The True Cost of Information Vulnerability in the Era of Machine Learning

March 11, 2026

In the 21st century, businesses have long known to be cautious with how they manage information. Well-publicized data breaches have cost Fortune 500 companies hundreds of millions of dollars in damage. That’s before you even take into account the harm that these instances have done to their reputations. There is a genuine financial and human cost to mismanaged information.

Unfortunately, with the advent of AI, those costs are higher now than they’ve ever been. In this article, we take a look at why cybersecurity is uniquely important in 2026.

How Artificial Intelligence Changes Cybersecurity

Over the last three years, nearly 100% of businesses have invested in some form of artificial intelligence. The problem? They don’t really know how to use it. Nearly 100% of business investments in AI are currently generating a loss for the companies that have invested.

Why is this relevant to information security? Because it speaks to a larger truth. Businesses may understand that they’re supposed to have AI, but very few of them understand how they’re supposed to use it.

There are unique sources of vulnerability that were not previously relevant. Bad actors are able to target native LLMs to corrupt internal information and extract sensitive data from companies without their knowledge. Some experts call this “shadow AI.” Essentially, it’s just another corridor of vulnerability.

Businesses have long been using software as a way of storing large quantities of proprietary data. AI integrations are simply a continuation of what’s already been taking place, but in a less secure and less understood package.

AI on the offensive angle can also be used to automate and accelerate intrusive attacks, further expanding on the problem.

The True Cost of Data Breaches

Totaled, the financial cost of AI-related information mismanagement has added up to $600,000 to the average cost of a data breach in 2026.

It’s a significant figure, though of course not necessarily one that’s relevant to every organization. A small e-commerce store, for example, or a mom-and-pop shop with a website, isn’t quite at the same level of risk exposure.

However, it is true that anyone who’s using modern software or AI integrations and doesn’t fully understand how to keep them secure can face the consequences of a data breach.

The costs of a data breach are severalfold:

Time: It sometimes takes the better part of a year to recover from a data breach. During that time, efficiency lags and productivity falters.
Cost: Data breaches generally require professional mediation. This can cost tens of thousands to many millions of dollars, depending on the scope of the breach.
Trust: Possibly the highest cost is trust. Consumers hand over a lot of information to businesses that they frequent. This can involve personal details and also financial ones. Once a business has become publicly associated with a data breach, it can be difficult to regain consumer confidence.

While these risks are alarming, there are simple steps you can take to protect yourself from them.

Step One: Prioritize Cybersecurity Best Practices

The simplest thing you can do to insulate yourself from risk is to be proactive and cautious from a cybersecurity perspective.

Most certainly, your business already has firewalls in place. These are actually really effective at successfully negating the majority of breach attempts. That said, you still need to be careful about several factors:

What devices you use to access sensitive information.
What Wi-Fi networks you sign onto while accessing work materials.
What kind of emails you open on work computers, phones, tablets, etc.

This latter point might sound obvious. Most people likely believe that they’re too smart to fall victim to a phishing campaign.

In fact, this is one of the most common causes of breaches. Modern bad actors are skilled at social engineering situations in which otherwise intelligent people will make mistakes that feel obvious in retrospect.

You might, for example, get a receipt that looks like it came from Amazon claiming that you made a $600 purchase.

Within the receipt is a link you can click to cancel the order. As your mind panics at the thought of an unexpected $600 bill, never for a moment does it occur to you that Amazon has never before sent you an email asking if you’d like to cancel your order. Maybe, probably, this thought enters your head two seconds after you click the link and are directed to a website that looks a lot like, but not quite, something belonging to Amazon.

At this point, you know you’ve made a mistake. You exit and hope for the best. What you don’t know is that this tiny action is all it took for a cybercriminal to get their foot in the door.

From there, they may lurk in the background for months, doing damage. By educating staff and prioritizing security, you can avoid mistakes of this kind.

Step Two: Understand How Your Tools Are Vulnerable

It’s also helpful to have a legitimate understanding of what your tools are doing, what information they’re storing, and in what ways a bad actor might compromise that information.

For example, if “shadow AI” is a phrase you only just heard in this article, it may be a good idea to examine how your artificial intelligence integrations are actually working, what information they have stored, how it could be compromised, and whether or not you even really need this integration in your business at all.

It’s ironic that many businesses are now being made more vulnerable than ever by tools that aren’t even producing revenue for them.

