Noha Gad

Saudi Arabia’s event management industry is experiencing a period of remarkable growth, driven by Vision 2030’s agenda and its ambition to transform the Kingdom into a leading global destination for business, culture, entertainment, and sport. Analysts believe the growth in the event management market is largely attributed to substantial investments in venues and groundbreaking infrastructure.

According to a recent report released by Research and Markets, the event management market in Saudi Arabia is expected to grow from $2.59 billion in 2025 to reach $3.92 billion by 2031, making a compound annual growth rate (CAGR) of 7.14%. In addition, the IMARC Group estimated the market to reach $21.1 billion by 2034, exhibiting a CAGR of 8.08% between 2026 and 2034. This growth, the group said, is driven by rising tourism, government initiatives, increased corporate spending, and growing demand for entertainment and cultural experiences, as well as developments in event technology and social media integration.

The growing role of technology in shaping the Saudi event management industry encouraged organizers and emerging companies to use digital tools to improve planning, communication, guest management, and post-event analysis, thereby delivering larger, safer, and more personalized experiences.

Artificial intelligence (AI) is a key tool organizers and event management companies use to understand attendee preferences, recommend relevant sessions or exhibitors, answer guest questions through chatbots, and translate content for international audiences.

Data analytics is another driver behind the transformation that the event management market is witnessing. It helps organizers and event-tech companies to benefit from digital registration systems, mobile applications, and smart badges to collect information about attendance, movement, engagement, and feedback. Analyzing these data responsibly could help organizers measure the success of an event more accurately and improve future editions. Sponsors and exhibitors can also understand audience behavior, generate qualified leads, and demonstrate return on investment.

Automation is another tool that simplifies many routine tasks that previously required significant manual work, such as sending invitations, registration confirmations, reminders, check-in processes, surveys, and post-event reports. This will reduce administrative burdens, lower the risk of human error, and allow event managers to focus more on creativity, guest experience, and strategic planning.

Also, augmented reality (AR), virtual reality (VR), interactive screens, and holographic displays can make exhibitions, brand activations, and entertainment events more engaging.

Together, these advanced technologies are not replacing event managers; they are redefining their role. The most successful companies in Saudi Arabia’s event management market will be those combining strong local knowledge and operational expertise with digital tools that create smarter, safer, and more memorable experiences.

The event-management sector is no longer dominated solely by traditional agencies and venue operators. A layered ecosystem has emerged, spanning full-service event agencies, specialized production and AV companies, venue-management companies, ticketing platforms, and a growing cohort of event-tech startups. 

Companies such as SYNC, one of the leading event solutions providers, position themselves as end-to-end event solutions providers, handling everything from Saudi Conventions and Exhibitions General Authority (SCEGA) licensing and venue coordination to AV production and on-site execution. Serving government entities, corporate clients, and conference organizers, the competitive advantage of these companies lies in regulatory familiarity, supplier networks, and in-house production capability rather than software innovation.

In the AV and staging area, Al-Khalediya for Theatres and Cinema is one of the key players that has executed more than 1,000 projects across Saudi Arabia and the GCC, specializing in theatre design, acoustic systems, seating, and cinema fit-outs.

Hybrid-event and event-tech providers, such as INVE, do not execute events themselves, but provide software that organizers use to manage invitations, registration, guest data, and entry.

INVE is one of the Saudi-based startups that leverage technology to transform the event management industry in the Kingdom by offering digital invitations, RSVP tracking, guest profiles, registration, check-in, and follow-up communication in one platform. Serving both corporates and individuals, INVE reflects the industry’s move toward relationship-based and technology-enabled event management, seeking to turn a single event into a long-term guest-relationship asset.

Venttat is a leading Saudi event management company, offering expert services for organizers and exhibitors. It serves as a one-stop shop for corporate events, meetups, conferences, and global event technology services, exhibitor infrastructure, and digital logistics.

The growing event management market in Saudi Arabia is providing significant opportunities for investors, startups, and established companies, as the Kingdom hosts more international conferences, entertainment events, sporting competitions, and cultural festivals. This increases demand not only for event managers and organizers but also for the technology, services, and infrastructure that support them.

Startups and event planning companies will need to tailor AI-powered solutions and products for attendance forecasting, personalized recommendations, attendee matchmaking, chatbots, feedback analysis, and automated content creation. Smart venue technology presents significant opportunities as startups can focus on developing digital access control, crowd monitoring, security systems, digital signage, and real-time venue-management dashboards.

