Capgemini Uncovers Top 5 Tech Trends to Watch in 2025

Sep 15, 2025

Capgemini unveiled today its “TechnoVision Top 5 Tech Trends to Watch in 2025”, focused on the technologies that are expected to reach an inflection point in the next year. The focus on AI and generative AI (Gen AI) is shared both by executives around the world as well as by the venture capital professionals that were interviewed in a global survey to be published at CES in January 2025. It is anticipated to also have a significant impact on other key technologies which are likely to reach a stage of maturity or breakthrough in 2025.

 

“Last year, Capgemini’s Top 5 Tech Trends predicted the emergence of smaller Gen AI language models and AI agents, both of which came to fruition. We also signaled the importance of Post-Quantum Cryptography, which was confirmed by the publication of the National Institute of Standards and Technology’s standards last summer. And as anticipated, semiconductors have been at the center of attention in 2024 with significant evolution driven by the massive use of AI and generative AI, as well as shifts in market dynamics,” explains Pascal Brier, Chief Innovation Officer at Capgemini and Member of the Group Executive Committee. “In 2025, we see AI and Gen AI having a major impact on companies’ priorities and also on many adjacent technology domains, such as robotics, supply chains, or tomorrow’s energy mix.” 

 

Technologies to watch in 2025

 

  1. Generative AI: From copilots to reasoning AI agents

Generative AI is now entering the dawn of a gentrification where AI systems are evolving from isolated tasks to specialized, interconnected agents. In fact, according to a Capgemini Research Institute survey of 1,500 top executives globally, which will be published in January 2025, 32% of them place AI agents as the top technology trend in data & AI for 2025.  Thanks to the increasing capabilities of logical reasoning in Gen AI models, these will start operating more autonomously while providing more reliable, evidence-based outputs, and will be able to manage tasks such as supply chains and predictive maintenance without constant human oversight. AI systems can handle dynamic decision-making in more sensitive environments where correctness is paramount. The next step will be the rise of a super agent, an orchestrator of multiple AI systems, optimizing their interactions. In 2025, these advancements will enable new AI ecosystems across industries, allowing new levels of efficiency and innovation.

 

Why it matters: With the maturation of AI models, transformer models and other Gen AI architectures have reached new levels of sophistication and accuracy, making multi-agent systems viable for real-world, complex, dynamic decision-making, even in unpredictable situations. This is set to unlock greater potential in industries that rely on quick, flexible responses to unexpected challenges, such as healthcare, law, and financial services.

 

  1. Cybersecurity: New defenses, new threats

AI is transforming cybersecurity, enabling both more sophisticated Gen AI-enhanced cyberattacks and more advanced AI-driven defenses to the point where almost all organizations surveyed (97%) in the recently published Capgemini Research Institute’s report say they have encountered breaches or security issues related to the use of Gen AI in the past year. In recent years, with remote work, companies now face a larger attack surface and greater vulnerability to these threats. In fact, 44% of top execs in the upcoming Capgemini Research Institute report place the impacts of Gen AI in cyber as the top technology topic in cybersecurity for 2025. To mitigate these risks, there have been renewed investments and innovations in endpoint and network security, increased efforts to automate threat detection, especially using AI-driven threat intelligence, as well as an effort to prepare for the future by reinforcing encryption algorithms, in particular the growing interest into Post-Quantum Cryptography to protect against the next expected disruption: quantum-computing threats. This shift marks a broader transformation in how businesses approach security and build trust in their increasingly autonomous systems. 

 

Why it matters: In 2025, generative AI-powered cyberattacks will continue to be more sophisticated and widespread, increasing risks for organizations. In parallel, as AI plays a larger role in decision-making and operational control, ensuring that humans trust these systems will become crucial. But it's not just about being safe—it's about feeling safe. Cybersecurity must address both technical and psychological concerns, ensuring not only protection but confidence in the systems people rely on daily.

 

  1. AI-driven robotics: Blurring the lines between humans and machines

Advancements in AI technology have accelerated the development of next-generation robots, building upon innovations in mechatronics and expanding beyond traditional industrial uses. While robotics used to be dominated by hard-coded, task-specific machines, the development of Gen AI is spurring the development of new products (including humanoid robots and collaborative robots - or cobots) that can adapt to diverse scenarios and learn continuously from their environment. According to the Capgemini Research Institute’s upcoming report, 24% of top executives and 43% of Venture Capitalists see AI-driven automation and robotics as one of the top 3 tech trends in data and AI in 2025. With robots becoming more autonomous and AI taking on complex decision-making roles, the future of work may see a shift in the traditional structure of authority. The rise of AI-powered machines that mimic human behaviors challenges our understanding of leadership, responsibility, and collaboration, ultimately pushing us to reconsider the role of humans.

