CIO CIO

What the framework says The new Framework creates a three-tier licensing hierarchy. Favored countries such as the 10 EU nations will be able to purchase AI chips, including the most powerful, without restriction. Most countries fall into the middle tier, subject to export licensing restrictions on how much computing power they can get hold of. And then there are coutnries that already can’t buy AI chips from the US, including obvious candidates such as China and Russia. For countries in the middle tier, if an individual order doesn’t exceed a “collective computation power up to roughly 1,700 advanced GPUs,” — the sort of GPU power used by a university or medical institute — no export license will be required. These sales won’t count against national chip quotas. As for LLMs, sales of the most powerful proprietary models will also be restricted outside of the favored countries. The US Department of Commerce’s Bureau of Industry and Security (BIS), which drafted the framework, defines the restricted models as those built using closed (as opposed to open-source) weights using more than 10^26 computational operations. source

00:00 Hi everybody, welcome to DEMO, the show where companies come in and they show us their products and services. Today I’m joined by Ameesh Divatia, he is the co-founder and CEO at Baffle. Welcome to the show, Amesh. 00:10Thank you, Keith. Happy to be here. 00:12So tell me a little bit about Baffle, and then tell me about what you’re going to show here today. 00:016Absolutely. So Baffle is what we call the easiest way to protect data. What we do is protect data all the way at the field level, so that the cloud service provider or somebody that’s managing the infrastructure never sees sensitive data. So that’s the crux of what we do. We do it with a with a no-code model, we make sure that there are no application changes needed for masking, tokenization, encryption of data. 00:39Who within the company is going to benefit most from using Baffle, is it the CIO level? Is it someone who’s trying to access data, or are you preventing certain people from not seeing data? 00:51Well, the main benefit is for data scientists, they want to analyze data, and they’re prevented from doing so if that data is sensitive. So there’s lots of rules and regulations around it, compliance requirements that security typically sets. So security is usually the one that finds us, but it’s a data scientist that we benefit the most. 01:10So in the problem you’re solving, as far as I can tell, and you can tell me if I’m right or wrong on this is that it allows certain people to see data that’s encrypted, and you’re not unencrypting it or decrypting it, right? So you can still see it, and that just that blows my mind. That’s just like magic wand to me at this point. So again, why should people care about this? Like, what problems are people having when you’ve got people trying to look at encrypted data? 01:34The two main problems, the first one is data breaches, right? Everybody is inundated with, we all get these requests all the time from companies that have shared our data inadvertently, and they’re trying to make make up for it. So data breaches continue to happen. They’re proliferating, which means that the existing data protection solutions don’t necessarily work. What is very interesting, though, is in the past five plus years since GDPR went into effect, there’s a plethora of regulations that are coming into effect for preventing exactly this problem, which is that individuals, just you and I, should not be losing their data just because we share it with somebody that we trust. 02:12So if a company didn’t have something like Baffle on their system in order for someone to look at the data, you would have to decrypt it, and then keep your fingers crossed that that data doesn’t then get breached or stolen or somewhere sitting on a server somewhere unencrypted. 02:26Actually, the problem is worse, because when the data is still on their systems as it’s being processed, it can be exfiltrated. It can be breached. Especially if the database admins credentials are compromised. So you know, at the highest level, we have our phones and we have our messages, iMessages or WhatsApp messages are end to end encrypted. Enterprise applications are not. 02:51So there’s data out there that could be unprotected at this point. 02:55Exactly. So we have protected data at rest. We’ve protected data in transit, but we don’t protect data in use. 03:00So you’ve got some cool things to show me on the demo here. Let’s jump right into it and show me the cool features. 