This isn’t to say that the best thing you can do is revert to 1990s business practices. Rather, you should be selective with how you integrate technologies that use large amounts of information.

Data is great, but it’s also a vulnerability. Be thoughtful about why, when, and how you take those risks in situations where it is worthwhile. Make sure that the information is being handled as securely as possible.

Step Three: Systemize Data Security

Think about data security the way you might think about a diet. You can read articles about various health recommendations and tips.

This might make you slightly more likely to order a side salad instead of French fries the next time you go out to eat. Or you can fill your real-life grocery cart with vegetables, ensuring that you eat healthy for lack of another option.

You should be similarly decisive in how you manage data security policies. It’s not enough to simply provide yourself and your staff with friendly reminders periodically. Rather, for true and impactful results, data security should be baked into every aspect of your business processes.

This means requiring multi-factor identification, possibly automating sign-outs periodically after short periods of inactivity to reduce risk, and so on.

These are exactly the types of steps that are required of many organizations that deal with sensitive information.

For example, HIPAA guidelines require many such steps for healthcare providers. While you may not need to be quite so proactive in your own approach to data security, ensuring that it’s baked directly into your business practices is a great way to avoid breaches. Your staff will be annoyed, but they’ll get over it.

Step Four: Consider the Role of a Data Security Specialist

The exact shape that this recommendation may take will vary based on the size of your organization. Some businesses have full-time data security specialists on hand. Others might utilize the occasional services of a consultant or even a fractional firm in which they share cybersecurity professionals with multiple businesses.

Obviously, adding skilled members to your teams in a non-revenue-producing role is not an option for every business.

That said, professional advisement can have a direct monetary value, particularly depending on your level of risk exposure.

If you’re dealing with many thousands of people’s financial data, for example, the risk of a data breach for your business could result in millions of dollars of damage. At that point, the upside potential of your investment in a data specialist takes on a much higher value.

Conclusion

Data security is difficult for many businesses. Owners, or even presidents and CEOs, don’t necessarily have a background in it. In many cases, despite 20 years of steep digitalization in the workforce, they don’t fully understand the levels of risk exposure that are at work here. Only after a breach has taken place does the level of dependency on digital technology fully crystallize.

Cybersecurity is never the most exciting thing a business will work on. It doesn’t clearly contribute to the bottom line, nor does it excite the way a newly developed product or marketing campaign might. Nevertheless, it’s essential, particularly now in an age where AI has created new forms of vulnerability and greater types of attacks.

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How High‑Demand Care Roles Reflect Broader Economic and Demographic Shifts

March 11, 2026

In the past decade, job listings for home‑health aids, personal care assistants, and early‑childhood educators have exploded. What was once a niche, often low‑pay sector— much like most social worker positions— is now a cornerstone of many national economies, and now offers a higher paying form of social work.

The surge isn’t a random blip; it mirrors deep‑seated changes in who we are, how we work, and where our money flows. By examining the forces behind the rising demand for care roles, we can read a broader story about aging societies, shifting labor markets, and the evolving contract between governments, businesses, and citizens.

Here are some observations on how high-demand care roles reflect broader economic and demographic shifts.

Demographic Drivers: Aging Populations and Changing Family Structures

Globally, life expectancy has climbed by more than a decade since the 1990s, denoting (among many other factors) the high demand for a variety of social work roles. While fertility rates have slipped below replacement levels in most advanced economies. The United Nations projects that by 2050, people aged 65 and older will constitute 16 % of the world’s population—up from 9 % in 2019.

More seniors mean more chronic conditions, mobility limitations, and cognitive impairments, all of which create a steady stream of demand for personal‑care aides, skilled nurses, and dementia‑specific support workers.

Historically, adult children and extended kin filled the caregiving gap. However, today’s families are smaller, more geographically dispersed, and juggling dual‑career households. A 2023 Pew Research study found that 68 % of working‑age adults in the U.S. live more than 30 miles from their parents, making daily in‑home assistance impractical. Consequently, the market has shifted from informal, family‑provided care to a professionalized, outsourced model.

Early‑Life Care: The Demographic Counterbalance

While the “silver wave” pushes demand for elder care, a parallel rise in birth rates in developing regions and a growing emphasis on early childhood development have amplified the need for qualified childcare providers. Research links quality early‑life care to higher educational attainment and long‑term economic productivity, prompting governments to invest heavily in preschool teachers and family‑support services.

