Artificial Intelligence Appreciation Day: How Saudi Arabia Turned AI into a National Mission

Jul 15, 2026

Ghada Ismail

 

A decade ago, artificial intelligence was largely viewed as a futuristic technology discussed in research laboratories and Silicon Valley boardrooms. Today, it writes code, detects diseases, powers government services, personalizes shopping experiences, and helps businesses make decisions in seconds. AI has rapidly evolved from a niche innovation into a transformative force that is reshaping industries and economies across the globe.

Every year on 16 July, Artificial Intelligence Appreciation Day celebrates these technological advances and the people driving them forward. Yet for Saudi Arabia, the occasion represents something even more significant. It is an opportunity to reflect on how artificial intelligence has become a central pillar of the Kingdom's economic transformation, driving innovation, attracting global investment, and creating entirely new industries under Vision 2030.

Rather than simply adopting AI technologies developed elsewhere, Saudi Arabia has pursued a far more ambitious goal: building an ecosystem where artificial intelligence can be developed, governed and commercialized at scale. In just a few years, the Kingdom has laid the foundations for an AI-powered economy through national strategies, digital infrastructure, talent development and partnerships with some of the world's leading technology companies.

 

From Vision 2030 to an AI Economy

Saudi Arabia's AI ambitions are rooted in Vision 2030, the national blueprint launched to diversify the economy beyond oil and position innovation at the heart of future growth. While digital transformation has long been a priority, artificial intelligence has evolved into one of the Kingdom's most strategic investments, underpinning everything from government services and healthcare to finance, manufacturing, and education.

A defining milestone came in 2019 with the establishment of the Saudi Data and Artificial Intelligence Authority (SDAIA), which was tasked with leading the Kingdom's AI and data agenda. The following year, the launch of the National Strategy for Data and AI (NSDAI) provided a comprehensive roadmap for developing AI capabilities, attracting investment, fostering innovation and creating a globally competitive digital economy.

Since then, Saudi Arabia has consistently demonstrated that AI is not merely a technology initiative but a national development strategy. The Kingdom has introduced policies to encourage innovation, developed governance frameworks for the responsible use of AI and invested heavily in the digital infrastructure needed to support increasingly sophisticated technologies.

This long-term commitment has translated into measurable international recognition. Saudi Arabia ranked first globally in the Government Strategy pillar of Tortoise Media's Global AI Index, an assessment that measures the strength of national AI policies, governance structures, public investment, and implementation. The ranking reflects more than ambitious targets. It recognizes the Kingdom's establishment of SDAIA, the rollout of the National Strategy for Data and AI, dedicated AI governance frameworks, sustained investment in digital infrastructure, and coordinated efforts to embed AI across government and industry. Together, these initiatives have positioned Saudi Arabia among the world's most proactive governments in developing a national AI ecosystem.

 

Saudi Arabia's AI by the Numbers

The scale of Saudi Arabia's ambitions is reflected in both its investments and expected economic impact. According to PwC, artificial intelligence is projected to contribute US$135.2 billion to the Kingdom's economy by 2030, equivalent to approximately 12.4% of GDP, making it the highest projected AI-driven economic contribution among Middle Eastern economies and one of the highest globally. Since establishing the Saudi Data and Artificial Intelligence Authority (SDAIA) in 2019, the Kingdom has launched the National Strategy for Data and AI (NSDAI), introduced the Arabic large language model ALLAM, established HUMAIN to accelerate AI infrastructure and innovation, and expanded AI applications across healthcare, finance, education, logistics, manufacturing, and government services. Alongside these initiatives, Saudi Arabia has introduced AI ethics principles and governance frameworks, demonstrating that its AI agenda extends well beyond technology adoption to encompass policy, talent development, infrastructure, and long-term economic transformation.

 

Saudi Startups Are Driving the Next Wave

Government initiatives may have laid the foundation, but Saudi Arabia's startup ecosystem is increasingly becoming one of the strongest drivers of AI innovation.