03:07All right, so the animation, the right sort of captures exactly what we do. If you look at the flow of data, it’s coming in from, usually from clear text from an on-prem database, or even if it’s in cloud, it’s the one where the data is clear text, then it goes into this particular protected data, usually in the cloud. So we transform the data all the way down at the field level. So you’re seeing these credit cards. These credit cards are now being transformed into something that’s still readable. It still looks at the credit card, but it’s not the original credit card, and then depending on the persona and the credentials that anybody who has access to the data can get, they can get views of that data. So that’s what you’re seeing in the second half of the animation. Okay, that sort of captures what we do in 30 seconds. So now let’s dive into this. This is our console. This is Baffle Manager. And there’s a few things that are going on, on the left. First of all, what we do, as you could see, there is the application, there is the database, and there is something in the middle, which is what Baffle is. So first things first, what we do is we enroll a database. So this is the database itself that’s been enrolled. It’s a Postgres database that has sensitive data. So step one is actually to figure out exactly what kind of data protection policy that you’re going to have, because, again, we’re going all the way down to the field level. So let’s first start with the data source, which means that you have different sources of information that’s coming in. I’m going to create one just for kicks, because it makes it fun to see. I’m going to see what we can do with this particular database, and what you’re able to do with this is to go all the way down to this particular table and see what is in there and be able to pick which column to encrypt. So now what we’re going to do is we’re going to go into the Postgres database. We’re going to go into the specific table that we’re going to protect. It’s called transactions, and you see all of these things in there. I’m going to make it very simple, just protect one particular field.

With advanced technologies like AI transforming the business landscape, IT organizations are struggling to find the right talent to keep pace. The gap between emerging technological capabilities and workforce skills is widening, and traditional approaches — such as hiring specialized professionals or offering occasional training — are no longer sufficient as they often lack the scalability and adaptability needed for long-term success. According to IDC’s July 2024 CIO Sentiment Survey, 26% of CIOs identify recruiting, retaining, and upskilling talent as their biggest challenge to success. Skill mismatches (31%) and inadequate training and development opportunities (29%) underscore the demand for talent as well as the difficulty in finding candidates with the right skills. The problem isn’t just the shortage of qualified candidates; it’s the lack of alignment between the skills available in the workforce and the skills organizations need. Take cybersecurity, for example. A staggering 21% of organizations report a severe shortage of skilled cybersecurity professionals, with another 30% finding it difficult to find suitable candidates. Only 8% of organizations have a relatively easy time finding qualified cybersecurity experts. This shortage puts additional pressure on existing IT staff and leaves organizations vulnerable to cyberthreats. As the pace of technological advancement accelerates, it’s becoming increasingly clear that solutions must balance immediate needs with long-term workforce transformation. Spoiler alert: The solution we will explore in this two-part series is generative AI (GenAI). But before we get into that, let’s talk about what steps CIOs have taken to ensure their teams are equipped to navigate this rapidly changing environment. Current strategies to address the IT skills gap Rather than relying solely on hiring external experts, many IT organizations are investing in their existing workforce and exploring innovative tools to empower their non-technical staff. Organizations have adopted several strategies to acquire and develop talent, as illustrated in the bar chart below. IDC’s CIO Sentiment Survey, July 2024 Cross-training or hiring line-of-business (LOB) staff to do IT: A notable 41% of organizations are cross-training or hiring internal LOB staff to perform IT functions. Leveraging current employees who already understand the company’s operations and culture can build a more versatile and adaptable workforce. This approach can help foster collaboration between IT and other departments, but while LOB staff bring valuable business insights, this approach doesn’t necessarily build the long-term technical expertise needed for the IT team to complete complex tasks. Devolving duties to LOB staff: 40% of organizations are delegating duties to non-IT staff through tools like no-code or low-code platforms. These tools enable employees to develop applications and automate processes without extensive programming knowledge. Using this strategy, LOB staff can quickly create solutions tailored to the company’s specific needs. However, without proper governance and oversight, this can lead to inconsistencies, security vulnerabilities, and technical debt. Additionally, while these tools are excellent for simple applications, they