Economic Transformations: From Manufacturing to Service‑Centric Economies

Post‑industrial economies have steadily migrated from manufacturing to services, now accounting for roughly 70 % of GDP. Within this service umbrella, “person‑centered” care has become one of the fastest‑growing subsectors. In the United Kingdom, the care economy contributes £113 billion annually—a figure that has risen by 30 % since 2015.

Wage Pressures and Labor Supply

Care roles traditionally suffered from low wages and limited career pathways, leading to chronic understaffing. Yet, as the sector expands, market forces are nudging salaries upward. A 2022 report from the International Labor Organization (ILO) shows median hourly wages for home‑care workers in the EU have increased by 12 % over five years, narrowing the gap with other low‑skill occupations. Higher wages attract a more diverse labor pool, including immigrants and younger workers previously drawn to retail or hospitality.

Gig‑Economy Integration

Platforms such as Care.com, TaskRabbit, and Uber‑style “on‑demand” services have introduced a gig‑based model to the care sector. While this flexibility can help families secure short‑term help, it also raises questions about benefits, training standards, and continuity of care. The gig‑economy’s footprint illustrates how technological disruption intersects with demographic necessity, reshaping labor contracts across the board.

Public Investment and Immigration Pathways

Countries with aging populations—Japan, Germany, Canada—have introduced comprehensive care‑worker subsidies, wage guarantees, and career ladders. Japan’s “Long‑Term Care Insurance” system, for example, funds training and wages for certified care workers, helping to mitigate the shortage despite a shrinking labor pool.

Many high‑income nations now rely on foreign‑born workers to fill care roles. The United Kingdom’s “Health and Care Visa” and Australia’s “Aged Care Workforce” initiatives prioritize skilled migrants, providing fast‑track residency. While this eases immediate staffing gaps, it also raises questions about brain drain in source countries and the sustainability of a care model built on transnational labor.

Conclusion

High‑demand care roles are more than a job market statistic, they are a barometer of how societies adapt to longer lives, smaller families, and shifting economic structures. The swelling need for caregivers reflects an aging demographic, a service‑oriented economy, and an evolving social contract that places human well‑being at the center of economic policy. By recognizing the interconnectedness of these forces, we can turn the care surge from a looming crisis into a catalyst for inclusive, resilient growth.

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How US/Israeli Iran Strikes Penalize Global and PH Prospects

March 9, 2026

iran israel us usa united state america flag waving

By Dan Steinbock

The US/Israel strike against Iran aims at regime change to dominate its energy resources and decapitate its leadership. It will disrupt energy markets and penalize economic prospects worldwide – particularly in the Philippines.

On February 28, a joint US–Israel air campaign targeted Iranian leadership, missile forces, nuclear facilities, and the Revolutionary Guards’ (IRGC) infrastructure.

Opening strike killed Iran’s Supreme Leader Ali Khamenei and senior commanders. Threatened by Israel’s obliteration doctrine, Tehran is retaliating with ballistic missiles, drones, and strikes on US bases in Gulf states and Israel.

US strategy reflects a phased escalation ladder moving from decapitation and air dominance to the suppression of missile and drones. It seeks Iran’s eventual regime collapse or “unconditional surrender.”

But this is just a prelude.

Surging economic pain

US strategy reflects a phased escalation ladder moving from decapitation and air dominance to the suppression of missile and drones.

In a briefing a week ago, I projected that this unwarranted, illegal and lethal war will have an adverse global impact. The human costs of the conflicts are climbing in Iran (over 7,300 killed and injured), Lebanon (1,100), Israel (140+), Gulf states (115). In Lebanon, 330,000-400,000 people have been displaced; in Iran, tens of thousands.

After oil price soared to more than $90, it could climb toward $120–150 if escalation persists. Production disruptions in the Gulf energy facilities will have long and adverse effects on gas/LNG. In the process, inflation will climb. For every $10 oil rise, factor in 0.3–0.4% additional inflation in major economies.

In global markets, equities are falling and, energy prices surging. If hostilities linger another full week, expect Brent oil to climb from $90-$95 to $95-$110. Gas/LNG prices could increase 30-40%. Global inflation will surge by 0.4-0.7%. At the same time, global GDP will fall by 0.1% or more.

A 1-2-month disruption scenario would raise inflation by 0.5-1.0%. A prolonged conflict could push inflation up to 7%, with a significant stagflation risk.

Oil shocks are likely to widen the Philippine current-account deficit and the rising debt burden.