A growing number of startups are demonstrating that the Kingdom is moving beyond AI adoption to AI creation. Rather than simply integrating off-the-shelf technologies, these companies are developing solutions tailored to regional markets and real business challenges.

Mozn has emerged as one of Saudi Arabia's leading AI companies, using machine learning to combat financial crime, strengthen compliance and support smarter risk management for financial institutions. Lucidya has built one of the region's most advanced AI-powered customer intelligence platforms, helping businesses analyze Arabic-language conversations across social media and digital channels to better understand consumer behavior.

Meanwhile, Intelmatix is applying artificial intelligence to enterprise decision-making, enabling organizations to optimize operations and improve strategic planning through predictive analytics. Companies such as Salla and Zid are also embedding AI into e-commerce platforms, while startups across healthcare, logistics, cybersecurity and retail continue introducing AI-powered products designed specifically for regional markets.

 

The Next Frontier Is Trust

As artificial intelligence becomes increasingly sophisticated, experts believe the next stage of AI adoption will depend less on algorithms themselves and more on the quality, security, and resilience of the data that powers them.

According to Tim Pfaelzer, Senior Vice President and General Manager for EMEA at Veeam, organizations are entering what he describes as the "agentic era," where AI systems are evolving beyond simple assistants into autonomous digital workers capable of making decisions and performing tasks with minimal human intervention.

"AI is revolutionizing how organizations unlock value from their data, providing instantaneous insights and uncovering opportunities that were previously out of reach," Pfaelzer says.

He believes this shift is fundamentally changing how businesses operate.

"These agents are becoming autonomous, 24/7 digital workforces, scaling productivity and accelerating decision-making."

The scale of investment reflects this growing confidence. According to Pfaelzer, hyperscale technology companies have collectively invested more than US$650 billion to build the infrastructure supporting the next generation of AI innovation. At the enterprise level, adoption is accelerating rapidly, with 88% of organizations already piloting AI agents across their technology environments.

Yet despite this enthusiasm, readiness remains a significant challenge.

According to Veeam's research, only around 7% of organizations currently possess the foundational capabilities required to be genuinely AI-ready.

For Pfaelzer, the problem is not artificial intelligence itself—it is the quality of the data feeding these systems.

"The lack of visibility into data can cause AI models and agents to act on incomplete, outdated or inaccurate information, leading to unreliable outcomes at machine speed."

To address this challenge, Pfaelzer argues that organizations must establish what he describes as a "trust layer" built on complete data visibility, governance and resilience.

"By ensuring AI agents are powered by secure, accurate and readily recoverable data, businesses can unlock AI's full potential without allowing it to become their Achilles' heel."

For Saudi Arabia, this approach aligns closely with its broader AI strategy, which emphasizes responsible innovation alongside rapid technological advancement. As the Kingdom continues expanding AI adoption, building trustworthy and resilient data ecosystems may prove just as important as developing increasingly powerful AI models.

 

Celebrating Progress While Preparing for the Future

Artificial Intelligence Appreciation Day is often viewed as a celebration of technological breakthroughs. Saudi Arabia's story offers a broader and more compelling perspective.

The Kingdom's AI journey demonstrates that meaningful progress requires far more than sophisticated algorithms or headline-grabbing investments. It depends on long-term national planning, modern digital infrastructure, responsible governance, strategic partnerships and, above all, people capable of transforming innovation into real economic and social value.

Over the past several years, Saudi Arabia has methodically laid these foundations. Through Vision 2030, it has established national AI strategies, built world-class infrastructure, nurtured a vibrant startup ecosystem, attracted global technology leaders and accelerated AI adoption across sectors that directly affect the lives of millions of people.

The next phase of this journey will likely be defined not by the size of AI models or the speed of technological breakthroughs, but by how effectively artificial intelligence improves productivity, enhances public services, empowers businesses, and creates sustainable economic growth.

As the world marks Artificial Intelligence Appreciation Day, Saudi Arabia is celebrating more than the rise of a transformative technology. It is celebrating the emergence of an AI ecosystem built with a long-term vision; one that is positioning the Kingdom not simply to participate in the global AI revolution, but to help shape its future.