might not be suitable for more complex systems that require specialized IT expertise. Training programs: To bridge the skills gap, 34% of organizations are utilizing external training and certifications, while 28% are implementing internal upskilling programs. By investing in their current workforce, companies can equip employees with in-demand skills and prepare them for evolving roles. However, this approach isn’t always feasible, as it requires significant time, money, and commitment from both the organization and the employees — and continuous updating to keep pace with rapid technological changes. This indicates a strong effort by CIOs to bridge skills gaps and offer some relief, with some organizations reallocating internal talent and others investing in formal training programs. However, while these fragmented strategies address immediate needs, they lack scalability and a forward-thinking approach. Is there a transformative solution that meets current operational demands while also fostering future skill development to effectively close the skills gap? GenAI: A transformative solution to the IT skills gap Enter GenAI, which offers the potential to revolutionize how organizations address the IT skills gap. GenAI can augment workers’ capabilities, automate complex tasks, and facilitate continuous learning. It can play a pivotal role in filling the skills gap through several key applications, such as: Cybersecurity assistance: GenAI can monitor networks 24 x 7, detect anomalies, and respond to threats in real time, helping to compensate for the shortage of skilled cybersecurity professionals. Knowledge management: GenAI helps organize and retrieve organizational knowledge, making it easier for IT professionals to access the information they need to solve problems and learn new skills. Virtual assistants and IT support: GenAI-powered virtual assistants can handle routine or repetitive IT tasks — like resetting passwords, troubleshooting common software issues, managing access permissions, and monitoring system performance — reducing the workload and allowing IT staff to focus on more complex and strategic tasks. Continuous learning and development: With GenAI-driven learning platforms, IT and business workers can have customized training modules tailored to individual learning styles and skill levels that continuously update based on the latest trends and technologies. And more: These are just a few examples; GenAI has many applications and can be tailored to meet specific organizational needs. Despite the pressing challenges posed by the IT skills gap, many organizations hesitate to embrace GenAI’s transformative capabilities: Just 30% of companies plan to augment IT and business workers with GenAI, according to the CIO Sentiment Survey. This leaves a significant 70% who aren’t exploring this avenue. CIOs who act decisively now will gain a competitive edge by building adaptable, AI-ready teams. The next step is understanding how to implement GenAI effectively, from overcoming adoption barriers to change management — a topic we will explore in Part 2 of this series. Conclusion As organizations strive to keep pace with rapid technological advancements, the limitations of current strategies to address the IT skills gap become increasingly apparent. While current strategies address parts of the problem, they lack the scalability and foresight needed for long-term success. GenAI offers a unified solution that fills immediate gaps and sets the stage for a more resilient and innovative IT workforce. In Part 2, we’ll explore practical steps for CIOs to adopt GenAI,

It’s a particularly relevant question now, as governments consider more AI regulations, the courts deal with AI-related cases, and society grapples with the real-world sometimes tragic consequences of the technology. Sack says companies need to consider what ethical, legal, and compliance implications could arise from their AI strategies and use cases and address those earlier rather than later. “Ethical, legal, and compliance preparedness helps companies anticipate potential legal issues and ethical dilemmas, safeguarding the company against risks and reputational damage,” he says. “If ethical, legal, and compliance issues are unaddressed, CIOs should develop comprehensive policies and guidelines. Additionally, they should consult with legal experts to navigate regulations and establish oversight committees.” 