Despite its strong growth potential, the event management industry in Saudi Arabia faces several challenges that could affect its long-term development. One of these challenges is the scarcity of specialized talent, particularly in areas such as event production, technical operations, digital marketing, data analysis, and multilingual guest services. 

The growing number of event agencies, venues, and technology providers is increasing pressure on companies, which will need to differentiate themselves through quality, creativity, reliability, and strong client relationships rather than competing solely on cost.

Quality and consistency are another challenge, especially as Saudi Arabia seeks to host world-class events. Thus, organizers must meet high expectations for safety, logistics, guest experience, and operational precision. 

To sum up, Saudi Arabia’s event management industry is entering a new phase of development, driven by Vision 2030, major technological advancements, and the Kingdom’s growing position as a regional hub for business, culture, and entertainment.

Technology will be central to this growth, helping event organizers and managers change how they plan, deliver, and measure events, ultimately enabling them to focus on creativity, guest experience, safety, and strategic decision-making. Companies that can combine operational expertise with digital innovation will be best placed to meet the rising expectations of corporate clients, government entities, sponsors, and attendees.

Noha Gad

Have you ever dealt with the manager who asks you to Cc them on every email? The one who rewrites your work not because it is wrong, but because it is not exactly how they would have done it. They think they are protecting quality, meeting deadlines, and ensuring good results by focusing on minor details, demanding approval for small decisions, and leaving employees with little freedom to make their own choices.

A micromanager excessively supervises employees, focusing on controlling every task detail. Although this management style might yield short-term results, it often undermines morale and hampers team productivity in the long run. Instead of directing employees on how and when tasks can be accomplished, micromanagers watch employees’ actions closely, providing frequent criticism.

Key features of micromanagers

Micromanagers share several common behaviors. Although every situation is different, these signs usually appear:

• Lack of trust and delegation. These managers refuse to delegate tasks or take over work because they believe no one else can accomplish it right.
• Continuous supervision. Micromanagers demand frequent status updates, require approval for minor decisions, and track every step of a project.
• Excessive focus on minor details: They obsess over formatting, wording, or trivial errors instead of looking at overall progress. They may criticize a report because of its font or structure, even when the content is strong and the client is satisfied.
• CC'ing on everything: They insist on being copied on all emails and sitting in on routine communications. This makes employees feel unable to act without asking permission first.

Negative impact on the workplace

Micromanagement may seem like a way to maintain control and quality, but it often creates serious problems for employees and the wider business, such as: 

• Reducing employee morale. When employees feel constantly observed and corrected, they start losing enthusiasm for their work. They may feel that their manager does not trust their skills or respect their judgment.
• Increasing stress. Frequent check-ins, repeated revisions, and constant approval requirements can make employees feel pressured and insecure. They may worry about making mistakes or being criticized for small details.
• Lowering confidence. When a manager rewrites employees’ work, questions their choices, or takes over tasks, they may begin to doubt their own abilities.
• Discouraging creativity and new ideas. Micromanagers often prefer their own method, leaving little room for different approaches. This makes employees less likely to share ideas when they believe every suggestion will be rejected or changed. 
• Slowing down the work cycle. When every small decision needs approval, projects take longer to be done, as employees may spend more time waiting for feedback than doing actual work.
• Reducing productivity.  Although micromanagers often believe they are improving performance, their behavior can have the opposite effect. Employees may lose motivation to work efficiently because they know their manager will likely change the work anyway.

Micromanagers can take concrete steps to change their management. First, they should establish a few key metrics that define success for any project, ignoring every other detail that falls outside those parameters. They should delegate specific needs to be done, not control the way team members do it. An open-door policy should be in place so team members can seek coaching or further guidance whenever they feel they need it. Finally, managers should set a deadline for each stage of an assigned project.

To sum up, micromanagement may seem to be a commitment to quality, but it often creates stress, lowers morale, and reduces productivity. When employees feel constantly monitored and are given little freedom to make decisions, they may lose confidence, avoid sharing ideas, and become less engaged in their work. Successful leaders focus on clear goals, trust their teams, delegate responsibility, and provide guidance when needed.