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Beyond the peak: How high-water marks keep performance fees fair

Noha Gad

 

In the investment management world, it is common for fund managers to earn a performance fee when they generate strong profits for their clients, but this arrangement can create an unfair situation if those gains are later lost and then partially recovered. Without additional safeguards, a manager could collect a performance fee during a good year, see the portfolio value drop sharply in the following year, and then earn another performance fee simply by bringing the fund back to its earlier level even though investors have not truly benefited from any new gains.

The high-water mark is a widely used rule in hedge funds and other managed investment products that prevents this outcome by linking performance fees to real, additional value creation rather than temporary swings in portfolio value. This rule sets the highest value that the fund has ever reached as a benchmark, allowing managers to charge a performance fee only on profits that rise above that previous peak.

 

What is meant by a high-water mark?

This term refers to the highest level that a body of water reaches, but metaphorically, it refers to the peak value of an investment fund or the highest point of achievement.

In the business realm, the high-water mark is a benchmark investment funds use to ensure investors only pay performance fees when a fund’s value reaches a new peak. It ensures that investors do not have to pay performance fees for poor performance, but, more importantly, guarantees that investors do not pay performance-based fees twice for the same amount of performance.

For asset management companies, including a high-water mark in their fee structure can be a strong signal of fairness and alignment with investors, ultimately contributing to attracting and retaining capital in a competitive market.

From a managerial perspective, the high-water mark encourages a focus on sustainable, long-term performance rather than short-term increases that might be followed by sharp declines. As performance fees are only available after the fund exceeds its highest historical value, managers have a clear incentive to avoid strategies that generate volatile returns with large drawdowns.

 

Why do high-water marks matter?

High-water marks are widely viewed as a key investor protection in hedge funds and other performance-fee-based investment structures, and they bring several clear advantages for both investors and fund managers. This includes:

  • Protecting investors from paying twice for the same gains.
  • Aligning manager incentives with genuine outperformance.
  • Promoting more disciplined risk management.
  • Supporting long-term thinking over short-term spikes.
  • Enhancing trust and credibility with investors.
  • Encouraging clearer communication about performance.

 

In conclusion, the high-water mark is more than a technical fee detail; it is a core element of fair and transparent performance-based compensation in investment management. Setting the fund’s highest historical value as the threshold for performance fees ensures that managers are rewarded only for creating new gains, not for recovering past losses or simply returning to earlier levels.

For investors, this structure provides a clear safeguard against paying twice for the same performance and helps align the manager’s interests with their own long-term outcomes. For managers and firms, it encourages more disciplined risk-taking, supports a focus on sustainable growth, and can strengthen trust and credibility in a competitive market.

World Entrepreneurs Day: Saudi Arabia’s Entrepreneurial Rise Enters a New Phase

Ghada Ismail

 

Every entrepreneur starts with an idea, but an economy becomes truly entrepreneurial when those ideas translate into businesses, jobs, investment, and new industries.

For Saudi Arabia, that transition is becoming increasingly visible.

As the Kingdom marks World Entrepreneurs Day on 21 August 2026, entrepreneurship is no longer a marginal part of its economic diversification agenda. It has become one of the key mechanisms through which Saudi Arabia is seeking to build a more dynamic private sector, create employment opportunities and develop new sources of non-oil growth.

The latest figures suggest that this transformation is gathering momentum.

According to the Global Entrepreneurship Monitor (GEM), Saudi Arabia’s Total Early-stage Entrepreneurial Activity (TEA), which measures the proportion of people aged 18 to 64 who are either starting a business or running a new one, reached 28.9% in 2025, up from 26% in 2024. The rate has more than doubled from 12.1% in 2018, highlighting the rapid expansion of early-stage entrepreneurial activity over the past seven years.

That growth is supported by an even larger pool of potential entrepreneurs. Entrepreneurial intentions reached 48.5% in 2025, meaning nearly one in two working-age adults not already involved in entrepreneurial activity intended to start a business within the next three years.