9. What’s our risk tolerance, and what safeguards are necessary to ensure safe, secure, ethical use of AI? Manry says such questions are top of mind at her company. “At Vanguard, we are focused on ethical and responsible AI adoption through experimentation, training, and ideation,” she says. “Resulting from senior leader and crew [employee] perspectives, our primary generative AI experimentation thus far has focused on code creation, content creation, and searching and summarizing information.” She advises others to take a similar approach. “CIOs must assess risk tolerance and implement safeguards for generative AI to address safety, security, and ethical concerns. By establishing healthy safeguards like data protection protocols and ethical guardrails, CIOs ensure responsible AI use and minimize risks,” she says. “Establish an AI governance framework that defines the organizations risk tolerance, and patterns of acceptable use based on data sensitivity, allowing low risk generative AI use cases to be fast-tracked while applying more rigorous evaluation on higher-risk applications. “This approach enables teams to innovate safely and efficiently, while ensuring more rigorous safeguards for use cases involving sensitive data. By implementing robust security measures, bias mitigation techniques, and an ethical review process, CIOs can minimize risks and ensure responsible use of AI.” Not all organizations are there yet, though: Data governance research from Lumenalta, which delivers custom digital solutions, found that only 33% of organizations have implemented proactive risk management strategies for AI governance. 10. Am I engaging with the business to answer questions? CIOs shouldn’t be going it alone, says Sesh Iyer, managing director, senior partner and North America co-chair of BCG X, the tech build and design division of Boston Consulting Group. “CIOs must ask themselves whether they are engaging with the business to deliver value with generative AI, whether there is a clear focus on gen AI with a defined pathway to achieving a meaningful return on investments within 12 months, whether they are leveraging the power of the digital ecosystem to support their gen AI agendas, [and] whether they have a clear plan to extract and use data at scale to achieve these goals,” Iyer says. “These questions are crucial for CIOs to ensure they are delivering value, targeting spend effectively to achieve returns, and considering velocity-to-value — leveraging intellectual property and products from a broader ecosystem to reach value faster. Also, they must determine whether they have the ‘digital fuel’ (i.e., data and infrastructure) needed to achieve these AI-driven outcomes.” He advises CIOs to “sit down with the business to devise or refine an integrated ambition agenda” and “develop clear business cases that demonstrate returns within 12 months, establish a robust ecosystem strategy, and actively engage with partners to maximize value.” source

With rich resources like a growing physical infrastructure and subsea cable network, Africa is uniquely positioned to emerge as a leader among today’s developing economies. A key factor in this potential is the improvement of  internet connection in Africa, which is central to facilitating the continent’s digital transformation. The African Union commits to growing Africa’s already burgeoning digital economy through The Digital Transformation Strategy for Africa (2020-2030), stating: “Innovations and digitalization are stimulating job creation and contributing to addressing poverty, reducing inequality, facilitating the delivery of goods and services, and contributing to the achievement of Agenda 2063 and the Sustainable Development Goals”1 Additionally, the continent is young with a median age of 20 years, and experiencing population growth with its 1.4 billion inhabitants making up 15% of the global population. This bodes well for growth in market size, GDP, and a population of digitally fluent consumers. Public and private sector efforts to boost Africa’s digital economy Global public and private institutions recognize Africa’s position as an emerging digital economy on the world stage. For instance, the U.S., European Union (EU), China, and India all have strategic programs in place for a solid digital infrastructure on the African continent. The foreign direct investment (FDI) sector financed $30 billion in sustainability projects, often referred to as “global greenfield megaprojects,” according to the UN’s latest World Investment Report. Barriers to Africa’s digital transformation In the near term, Africa’s land-based (terrestrial) infrastructure can hinder the strides forward many see on the horizon for the continent. For data center capacity to spread to more regions of Africa, there will need to be a major effort to create structure for overland routes. Additionally, Africa needs 500,000 kilometers of fiber-optic cable construction to connect the continent, says the International Finance Corporation (IFC). For enterprises to leap over these boundaries, they need partners with knowledge, sophistication, and a keen understanding of how business works from both a continental and a regional perspective, such as those offering specialized services like colocation in Africa. The future of greater digital access to the African economy In this article, we’ll provide an overview of Digital Realty’s capabilities to connect enterprises to the opportunities on the African continent, touching on topics such as: The growth of the digital economy in Africa Africa’s digital infrastructure both now