Inadequate responses

On Friday, President Marcos Jr. announced a temporary 4-day work week in several government offices. As an oil crisis response, such measures have limited value.

The government is already struggling with a historical corruption scandal, which has not led to structural reforms, and an economic slowdown, which is about to worsen further. Now Manila must additionally tackle higher import bill for energy, peso depreciation, lower consumption and weaker investment sentiment.

The Philippines is highly exposed to Middle East energy disruptions because a whopping 98% of its crude oil imports originate from the Middle East.

Fuel costs raise transport fares, electricity, food prices and manufacturing costs. Philippine fuel prices have already surged. But there is much more economic pain ahead.

The Marcos Jr government has also initiated repatriation efforts for the Overseas Filipino Workers (OFWs) in the Gulf region, with recent reports indicating hundreds have returned or are in the process of returning.

Unfortunately, that’s grossly inadequate.

Over 1 million Filipinos at risk

Despite elevated geopolitical tensions and regional conflicts since 2023, up to 2.5 million Filipinos continue to live and work in the Middle East. The Gulf is one of the largest OFW concentrations worldwide.

Saudi Arabia alone ranks as one of the top sources of cash remittances worldwide, alongside the US and Singapore.

UAE and Saudi Arabia each host up to 1 million Filipinos, while up to 250,000 live in Qatar and Kuwait each. As of today, over 1 million OFWs face risks due to the elevated hostilities in the region.

Also, some 20,000 seafarers of all nationalities have been stranded aboard ships in the region. Since Filipinos make up a fourth of crews worldwide, this implies roughly 4,000–5,000 Filipinos among them.

Should the Iran war linger further, no plans can ensure the full safety of the Filipinos in the region.

EDCA sites as potential targets

Furthermore, concerns have been expressed about possible reverberations in the Taiwan Straits. There are 160,000-200,000 OFWs in Taiwan and 12,000 in China.

If the region, including Philippine EDCA logistics platforms enabling a Taiwan war effort, is swept by a major conflict, there is no fast way to repatriate Filipinos.

Recently, Senator Erwin Tulfo called for a review of the Enhanced Defense Cooperation Agreement (EDCA) sites, fearing that the presence of U.S. military facilities could turn the Philippines into a target for retaliatory attacks amid the escalating Iran-Israel conflict.

Historically, US military bases, whether fixed or rotational, have asserted sovereignty, which makes them and the region hosting them a target. Hence, the concern that conflict could spill over into and from US military bases in the Philippines.

But there is more to possible targeting. Manila presents itself as a peaceful neutral in the Middle East. But realities are more complex.

PH as a growth market for Israeli arms

In 2020-2024, the Philippines had three main military suppliers. South Korea’s arms transfers accounted for a third (33%) of all arms imports to the Philippines. It was followed by Israel (27%) and the United States (20%).

In Israel, Philippines is seen as a growth market. It accounts for some 8% of Israel’s total arms exports worldwide.

Manila’s recalibration in foreign affairs, which was introduced to ensure security and prosperity, could contribute to undermine both.

Until recently, the Armed Forces of the Philippines largely bought from the Israeli Elbit Systems and Rafael Advanced Defense Systems, with key acquisitions including unmanned aerial vehicles, missile systems and air defense, artillery, maritime security, ground vehicles, small arms and surveillance.

Many of these weapons have been battle-tested on Palestinians in Gaza’s genocidal atrocities, ethnic cleansing in the West Bank, the lethal spillovers in Lebanon and Syria, and the US/Israel war against Iran.

The Philippines’ broad military cooperation with the Israeli military proxies has exposed millions of Filipinos to risks from the Middle East to Southeast Asia.

Ironically, Manila’s recalibration in foreign affairs, which was introduced to ensure security and prosperity, could contribute to undermine both.

The original version was published by The Manila Times on March 9, 2026.

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About the Author

Dr. Dan Steinbock is an internationally recognized strategist of the multipolar world and the founder of Difference Group. He has served at the India, China and America Institute (USA), Shanghai Institutes for International Studies (China) and the EU Center (Singapore). For more, see https://www.differencegroup.net

Failure: The Secret Sauce In Successful Gen AI Strategy

March 9, 2026

By Dr. Gleb Tsipursky

Generative AI rewards those who embrace constant iteration. Instead of fearing errors, treat them as essential data. Every strange output reveals how the system actually thinks, providing the edge you need to master the tool.