The figures point to something broader than a startup boom: a shift in attitudes toward entrepreneurship itself.

GEM found that around nine in 10 adults in Saudi Arabia either know someone who has recently started a business, believe they have the skills and experience to do so, or see good opportunities to establish a company locally. The findings suggest that entrepreneurship is increasingly viewed not simply as an alternative to employment, but as a viable career and wealth-building path.

 

From intention to business creation

Intentions, however, only matter when they translate into businesses.

Here, Saudi Arabia's latest company formation figures provide another indication of momentum.

During the first half of 2026, 46,900 new companies were established in the Kingdom, according to the Saudi Competitiveness and Business Center. During the same six-month period, the center delivered more than 2.9 million services to businesses, registered 86,800 establishments and verified 3,500 online stores.

The numbers reflect an increasingly streamlined environment for entrepreneurs. The center now connects businesses to around 4,800 services through integration with 80 government entities, covering areas ranging from company formation and licensing to tax, zakat and commercial registration.

This infrastructure matters because entrepreneurship is shaped not only by access to capital, but also by how easy it is to turn an idea into a legally operating business.

Saudi Arabia's broader competitiveness indicators also point in the same direction. The Kingdom ranked 13th globally and third among G20 economies in the 2026 World Competitiveness Yearbook, while authorities say around 1,000 legislative, procedural and technological reforms have been implemented to improve the business environment.

 

Capital follows opportunity

The evolution of entrepreneurship can also be measured by the willingness of investors to back Saudi founders.

Saudi Arabia recorded its strongest venture capital year on record in 2025, with both funding and transaction activity reaching new highs, according to MAGNiTT. The Kingdom raised $1.72 billion across 257 venture capital deals, making it the largest venture capital market in MENA by both funding and deal activity.

The momentum continued into 2026, although the market became more selective.

MAGNiTT's H1 2026 Saudi Arabia Venture Capital Report found that funding declined 74% year on year to $219 million, while deal count fell 41% to 72 transactions. Despite the slowdown, Saudi Arabia remained one of MENA's most active venture markets, although its share of regional funding fell sharply from 49% in H1 2025 to 16% in H1 2026.

The changing funding landscape is important. A mature ecosystem is not necessarily one where funding rises every year. It is one where investors increasingly distinguish between scalable businesses, sustainable business models and companies that can generate long-term value.

 

The next challenge: building companies that last

Saudi Arabia's entrepreneurial story, therefore, is no longer simply about how many companies are being created.

The more important question is how many can survive, scale, and become major employers or regional businesses.

This is particularly relevant because GEM found that while the percentage of adults starting or running new businesses reached 28.9% in 2025, established business ownership fell to around one in eight adults, compared with around one in five a year earlier.

The gap highlights the next stage of Saudi Arabia's entrepreneurial journey: turning a high volume of early-stage activity into businesses that survive, scale and contribute to long-term economic growth.

Creating a company is only the first milestone. Entrepreneurs need access to follow-on funding, skilled talent, customers, technology and international markets if startups are to progress from early-stage ventures into durable businesses.

There are encouraging signs. Four in five Saudi new entrepreneurs surveyed by GEM anticipated employing more than five additional people within five years, pointing to strong growth and employment ambitions among the country's emerging business owners. At the same time, digital technology is becoming increasingly central to how these entrepreneurs reach customers and grow, with a similar proportion expecting to use more digital technology to sell their products in the following six months.

For World Entrepreneurs Day 2026, this may be the most important story behind the numbers.

Saudi Arabia is not simply producing more entrepreneurs. It is building the infrastructure, capital markets and institutional environment around them.

The Kingdom's next entrepreneurial chapter will be measured not only by the number of startups founded, but by the number that scale from local ideas into national champions, regional platforms and global companies.

That is where the real economic impact of Saudi entrepreneurship will ultimately be decided.

