allcorn (31:52):

So, my last question is to you, Samer, well, actually we got one more point [inaudible] with Samer, back to you, I guess, is, you know, machine learning, AI, is it for everyone? Or are we really practicalities just talking about of organizations? You know, can small businesses use these types of technologies or is it just out of their reach? What’s your view there?

Samer Mahmoud (32:12):

For me, it’s a very straightforward answer. Definitely indeed, it’s for everyone. And, the main reason for that is the, what cloud brings in. So, the cloud empowers everyone to go and test and innovate without having to put in a huge capital investment at the beginning. And, again, so as we discussed before, AI will help you to beat a competition and have a high barrier of entry. But to enter AI itself, the barrier of entry is very low and that’s, again, back to what the cloud provider can help and provide.

Samer Mahmoud (32:46):

However, there’s some key points that’s very important to have a very successful AI project. So, it’s always start with the business. So, whatever we do, whatever technology we’re using, these technologies are only enablers for our business or for a business case or something we need to achieve from a business point of view. So, to understand what question we need AI to answer, and if this question will be helpful or not, that’s very important as a starting point.

Samer Mahmoud (33:11):

Next data, as Dr. Mahmoud mentioned, the quality of the output depends on the quality of the input so we need to know, make sure you have the data and the data actually affects the prediction of the future so you can use it and build on top of it. And then, resources. Again, you need to make sure you have the right resources either by having them in-house or to outsource the skills you need, like data scientists, data engineers, and so on. And the last thing to keep in mind, which is very important, and this is again, back to Kevin point at the beginning, and Mahmoud touched on it and I will second this again. Education at all levels of organization, because this will make it very, very easy to have a successful project. Without education, for example, AI, many people think AI is something magic that if I have it, I can do magical stuff, which is not the case. Education will help in picking the right use case that benefit the business and the success rate to be much higher in an organization and all levels, not only the higher levels, all levels, including online of business in the business.

Lee Allcorn (34:15):

Brilliant. Thank you, Samer. That’s very insightful, I think. Well, gentlemen, we’re coming towards the end now of the session. I just want to wrap up and don’t think you’ve got wait for this for free. I want you all now to, and I’m putting you on your toes here. I want to come over an offer guys each, right, one minute each. I want something you can offer the Qatari, you know, people here that are listening, what can we do to help them, right? You know, us, as individuals or the organizations we represent, what can we do to help these guys get going faster? Dr. Mahmoud, I’ll pick on you first.

Dr. Mahmoud Barraj (34:47):

Yeah. So, I mean, basically, there’s a lot of things that we need to basically adapt on. But, I mean, I’m just going to compile them into possibly three or four points. As far as AI is concerned, first, I would advise, I will suggest enterprise executives to start by researching different AI domains across their own verticals, understanding what goes on within it, understanding the underlying dynamics and what is the best practices, what other use cases, check around what’s happening in their industry, recent developments. And then, identify business processes where AI can create and capture value. And this is really important to avoid like a vicious circle of looking for business process to kind of create unnecessary havoc within this business unit. Make sure that those processes are already in good shape so that you can, again, you wouldn’t create havoc within this business processes. Third, I would advise to determine the potential returns that AI could deliver in each area or process. And finally, designate three or four or five business tops, five business processes with the highest AI potential returns and focus on those and deliver on those. And as soon as you are achieving or are making business sense of them, you can introduce other AI initiatives or projects.

Lee Allcorn (36:25):

Wonderful. Thank you, Mahmoud. Samer, from you, please. What can you give up?

Samer Mahmoud (36:30):

I would highly recommend – so, I represent AWS and we do have a lot of services that in the domain of AI and machine learning and data processing. So, I will highly recommend to go and test them. Most of these services have a trial period or version. It’s very nice to go test them, play with them, try your ideas. Something may work and get familiar with them. That will be very useful.

Lee Allcorn (36:54):

Brilliant. And I think that money’s particularly valuable one. Thank you. It’s nice to made riff on the call, Kevin, last but not least, what can you offer?

Kevin L. Jackson (37:02):

All right. So, with all due respect to Samer and AWS and many other CSPs that I work with, do not rely on vendor specific training or education when you’re developing and embarking on your cloud journey. Doing so may lead you on a blind path to vendor lock in. You should always expect to use multiple cloud service providers and make sure that your policies are in place and that you expect, you can expect to change and use different cloud service providers. So, you must always have a vendor exit strategy in mind. I love AWS Samir, but.

Lee Allcorn (38:01):

That’s brilliant. Well, hey, I’m a vendor myself, so that hurts a little bit. But no, I think that’s very, very valuable point. That’s very good. I’ll extend and say here at [inaudible], so if anyone on the call from banking, et cetera, then give us a shout. What we can offer you is you’ve got an independent benchmark called Temenos value benchmark, where we look at banks that have adopted various technologies and get rated on their agility, their cost of ownership, their return of equity, things like that. So, you can go [inaudible] adopting this technology compared to other banks, what would that look like? So, you get a representative set of data to use. So, that’s the offer from Temenos that we can – the Temenos value benchmark.

Lee Allcorn (38:44):

So, gentleman amazing. You’ve been a great crowd that flow brilliantly. I hope the audience enjoyed it as much as I did. So, with that, thank you very much.

Intro/Outro (38:53):

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