and in the future Digital Realty’s unique positioning as a digital transformation leader in Africa Potential challenges and opportunities for leading enterprises expanding to the African continent First, we will highlight interesting developments and results from efforts to provide greater digital access to the African economy. The growth of the digital economy in Africa Since 2020, the African Union (AU) has partnered with public and private institutions to fund its goal of uniting the continent through universal internet access. This attracted billions of dollars for digital infrastructure investments in Africa. Here’s a summary of the results so far as researched by the World Bank: 115% – Between 2016 and 2021 internet users increased by 115% in Sub-Saharan Africa 160 million – The number of Africans who gained broadband access between 2019 and 2022 191 million – New recipients or senders of digital payments between 2014 and 2022 The African Union enacted a 10-year strategy to enhance Africa’s digital economy in February 2020. The release of the Digital Transformation Strategy for Africa attracted financial support from the World Bank which set off a series of funding initiatives spanning the globe and the public and private sectors. Government investment leads to growth of Africa’s digital economy AU efforts lead to World Bank investment. One year after the AU’s digital transformation strategy, the World Bank launched the All Africa Digital Economy Moonshot. This initiative aims to “digitally connect every individual, business, and government in Africa by 2030.” Results: By January 2024, World Bank closed on $731.8 million in financial commitments across 11 digital transformation projects across Sub-Saharan Africa. The organization also secured $2.8 billion for 24 more digital development projects since 2014. The EU launched the EU-Africa Global Gateway Investment Package of €150 billion in investments. In addition to sustainability, climate resilience, and biodiversity projects, the Global Gateway aims to fast-track universal access to reliable internet in Africa by 2030. Progress: The Global Gateway project features the AU-EU Digital4Development (D4D) Hub, connecting North Africa to EU countries with an extension into West Africa via Dakar, Senegal. (European Commission) The U.S. launched the Digital Transformation with Africa Initiative (DTA) in December 2022, committing $800 million to the continent’s digital transformation journey. (Carnegie Endowment for International Peace) Results: In its first year, the DTA funded $82 million in four all-Africa initiatives and more than 20 regional projects focused on country-specific goals. (Carnegie Africa analysis) Of particular interest is the investment in: Digital trade alliances Funding infrastructure of information and communications technology (ICT) Feasibility studies to expand Internet access to rural parts of Africa These efforts have also led to a cascade of private investments from some of the world’s largest technology enterprises. Future impact of public and private digital infrastructure investment in Africa One purpose of these investments is to leverage Africa’s unique status as the fastest growing continent by population and gross domestic product (GDP), according to United Nations (UN) and African Development Bank figures. The ultimate payoff will be Africa’s contribution of $180 billion in GDP to the global economy by 2025 and a potential $712 billion by 2050. Leading enterprises know the time is now to partner with experts with an established presence in Africa’s digital infrastructure transformation. Digital infrastructure critical to Africa’s data sovereignty Currently, Africa represents two percent of the world’s data center footprint which greatly affects the continent’s data sovereignty efforts.2 The data regulations landscape on the continent remains fluid, but it’s also a top priority within established data economies in Africa. For example, in 2023 the Data Protection Act became law in Nigeria, which provides data protection guardrails that previously did not exist. Africa’s data center landscapeThis push for data sovereignty and more stringent data regulation calls for enterprises to establish partnerships with an experienced multi-tenant data center (MTDC) operator with a wide