What Running Our Own AI and GPU Stack Taught Us About Managing Agentic AI

By: Ahmed Rashad, Sr. AI Specialist, Middle East & Africa at Nutanix

 

Have you seen this film before? A new technology arrives, powerful and effortlessly accessible. Departments spin up projects with minimal oversight from IT or finance. The first efforts reproduce old ways of working, and then somebody rethinks the workflow entirely, and the pace picks up. Then the invoice arrives, and the organization discovers it must bring things under control without cutting off access, because access is now how the work gets done.

 

That was the cloud, twenty years ago. It is gen AI today, on fast forward. What took cloud most of a decade is taking enterprises about eighteen months.

 

We watch this from two seats. We run our own AI workloads on our own GPUs, so we have made these mistakes with our own money. We also sit alongside a great many organizations making them at the same time, in different industries and under different regulatory regimes. The striking thing is how little the story varies.

 

Everyone’s first question is the wrong one

It is almost always “which model?”, and it is the question that matters least, because the answer changes every quarter.

 

The question that survives contact with production is what a unit of work costs. Not cost per token, but cost per resolved support ticket, per merged pull request, per document retrieved. The unit price keeps falling while total spend keeps climbing, because cheaper inference simply means more inference. Jevons would have recognized it immediately.

 

The same discipline applies to the benefit side. Where organizations measure carefully, the gains tend to land in a recognizable range: on the order of 10 to 15 percent for support teams, and 20 to 25 percent in feature delivery velocity for engineering teams. Those numbers are only worth quoting when they have been instrumented beforehand, against a baseline captured before deployment. Worth knowing: a randomized trial by METR found that experienced developers completed real tasks 19 percent slower with AI tools, while believing they had been 20 percent faster. If you cannot say how you measured, you have a feeling rather than a result.

 

Agents are not chatbots, and they do not fail like chatbots

This is the shift most organizations are unprepared for. A person using an assistant makes a request and receives an answer, and both the cost and the blast radius are bounded by their attention. An agent decides for itself how many steps to take, which systems to touch, and what to do with whatever it finds. The same instruction on a different day produces a different number of tool calls, a different bill, and a different set of side effects.

 

Which means the controls that work are the ones you would apply to a new joiner with production access, not the ones you would apply to software licenses. An identity for every agent, distinct from the human who launched it. Permissions scoped to each tool and each system, because MCP support is table stakes now, but speaking MCP and letting you grant

an agent read access there and write access nowhere are very different things. Budget ceilings that are enforced rather than alerted on. Traces detailed enough to reconstruct why an agent took eleven steps rather than three. And a human gate on anything irreversible.

 

The organizations getting this right have arrived at the same architectural conclusion independently. Those decisions cannot live inside each application. They belong at a single point that every agent’s requests pass through, so that policy, spend and audit are answered once for the whole estate rather than reimplemented project by project.

 

Running inference in production is a different discipline from running a pilot

A demo needs one model to work once. Production needs many models to work continuously, at predictable cost, while the field moves underneath you. Every organization we work with has replaced a model in production faster than it expected to, whether because of a cheaper open weight release, a regulatory constraint, or a change in vendor pricing. The ones who suffered were those who had welded a specific model to a specific location and a specific set of applications.

 

Flexibility here is not a luxury; it is the whole game: serving different models for different tasks, sizing endpoints to demand, and sharing GPUs across workloads through partitioning and scheduling rather than dedicating them. And, unfashionably, batch. Document classification, index rebuilds and evaluation runs do not care whether they complete at 14:00 or at 04:00. Defer them, and interactive workloads get the daytime capacity they need. Banks ran on this logic throughout the mainframe era. It was never wrong. It merely stopped being necessary when compute was cheap.

 

Location is becoming a variable, not a decision

Public cloud wins on speed and on access to the newest hardware. Other forces push the opposite way. Data residency and sovereignty requirements are no longer a compliance checkbox to be satisfied at the end of a project. For a growing number of organizations, they determine which workloads can exist at all, and where. Add data gravity, latency to customers, and the economics of sustained utilization, and owned or collocated infrastructure starts to look like the sensible home for a meaningful share of inference.

 

Meanwhile, a new class of specialized GPU providers has appeared, and some of the organizations we work with are becoming those providers themselves, turning regional advantage and spare capacity into a business of their own.