Ghada Ismail

As artificial intelligence continues to reshape education, edtech startups are exploring new ways to personalize learning, improve student performance, and support teachers with data-driven insights. AILA is among the companies working to transform the learning experience through AI-powered solutions tailored to students’ individual needs and the Saudi education system. In this interview with Sharikat Mubasher, AILA discusses its approach to personalized learning, the challenges of developing effective AI-driven educational tools, and the opportunities for edtech startups as Saudi Arabia advances its education and digital transformation goals.

AILA has recently secured a $3 million funding round. What does this investment enable the company to do that it could not do before?

Our earlier funding helped us build the product and reach product-market fit. We now have schools using AILA every day and results we can stand behind. This round is about scaling what already works. 

First, it lets us go deeper on our adaptive engine and our research. We want to keep proving, with rigorous evidence, that AILA improves how students learn, building on the work we have done with King Fahd University of Petroleum & Minerals. 

Second, it lets us scale our commercial and customer success teams so we can serve many more schools across the Kingdom, and support each one properly after launch. 

Third, it lets us expand beyond the Saudi curriculum. Today we are strongest around Qudurat, Tahsili and NAFES. By adding other curricula, we can take the same engine to new markets and serve many more students. 

Do you expect this round to take AILA to profitability, or is the priority still aggressive growth and market expansion? 

Our priority is growth, but disciplined growth. We have built a business with strong fundamentals, and our product runs at a gross margin of around 67%, which gives us a lot of room to grow efficiently. 

Reaching profitability is a clear goal for this round. We want to scale to more schools and new markets while becoming profitable, so that we go into our Series A from a position of strength. We are not buying growth at any cost. Every school we sign needs to make sense on its own. 

AILA describes its approach as personalized, AI-powered learning. What makes your personalization technology different from the growing number of AI tutoring and edtech platforms entering the market? 

Many new AI platforms are essentially content generators: you ask a question, you get an answer. That is useful, but it is not the same as teaching. AILA is built around diagnosis. We work out exactly where each student is, what they have mastered and what is holding them back, and then we guide them on the shortest path to improvement. 

Three things set us apart. First, we are built for the Saudi context, mapped to national learning outcomes and assessments such as Qudurat, Tahsili and NAFES, and available in both Arabic and English. Second, we work inside schools, so the insight does not stay with the student. Teachers, administrators and principals see the same picture and can act on it. Third, we measure results. Our benchmark shows students learning about 2.3 times more efficiently, and our pilot results have been validated through a research partnership with King Fahd University of Petroleum & Minerals. 

How does AILA use student data and learning behavior to determine what a student should learn next? 

Every interaction on the platform tells us something: whether the answer was right, how long it took, how many attempts were needed, and what kind of mistake was made. We map all of that to a structure of skills and learning outcomes, so we can estimate each student's level of mastery skill by skill. 

From there, the engine decides what comes next. It looks at the gaps that matter most, the prerequisite skills that need to be secured first, and how heavily each skill counts in the assessment the student is preparing for. It also brings back earlier material at the right moment, so learning sticks rather than fading. 

The same data flows to teachers and school leaders as clear, actionable reports, so they know which students need help and on what. 

What are the biggest technical challenges in building AI systems that can genuinely improve learning outcomes rather than simply generate educational content? 

The hardest part is measuring learning rather than activity. It is easy to build something students click on a lot. It is much harder to prove they actually know more afterwards. That is why we invest in validation and research, not just in features. 

The second challenge is quality and alignment. Content must be accurate, pedagogically sound and aligned with the Saudi curriculum, in both Arabic and English. Generative AI can produce a lot very quickly, but in education a confident wrong answer does real damage, so we keep strong quality control around everything the system shows a student. 

The third is getting the recommendation right from limited data, especially when a student is new to the platform, and keeping it right as they progress. 

And finally, the system has to fit how schools actually work. AI does not replace the teacher. It has to give teachers and school leaders insight they can act on in the time they have. 

What gaps in the Saudi education system did you identify when you first built AILA, and how have those needs evolved since the company launched? 

When we started, the biggest gap was that one classroom holds students at very different levels, yet they are largely taught the same way at the same pace. Teachers knew some students were falling behind, but they did not have the time or the granular data to know exactly why. At the same time, national assessments carry high stakes for students, and much of the targeted preparation was happening outside school. 

We built AILA to bring that personalized, data-driven support inside the school, where every student can access it. 