00:00 Hello. Good afternoon and welcome to CIO Leadership Live. I’m Maryfran Johnson, CEO of Maryfran Johnson Media, and the former editor in chief of CIO magazine and events. Since November 2017this video show and audio podcast has been produced by the editors of cio.com and the digital media division of foundry, which is an IDG company. Our sponsor for this episode today is Ohio based Hyland Software, which provides industry leading enterprise content management and process management software. Hyland’s content solutions empower its customers to deliver exceptional experiences by connecting their systems and managing high volumes of diverse content that accelerates and automates processes and workflows. Visit the hyland.com website to learn more. And now onward to today’s guest, which I’m very pleased to say is the Senior Vice President and CIO at Hyland Software, Stephen Watt, Steve is responsible for the global delivery of corporate IT services for Highlands, rapidly expanding employee base now encompassing more than 3500 Highlanders around the world. He joined Highland 20 years ago as an is infrastructure administrator, back when the company had only 185employees and an IT team of six people as the business grew rapidly and expanded globally, Steve played key roles in the deployment of new technologies that supported the company’s explosive growth. He served in several key roles during his long tenure, much of that focused on infrastructure, systems, process and policy, and he was promoted into the CIO role, officially in early 2021 prior to Hyland, he worked as an IT director in the education industry and an independent IT consultant. Steve, welcome and thanks for joining me here today. Thank you very much. Maryfran, it’s a pleasure to be here. All right. Excellent. Now it is, as we talked about earlier, as we were getting ready for this show today. It’s really rare I went and I think I called you a unicorn, and because it’s rare to find a CIO who has such a long tenure with a single company, talk about what has kept you challenged and engaged at Hyland software all of these years.Yeah, for me, personally, it’s been, it’s been quite a journey.You know, when I was working in the IT field, especially as I was finishing school,you know, I was planning on a career in electrical engineering, and I happened to get in contact with what Hyland was, and really over this time,you know, it’s a couple of specific things for me, I was really interested in the IT front on a company that was sort of in that mid market, that was on a growth trajectory, You know, striving to become enterprise.And that was very that was very attractive. And then really, what’s kept me here is that with our growth and everything, there’s never been a, you know, a slowdown in the number of challenges that we’ve had to solve. And I love solving interesting problems. And then the cliche answer of it is that I’ve truly enjoyed the people that I’ve worked with over this amount of time. I think we’ve all had those jobs where we worked with people that we did not enjoy, the people that you were working with on a day to day basis, but Highland, I think, has had a unique position to attract great people that I’ve really had an honor working with, and, you know, being a part of that journey with them. So that has been a big part of it, as well as just the pleasure I’ve had with my colleagues and, you know, solving big problems together is a great way to spend your time. Well, tell us too, a little bit about Hyland’s market, the people that buy the Hyland software that has expanded over time as well. Tell us a little bit about that customer base out there that has part of that explosive growth?Yeah, definitely. We sell into almost any vertical market that you can think of, whether it’s healthcare, financial services, commercial manufacturing. Our software is pretty ubiquitous in its application, and that’s just, you know, a lot of it is due to the configurability and the in the, you know, the number of solutions that we can offer our customers today, that is that has been exciting. Our customer base has continued to grow significantly since I’ve been with the organization. And it’s been interesting to see how that, how that presents itself comes with its own unique challenges as you enter into like highly regulated markets like health care or financialbut again, it’s it’s fun to solve those interesting challenges. So yeah, and around the world at this point, you’ve got somewhere around 15,000 customers. That is correct. Yeah, around 15,000 customers across two.Pretty much every vertical market you can think of. Okay, now let’s talk about the size and scope of your technology team. Those six people that you started out with back 20 years ago is now about the size that the entire company was when you joined. It’s a upwards of 170 folks in it now. Yes, that is correct, yeah. So that’s been kind of a surreal experience of itself, and that growth of seeing that when you’re running a department that’s the same size as the entire organization was, kind of puts in perspective, you know, what the stakes are, and the fact that you shoulder a lot of responsibility to help the organization continue to move in the right direction, yeah. How have you, how have you structured that technology team to deliver the most value to the rest of the business? And I take it that’s changed a great deal over the 20 years. So what is your most kind of, the most recent snapshot of what your org structure looks like for the technology group? Yeah, you know, the way that we’re structured now is, is, it’s definitely not a unique perspective on on what we do, but we try to organize in sort of