 

Nobody gets this allocation right at the first attempt. What matters is that getting it wrong stays cheap to correct: that a workload can move between owned, rented and regional infrastructure without being rewritten, and that governance follows it when it moves.

 

Do not build a walled garden

The temptation is to stand AI up as a separate estate, with its own tooling, its own rules and its own team, deliberately quarantined from everything else. There are two problems with that.

 

The first is that agents produce nothing of value until they can reach the systems and the data where your business actually runs. A wall built for safety very often becomes the reason a promising pilot never becomes production. The capability works. It simply is not allowed near anything that matters.

 

The second is the arithmetic of running everything twice. Two sets of policies, two audit trails, two places to look during an incident, and two opportunities for them to contradict each other, while the people who understand your controls best sit on the far side of the wall from the workloads that need them most.

 

The organizations moving fastest treat AI as a workload like any other, subject to the same access model, the same operational discipline and the same teams, with the controls that are specific to AI layered on top rather than rebuilt alongside.

 

Where that leaves us

There is no magic bullet for a technology moving this fast, and anyone selling one is selling something else. But the discipline transfers even when the tools do not. Measure cost per unit of work. Instrument your claims before you repeat them. Give agents identities, budgets and boundaries, enforced in one place. Keep models and workloads free to move. And govern all of it with your estate rather than beside it.

 

The film is on fast forward, and none of us gets to slow it down. But you can learn the genre well enough to see the twists coming, and avoid being the character who loses the plot.

What Is an Entrepreneur-in-Residence (EIR)?

Ghada Ismail

 

Starting a company usually means dealing with uncertainty from day one. There is no guaranteed market, no perfect product, and often no clear answer to what comes next. This is exactly where an Entrepreneur-in-Residence (EIR) can make a difference.

An EIR is an experienced entrepreneur who temporarily joins an organization such as a venture capital firm, accelerator, incubator, university, or large company. The idea is fairly simple: bring someone with real experience of building businesses into an environment where new ideas are being explored.

But an EIR is not just another adviser sitting in meetings and giving founders advice. Depending on the organization, they may be expected to find a business opportunity, test an idea, work with startups, build a product, or even create a new company.

 

So, What Does an EIR Actually Do?

There is no single job description for an Entrepreneur-in-Residence. The role can look very different from one organization to another.

At a venture capital firm, an EIR might spend time looking at new markets and technologies, meeting founders, helping portfolio companies, or developing a startup idea that the firm believes could have potential.

In other cases, the EIR may already have an idea. The organization provides access to its network, resources, funding, or expertise while the entrepreneur works on turning that idea into something viable.

 

EIR vs. Consultant: What’s the Difference?

The two roles can sound similar, but there is an important distinction. A consultant is usually brought in to solve a specific problem. They analyze the situation, provide recommendations, and move on to the next project. An EIR is generally much closer to the building process. They might spot an opportunity, test whether customers actually want the product, find potential co-founders, develop an early version of the business, and eventually launch it.

In other words, a consultant is often paid to advise, while an EIR may be expected to build.

 

Why Are Venture Capital Firms Interested in EIRs?

For VC firms, an EIR can be a way to create opportunities rather than simply wait for founders to walk through the door.

Experienced entrepreneurs often know how to recognize problems worth solving. They also understand what it takes to turn an early idea into a company. By bringing these people into the firm, investors can explore new sectors and business models from the inside.

There is another advantage: relationships.

An experienced entrepreneur usually brings a network of founders, engineers, executives, investors, and industry specialists. That network can be valuable when an idea starts moving from the whiteboard to the real world.

 

What Makes a Good EIR?

Being a successful founder is helpful, but it is not enough.

A good EIR needs to be comfortable with uncertainty. They need to know how to ask the right questions, test assumptions quickly, and recognize when an idea is not working.

Curiosity is just as important as experience. Markets change, technologies evolve, and what worked for a previous startup may not work for the next one.