At the same time, AI itself has advanced enormously since we launched. Models today understand language, reasoning and student errors far better than they did a few years ago, in Arabic as well as English. That has let us do much more than we originally planned: sharper diagnosis, richer and more personal feedback, and a far better experience for students and teachers. Our offering today is stronger than what we could have built at the start. 

The need has also matured. Schools are no longer only asking how to prepare students for an exam. They want continuous visibility on learning outcomes across the year, aligned with national standards, so leaders can make decisions based on evidence. That shift, driven by Vision 2030 and the Human Capability Development Program, has shaped how our platform has grown. 

Saudi Arabia is investing heavily in education technology as part of its broader digital transformation. Where do you see the biggest untapped opportunities for Saudi edtech startups? 

I see three big opportunities. The first is assessment and learning analytics. The Kingdom has clear national learning outcomes, and there is huge value in tools that show schools, in real time, where students stand against them. 

The second is scale in the public sector. Private schools have moved fast, but the largest impact will come from solutions that work reliably across government schools, at national scale. 

The third is high-quality AI built for our own context. Global tools are not designed around Saudi curricula, assessments, and classroom realities. Startups that build for this market from the ground up, in both Arabic and English, have a real advantage. 

More broadly, anything that connects learning in school to what comes next, university and the job market, is still underserved. 

Looking three years ahead, what would success look like for AILA in terms of users, markets, and impact? 

Today we work with around 100 schools and roughly 65,000 students. In three years, success means having a proven adaptive engine, backed by published research, used by 300,000 students. 

On markets, Saudi Arabia will remain our home and our largest market, and we plan to extend across the GCC and the wider MENA region, supported by the new curricula we are adding. 

But the number that matters most is impact. We want to show, with independent evidence, that students on AILA achieve measurably better learning outcomes, and that schools using AILA make better decisions because of the data we give them. If we can prove that at scale, the growth will follow. 

Ghada Ismail

Finding the right investment opportunity is a crucial step toward achieving strong returns. Before investors evaluate valuations, conduct due diligence, or negotiate terms, they must identify businesses and assets that fit their objectives. This process, known as deal sourcing, plays a central role in private equity, venture capital, and mergers and acquisitions (M&A).

What Is Deal Sourcing?

Deal sourcing is the process of identifying and establishing contact with potential investment opportunities. These may include startups seeking funding, established businesses looking for investors, or companies available for acquisition.

Investors use market research, professional networks, referrals, direct outreach, and financial intermediaries to build a pipeline of potential deals. Effective sourcing focuses not only on finding opportunities but also on identifying businesses that match an investor’s sector preferences, budget, risk tolerance, and expected returns.

Two common approaches are proprietary and intermediated deal sourcing.

What Is Proprietary Deal Sourcing?

Proprietary deal sourcing involves identifying opportunities through an investor’s own research, relationships, and direct outreach rather than relying primarily on formal intermediaries or widely marketed transactions.

For example, a private equity firm may approach a business owner directly to explore an acquisition before the company is formally put up for sale. Investors can develop such opportunities through industry events, founder networks, referrals, and targeted research.

The main advantage is the potential for less competition, giving investors more time to build relationships and negotiate terms. Early engagement can also help investors understand a business before a formal transaction begins.

However, proprietary sourcing requires considerable time, research, and relationship-building. It does not guarantee exclusivity, lower valuations, or a successful transaction.

What Is Intermediated Deal Sourcing?

Intermediated deal sourcing involves accessing investment opportunities through third parties, such as investment banks, M&A advisers, business brokers, and other professional networks.

For example, a company planning to sell may appoint an investment bank to identify potential buyers and coordinate the bidding process. Interested investors receive information about the business and can assess whether it fits their investment strategy.

This approach can provide access to a broader range of opportunities and streamline the initial screening process. However, competitive bidding may push valuations higher, while intermediary fees can increase transaction costs. Investors may also face tighter timelines when evaluating deals.

Proprietary vs. Intermediated Deal Sourcing

The key difference lies in how investors access opportunities and the level of competition involved.

Proprietary sourcing emphasizes direct relationships and targeted outreach. It may provide earlier access and less competition but requires sustained effort to build a reliable pipeline.

Intermediated sourcing uses established professional channels to connect investors with potential transactions. It can improve access to available deals and simplify the sourcing process, although competition and fees may be higher.