AI offers the rocket fuel that propels innovation forward and enables organizations and teams to overcome challenges and manage risks. This is especially true in a field as unpredictable and transformative as Gen AI. When we talk about innovation, we must acknowledge that failure is not the opposite of success, but a crucial part of it.

Gen AI solutions, by their nature, demand iteration, testing, and refinement. Not every experiment will hit the mark immediately, if at all.

De-Stigmatizing Failure in Gen AI Strategy

The traditional corporate landscape often views failure through a punitive lens. This leads to fear and risk-averse behavior. Employees who experience setbacks might worry about career repercussions, public embarrassment, or losing credibility.

This mindset is a death knell for innovation, suffocating the exploratory nature of Gen AI work, where trial and error are not just common, but essential.

This mindset is a death knell for innovation, suffocating the exploratory nature of Gen AI work, where trial and error are not just common, but essential.

Researcj by McKinsey shows that companies cultivating a culture of innovation and embracing failure greatly outperform their peers in implementing technology, with 21% of weak innovators succeeding in digital transformations compared to 45% of strong innovators. This underscores the undeniable link between embracing failure and achieving tangible business success.

So, how do we dismantle this culture of fear? We need a seismic shift in how we perceive failure, starting at the top.

Leaders must actively cultivate an environment where calculated risk-taking is not just tolerated, but celebrated. Employees need to know that their careers won’t be derailed by experiments that don’t pan out. Instead, the focus should be on the insights gained from every experiment, regardless of the outcome. Each “failed” project is a treasure trove of data.

Consider a recent engagement where I consulted for a mid-sized regional retail chain struggling to personalize its marketing efforts. This company, with around 500 employees and $200 million in annual revenue, was eager to leverage Gen AI to improve customer engagement.

Initially, they were hesitant. The leadership team was concerned about the potential for wasted resources and the stigma of failed projects.

We began by implementing a small-scale pilot project using Gen AI to tailor email marketing campaigns. The first few attempts fell short of expectations. The personalized content didn’t resonate as anticipated, and click-through rates remained stagnant at a measly 2.5%.

However, instead of viewing this as a failure, we treated it as a learning opportunity. We conducted a thorough analysis and discovered that the initial customer segmentation model was too broad, resulting in generic messaging that didn’t appeal to specific customer interests.

We also found that the tone of the AI-generated content didn’t align with the brand’s voice, with a formality score 15 points higher than their usual communications.

The Power of Post-Mortem Analysis for Gen AI Strategy

When an experiment doesn’t go as planned, the knee-jerk reaction might be to find someone to blame. This is counterproductive and stifles learning. A constructive approach involves a detailed post-mortem analysis.

What went wrong? Why did certain methods fail? How can we adjust our approach in the future? These questions are not about assigning blame, but about extracting knowledge.

We’re not looking for scapegoats; we’re searching for understanding. Were there gaps in the data or model training? Did we misalign the Gen AI tool with the business problem we were trying to solve?

Systematically answering these questions creates a roadmap for future success. This analysis also helps build institutional knowledge, ensuring that the entire organization benefits from individual teams’ learnings.

In the case of the retail chain, the post-mortem analysis of the initial Gen AI marketing campaign revealed critical insights. We refined the customer segmentation model, focusing on more granular data points like purchase history, browsing behavior, and demographic information, increasing the number of segments from 10 to 25.

We also fine-tuned the Gen AI model to generate content that better reflected the brand’s personality, adjusting the formality score down by 15 points to match their existing brand voice.

The subsequent campaigns, informed by these learnings, showed significant improvement. Within three months, the retailer saw a 25% increase in click-through rates, rising from 2.5% to 3.125%, and a 15% rise in conversion rates, jumping from 1% to 1.15% from their email marketing efforts. They also received a 10% increase in positive customer feedback regarding email content relevance.

This translated to a noticeable uptick in sales directly attributed to the Gen AI-driven campaigns, with an eventual 8% increase in sales from email marketing.

This experience underscored the importance of embracing failure as a learning opportunity. By openly analyzing what went wrong and adjusting our approach, we were able to unlock the true potential of Gen AI for this organization.

It’s worth noting that the organization saved an estimated $50,000 in marketing costs within six months by switching from broad marketing campaigns to more targeted Gen AI driven campaigns. And that was the first project of many, which overall improved their bottom line by over $300,000 in a year. Such a case study clearly illustrates how real businesses gain real, financially-relevant benefits from applying the approach of viewing failure as a learning opportunity when implementing Gen AI.