Most importantly, an EIR needs to be willing to get their hands dirty. Building a company involves far more than having a good idea. It means speaking to customers, testing products, recruiting people, changing direction, and sometimes starting over.

 

To Wrap Things Up…

An Entrepreneur-in-Residence is essentially an experienced builder given the time, space, and resources to explore what could come next. For investors and organizations, it can be a way to uncover new opportunities while bringing entrepreneurial experience closer to the decision-making process. For entrepreneurs, it offers a chance to explore their next move without having to start entirely from zero.

As startup ecosystems become more sophisticated, the EIR model offers an interesting middle ground between building, investing, and exploring.

High-Net-Worth Individuals: How they invest, protect capital, build legacy

Noha Gad

 

High Net Worth Individuals (HNWIs) occupy a unique space in the financial ecosystem, sitting at the intersection of private wealth and public consequence. Yet, for all their visibility in luxury markets and investment circles, their decision-making processes remain widely misunderstood. Today's HNWIs are navigating a world of increased regulatory scrutiny, shifting family dynamics, and a growing expectation to use their resources deliberately.

For many high-net-worth individuals, the central question changes once wealth has been created. Instead of focusing only on earning more, they must decide how to protect capital, diversify investments, manage risk, maintain liquidity, and pass wealth on responsibly. For example, a successful entrepreneur who has sold a business may suddenly move from having most of their wealth tied to one company to managing a large pool of investable assets. That transition requires a very different mindset, one centered on long-term planning rather than short-term growth alone.

Who is a high-net-worth individual?

A high-net-worth individual is someone with liquid assets of at least $1 million in investable or liquid assets, excluding their primary residence. Liquid assets held by HNWIs include cash and investments that can be easily liquidated or converted to cash, including stocks. These individuals need and receive tailored financial and money management services due to their net worth.

HNWI individuals may demand and can justify personalized investment management, estate planning, and tax planning services. They generally qualify for separately managed investment accounts rather than mutual funds.

These individuals may get various benefits from financial institutions. For instance, they may qualify for banking, investment, and other financial services with reduced fees, discounts, and special rates, in addition to access to special events and perks.

How do HNWIs invest?

High-net-worth individuals do not necessarily invest according to an entirely different set of financial principles. Diversification, risk management, liquidity, and long-term discipline remain important for every investor; however, the size and structure of their wealth often give HNWIs access to a broader range of opportunities.

HNWIs’ portfolios may need to support a business, preserve family wealth, generate recurring income, fund philanthropic goals, and prepare for the transfer of assets to future generations. Accordingly, investment strategy becomes less about selecting a single high-performing asset and more about building a resilient system of assets that work together.

Many HNWIs hold a core portfolio of traditional investments, including public equities, bonds, cash, and real estate. However, wealthy investors may also allocate part of their capital to private-market opportunities that are less accessible to the average investor. This includes private equity investments in established, non-listed companies; venture capital investments in startups and high-growth businesses; commercial real estate and development projects; hedge funds; and more.

Types of High-Net-Worth Individuals 

HNWIs can be divided into several different categories. Where they fall depends on how much they are worth:

  • Sub-HNWI: An individual with more than $100,000 but less than $1 million
  • Very-HNWI: An individual whose net worth is at least $1 million
  • Mid-Tier HNWI or Mid-Tier Millionaire: An individual whose net worth is between $5 million and $30 million in investable assets.
  • Ultra-HNWI: An individual who holds $30 million or more in investable assets and sits at the highest end of the standard HNWI classification framework.

Finally, the wealth of high-net-worth individuals can provide access to specialized investment opportunities, private-banking services, and sophisticated financial structures; however, it brings greater responsibility. Managing substantial wealth requires more than identifying attractive investments; it demands a clear strategy for preserving capital, maintaining liquidity, reducing concentration risk, and preparing for uncertainty.

For HNWIs, the financial journey often changes after wealth has been created. Over time, protecting that wealth becomes just as important as growing it. This often involves diversifying across asset classes and geographies, balancing liquid and long-term investments, and seeking professional support in areas such as estate planning, tax coordination, and family governance.