Neither approach guarantees better investment outcomes. Success ultimately depends on the quality of the opportunity, due diligence, valuation, and negotiated terms.

Which Strategy Is Better?

For many investors, combining both approaches offers the greatest flexibility. Proprietary sourcing helps uncover opportunities and establish long-term relationships, while intermediated sourcing provides access to businesses already seeking investment or considering a sale.

The right balance depends on the investor’s objectives, resources, target market, and investment stage. Ultimately, successful deal sourcing is not about finding the most opportunities, but about identifying the right investments and building relationships that lead to sustainable value creation.

Noha Gad 

Artificial intelligence (AI) is no longer a tool for improving products and services; it has become a strategic asset that shapes economic competitiveness, national security, and digital independence. As governments and enterprises increasingly rely on AI for critical decision-making, questions are emerging about who controls the data, infrastructure, models, and rules behind these systems.

As AI deployment is accelerating worldwide, countries have concerns about their ability to build and run AI systems independently without the need for foreign technology providers, while maintaining the highest levels of security and privacy with regard to data, technology infrastructure, operations, and legal structures. This has brought sovereign AI to the center of global technology and policy debates.

What is meant by sovereign AI?

Sovereign AI refers to AI systems developed, deployed, and governed within a nation's legal and operational boundaries to ensure data and jurisdictional control. It helps governments and organizations address issues related to control, governance, and dependence. 

The difference between sovereign AI and global AI models lies in where the data resides and who holds the legal authority over the system. For Jurisdictional control, sovereign AI ensures that all data and operations remain under the legal authority of a specific country or region, perhaps within a sovereign cloud. Meanwhile, global AI models often operate on international cloud platforms where data may move across borders 

For data movement and privacy, sovereign AI restricts data movement, ensuring that sensitive information never leaves the local jurisdiction, unlike global AI models that use users' data to improve a centralized, multi-tenant model governed by a provider’s terms of service.

For alignment and autonomy, sovereign AI helps create models that are natively aligned with local dialects, legal codes, and social norms. In contrast, global models may reflect the cultural or linguistic biases of the region where they were developed. 

Types of sovereign AI deployment models

Sovereign AI is not a single architecture, but rather a spectrum of control based on data sensitivity, regulatory requirements, cost, scalability, and the need for operational control.

• Full sovereignty: This model hosts data, models, infrastructure, and personnel all within national borders, utilizing a domestic supply chain for hardware and software wherever possible.
• Hybrid sovereignty: Sensitive workloads remain on domestic, sovereign infrastructure, while non-sensitive tasks are offloaded to global platforms to take advantage of scale.
• Regional or bloc sovereignty: Sovereignty is defined at the level of a political alliance, such as the European Union, allowing for cross-border data flows within the member states while preserving regional legal control.
• Sector-specific sovereignty: Sovereignty requirements are applied only to critical industries like defense, healthcare, or finance, while other sectors continue to use global AI services.

Pros and Cons

Implementing a sovereign AI strategy provides the regulatory assurance and strategic control necessary for high-stakes environments. Other advantages include:

• Enhanced regulatory compliance: Systems adhere to national data protection laws from the point of deployment, reducing the risk of legal penalties.
• Greater data control: Sensitive government, financial, healthcare, and business data remain under local jurisdiction, with clear rules for storage, access, processing, and deletion.
• Data and intellectual property protection: Sensitive data and proprietary models are stored in isolated, controlled environments to prevent data leaks and model theft.
• Operational resilience: Local, hybrid, or disconnected deployment can reduce reliance on a single external provider and support continuity for critical services.
• Operational continuity: Localized infrastructure ensures that critical national and corporate services remain online regardless of international geopolitical events or trade restrictions.

Building and operating sovereign AI capabilities also involves high costs, talent constraints, and continued dependence on global supply chains. Key disadvantages are:

• High infrastructure and legal costs: Building local compute clusters and navigating complex, often conflicting regional regulations requires massive upfront capital investment.
• Talent shortage: There is a global shortage of AI engineers, data scientists, cybersecurity specialists, and infrastructure professionals required to build and maintain complex sovereign environments.
• Hardware dependence: Even with local infrastructure, many countries remain dependent on global supply chains for advanced chips, GPUs, and specialized components.
• Data lineage and provenance: Maintaining a verifiable, auditable record of where training data originated is essential for proving compliance with local privacy and copyright laws.