Building a Gen AI Strategy of Shared Learning and Resilience

An open and transparent approach to failure helps facilitate shared learning. When failures are openly discussed and analyzed, it allows teams to learn from one another’s mistakes, accelerating the organization’s overall learning curve.

Instead of burying failed experiments, organizations should create forums where teams can present their findings, both successful and unsuccessful, to the broader group. This practice democratizes the learning process and reduces the likelihood of repeated mistakes, while simultaneously creating trust and openness.

Leaders can also encourage peer support networks, where employees involved in different Gen AI initiatives can offer advice and share lessons learned from their own successes and failures. This creates a communal learning environment, where the responsibility for Gen AI success is shared, rather than resting solely on individual teams.

These forums also allow for cross-functional collaboration, where failures in one department can provide insights that benefit another. This cross-pollination of ideas can lead to new approaches and methods for leveraging Gen AI that would not have emerged if failures were hidden or minimized. Moreover, organizations can take a proactive approach by building controlled environments where risk-taking is encouraged and the consequences of failure are minimized.

Innovation sandboxes — safe, controlled spaces for testing new technologies and processes — allow teams to experiment with Gen AI without the fear of disrupting core business operations. Such environments encourage risk-taking because the potential downsides are contained, allowing teams to focus on learning and improving rather than avoiding mistakes.

Creating a psychologically safe environment is paramount. This means a workplace where employees feel free to take risks, voice their ideas, and engage in creative problem-solving without fear of retribution if things don’t go as planned. This sense of safety is essential for encouraging experimentation, particularly in the context of Gen AI, where uncertainty is high.

A lack of psychological safety leads to a “play-it-safe” mentality, where employees only propose ideas they are confident will succeed. This limits the organization’s capacity to push boundaries and innovate. In contrast, when employees know that failure will be met with support rather than blame, they are more likely to take bold steps.

Leaders can foster this environment by publicly acknowledging the efforts of teams who take risks, regardless of the outcome, and by consistently framing failures as opportunities for growth.

An article by Forbes highlights the importance of psychological safety in driving innovation. It emphasizes how leaders can create a culture where employees feel empowered to take risks. Additionally, a study by Google, discussed on their re:Work platform, found that psychological safety was the most important factor in team effectiveness.

Failing to Gen AI Success

Creating a culture where failure is viewed as a natural part of innovation enables the organization to remain agile and responsive.

Ultimately, creating a culture where failure is viewed as a natural part of innovation enables the organization to remain agile and responsive. In a field as dynamic and quickly progressing as Gen AI, staying ahead requires continuous learning, which can only happen when employees feel empowered to experiment, fail, and try again.

Organizations that embrace failure as part of the process will not only see greater innovation but will also build a more resilient and adaptive workforce, capable of navigating the complexities of AI adoption with confidence and creativity.

Failure, when approached with the right mindset, is not an ending but a beginning. It’s the secret sauce that fuels the engine of innovation, driving us toward a future where Gen AI transforms our businesses and our world.

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About the Author

Dr. Gleb Tsipursky was named “Office Whisperer” by The New York Times for helping leaders overcome frustrations with Generative AI. He serves as the CEO of the future-of-work consultancy Disaster Avoidance Experts. Dr. Gleb wrote seven best-selling books, and his two most recent ones are Returning to the Office and Leading Hybrid and Remote Teams and ChatGPT for Leaders and Content Creators: Unlocking the Potential of Generative AI. His cutting-edge thought leadership was featured in over 650 articles and 550 interviews in Harvard Business Review, Inc. Magazine, USA Today, CBS News, Fox News, Time, Business Insider, Fortune, The New York Times, and elsewhere. His writing was translated into Chinese, Spanish, Russian, Polish, Korean, French, Vietnamese, German, and other languages. His expertise comes from over 20 years of consulting, coaching, and speaking and training for Fortune 500 companies from Aflac to Xerox. It also comes from over 15 years in academia as a behavioral scientist, with 8 years as a lecturer at UNC-Chapel Hill and 7 years as a professor at Ohio State. A proud Ukrainian American, Dr. Gleb lives in Columbus, Ohio.