“More so than any previous platform shift, every layer of the application stack will be impacted. It’s akin to GUI, internet servers, and cloud-native databases all being introduced into the app stack simultaneously. Thirty years of change is being compressed into three years,” Nadella said. “This is leading to a new AI-first app stack — one with new UI/UX [user interface/user experience] patterns, runtimes to build with agents, orchestrate multiple agents, and a reimagined management and observability layer. In this world, Azure must become the infrastructure for AI, while we build our AI platform and developer tools — spanning Azure AI Foundry, GitHub, and VS Code — on top of it.” Info-Tech’s Brunet said part of the challenge with Microsoft is that they offer so many different options, many overlapping, that “it can feel like a very fragmented offering that can be very confusing. They are trying to make their infrastructure and offerings feel less fragmented.” He said that he sees this as Microsoft’s way of leveraging the Azure cloud “to make it easier to stitch their pieces together.” source

As IT professionals and business decision-makers, we’ve routinely used the term “digital transformation” for well over a decade now to describe a portfolio of enterprise initiatives that somehow magically enable strategic business capabilities. Ultimately, the intent, however, is generally at odds with measurably useful outcomes. Transformation initiatives usually defy gravity in terms of what is practical and realistic for modern enterprises with legacy applications and infrastructure, yet we persist in funding them on a large scale and positioning them as value and outcome-driven   When we consider the implications of fixed infrastructure costs and capex investments, efforts like cloud migration, enterprise data platforms, robotic process automation (RPA), and API-first initiatives presented an almost irresistible opportunity to enable and unlock business capabilities and value. What we consistently overlooked were the direct and indirect consequences of disruption to business continuity, the challenges of acquisitions and divestitures, the demands of integration and interoperability for large enterprises and, most of all, the unimpressive track record for most enterprise transformation efforts. The scorecard speaks for itself. A study by McKinsey found that less than 30% of digital transformation initiatives are successful in achieving their objectives. For large enterprises, the success rate is even lower, with estimates hovering around 16-20% due to the scale and complexity of the initiatives.  The API-first era  In 2012, as a software architect in a global sportswear and apparel enterprise, it became clear to me during the API-first era that transformation was no longer a matter of lofty ambitions that included monolithic service bus implementations, refactoring, reverse engineering or re-engineering in-house applications along with infrastructure modernization. Later, as an enterprise architect in consumer-packaged goods, I could no longer realistically contemplate a world where IT could execute mass application portfolio migrations from data centers to cloud and SaaS-based applications and survive the cost, risk and time-to-market implications. Our commitments to the businesses we supported as architects were perpetually at odds with reality. A tectonic shift was moving us all from monolithic architectures to self-service models and an existential crisis for architecture and IT was upon us.    source

A recent report from the Ministry of Communications and Information Technology, King Abdullah University of Science and Technology, and consultancy firm Hello Tomorrow highlights the rapid growth of deep tech startups in Saudi Arabia, with 50% of these startups focusing on AI and IoT. These sectors are emerging as key drivers of innovation and investment in the Kingdom, with over 43 high-growth startups collectively raising more than 987 USD in funding. Saudi Arabia has become one of the leading ecosystems for tech startups in the Middle East and North Africa , ranking among the top three for funding and deal activity. This success is a testament to the growing availability of venture capital, a dynamic entrepreneurial ecosystem, and government support for innovation-driven ventures. The deep tech sector, while still in its early stages, is drawing significant attention from international companies and investors, eager to tap into the country’s potential for technological advancement. The surge in AI and IoT-focused startups is directly aligned with the objectives of Saudi Vision 2030, a strategic framework designed to diversify the Kingdom’s economy and reduce its reliance on oil revenues. Vision 2030 aims to foster a knowledge-based economy and establish Saudi Arabia as a global leader in technology and innovation. The deep tech sector plays a crucial role in achieving this vision, positioning AI and IoT at the forefront of the Kingdom’s digital transformation. source