 

Why it matters: As Industry 4.0 progresses, AI-powered robots will drive efficiency, flexibility, and innovation, becoming key components of intelligent, connected systems that redefine industrial processes. By 2025, advances in natural language processing and machine vision will further enhance their capabilities, allowing robots in manufacturing, logistics, and agriculture to take on more complex roles within the modern workforce.

 

  1. Nuclear: The surge of AI driving the clean tech agenda

The energy industry is in the midst of a transformative shift, with the energy transition accelerating at an unprecedented pace. This change is fueled by mounting pressure to fight climate change and supported by rapid innovations across various sectors, from renewables and biofuels to low carbon Hydrogen and beyond. Nuclear energy stands out as a focal point for 2025: nuclear is re-emerging at the top of the business agenda, propelled by the urgent need for clean, dependable and controllable power that can support the rising energy demands of AI and other high-energy technologies. Although in September/October 2024,   very few top execs globally identified Small Modular Reactors (SMRs) as a top 3 Sustainability technology for 2025, SMR technology development is expected to accelerate by 2025, and other key innovation priorities include strides toward limitless, clean power with nuclear fusion, or Advanced Modular Reactors that differ from light water reactors in the use of new types of fuels and a higher temperature and for some of them the promise to reduce the production of nuclear waste. 

 

Why it matters: Driven by the massive energy demands of AI, major tech players are turning to nuclear energy to meet their growing computing needs. Large-scale investments are expected to further accelerate innovation in reactor technology and waste management, as the tech industry acknowledges that renewables alone cannot sustain its energy demands.

 

  1. New generation supply chains: Agile, greener and AI-assisted 

In the last few years, businesses have had to navigate increasingly complex, unpredictable market conditions. Key technologies including AI, data, blockchain, IoT, and connectivity with Terrestrial Satellite Networks are now playing a strategic role in improving the cost efficiency, resilience, agility, circularity, and sustainability of supply chains. These technologies are allowing companies to enhance their predictive capacities and navigate an ever-changing ecosystem as they have now reached a sufficiently high level of maturity and therefore reliability. Meanwhile, progress in space techs such as low-earth orbit satellite constellations is particularly essential to increase coverage in white spots which is crucial for companies to be able to control their entire supply chains throughout the globe. In fact, according to the Capgemini Research Institute’s upcoming report, 37% of top executives see these new-generation supply chains powered by technologies as the top tech trend in industry and engineering in 2025. Additional regulatory and environmental constraints will make this shift all the more critical to ensure competitiveness, agility and resilience.

 

Why it matters: In 2025, global supply chains will keep facing environmental disruptions, regulatory pressures, and geopolitical tensions which will impact the flow of goods and raw materials. New regulations like the European Union’s Digital Product Passport will make it mandatory for companies to track and disclose the environmental footprint of their products, pushing them to adopt more sustainable practices. 

 

Beyond 2025 - technologies shaping the next 5 years:

 

  1. Engineering biology: BioSolutions to today’s most pressing challenges

While the potential of engineering biology and its ability to transform manufacturing, develop drugs, and produce materials with novel properties has been widely discussed over the past years, this technology is yet to reach its scaling phase. According to the Capgemini Research Institute’s upcoming report, 41% of top executives believe that molecular assembly will reach maturity and become commercially viable by 2030. Meanwhile, 37% of them envision the same for Genomic Therapies. In the coming years, we can look forward to new innovations in this diverse field, such as personalized mRNA vaccines and GenAI for protein design.

 

  1. Quantum computing: on the verge of the quantum leap

According to the upcoming Capgemini Research Institute survey, 55% of top executives and 44% of VCs expect quantum computing to be one of the top 3 technologies within the ‘Computing & Networking’ space which will create a major impact in 2025. 41% of top executives expect to be experimenting with quantum computing Proofs of Concepts with limited use cases, and 27% of the top executives surveyed expect the technology to be partially scaled in some parts of the organization in 2025. The key question is – when will the quantum leap happen, and who will master it?

 

  1. Artificial General Intelligence: I think, therefore AI am? 

AI reasoning capabilities have made spectacular progress over the past 5 years, and some predict an era of artificial general intelligence (AGI). As such, 60% of top executives and 60% of VCs surveyed by the Capgemini Research Institute believe this technology will reach maturity and become commercially viable by 2030. Would this technology basically be able to mimic human intelligence to the point of making it irrelevant? This topic leads to exaggerated predictions, and some now question whether the intelligence potential of the technology is really unlimited.

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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.