Not for Now — For the Future: Why the Next decade of AI Commerce Needs a Trust Layer

March 8, 2026

By Dražen Kapusta and Terence Tse

As AI agents increasingly power cross-border commerce, a critical gap is emerging: digital infrastructure can exchange data but not understand it. Without a semantic interoperability “trust layer” — a shared, machine-readable framework for verifying what actually occurred in a transaction — AI-driven economies risk compounding errors, governance failures, and systemic opacity at unprecedented speed.

If someone is quietly congratulating themselves on finally understanding digital identity and AI compliance, here’s a reality check. Building trustworthy infrastructure involves more than just wallets and regulations. The past two years have seen the development of infrastructure like the EU Digital Identity Wallet, the AI Act, and the Digital Euro. However, the landscape has shifted. A new question is emerging, one less about infrastructure components and more about whether those components can understand each other. This is about semantic interoperability – the ability for machines to not only exchange data but also interpret its meaning across borders, systems, and languages. Unlike previous technical debates, this issue could determine whether our digital future truly succeeds. The reason for this new – and perhaps inevitable – development is simple: around the world, the foundational pieces of an autonomous economy are being assembled. But they were all put together without the layer that allows them to be understood by one another.

Many Conversations, One Missing Layer

We don’t need to look far to see the lack of semantic interoperability. In Brussels, technical experts warn that the EU Digital Identity Wallet – Europe’s leading digital infrastructure – is being developed with a critical flaw. The draft Implementing Regulations support basic data exchange but omit the semantic layer necessary for machines to comprehend what they’re reading. In other words, a professional qualification issued in Spain cannot be automatically understood by a German system. An educational credential cannot carry meaning across institutions. A regulatory attestation cannot be verified across borders without human intervention. In short, Europe is constructing an identity infrastructure that enables machines to read but not understand.

AI leaders from around the world convened at the India AI Impact Summit 2026. Sam Altman of OpenAI called for a global AI regulatory framework similar to the International Atomic Energy Agency. French President Emmanuel Macron proclaimed Europe a “safe space” for regulated AI. UN Secretary General António Guterres warned that no child should be a test subject for unregulated AI.

Innovation and governance, they all agreed, must go hand in hand.

Yet among these conversations lies a gap. Digital infrastructure is being built without interoperability. Can these setups exchange data or apply the same governance principles? The policymakers governing AI are focused on principles – should AI be regulated? No one seems to be creating the layer that links these individual, self-reliant systems.

The Problem

Sooner or later, issues caused by such divergent development pathways without interoperability will catch up with us. Imagine a routine cross-border transaction. A Spanish supplier’s AI agent negotiates with a German buyer’s agent. The supplier ships goods. The carrier logs delivery. The buyer’s system triggers payment. But the supplier’s product identifier uses a different schema than the buyer’s ERP. The carrier’s delivery event employs different semantics than the buyer’s proof-of-delivery requirements. The AI agents, acting rapidly, lack a shared layer of meaning.

Within minutes, three systems claim incompatible realities. The buyer’s agent disputes payment. The supplier’s agent raises a breach. Treasury automatically suspends the vendor. By the time a human investigates, dependent actions have already been carried out: reorder loops, penalty clauses, and credit holds. This isn’t very different from a situation where three witnesses to the same car accident, each speaking a different language and following different legal systems, submit their reports. The accident happened. Everyone agrees something took place. But without a shared framework to interpret what each report means, the insurance claim collapses — and by the time a translator arrives, the car has already been towed, the claim rejected, and the policy cancelled.

An Old Idea, Whose Time Has Come Again

In 1458, a merchant from Ragusa in southeastern Sicily, Italy, named Benedetto Cotrugli authored the world’s earliest known treatise on double-entry bookkeeping, thirty-six years before Luca Pacioli received most of the historical credit. Yet, what Cotrugli recognised was not merely an accounting technique. He understood that commerce on a large scale requires a shared framework of truth: a method for parties who have never met, trading across borders they cannot physically cross, to establish a mutually understandable record of what they agreed to and what they owe each other. His ledger was not just a business record. It was a social contract.

The challenge we face today remains largely the same. We operate in a global marketplace — an AI-driven economy enabling an increasing number of cross-border and cross-system transactions at unprecedented speeds. What we lack is the equivalent of Cotrugli’s ledger: not a record maintained by one party or another, but a shared, verifiable, collectively authoritative account of what truly transpired. The difference is that this time, the ledger cannot be paper-based, nor can it wait until the month-end close. It must be machine-readable, policy-aware, and capable of operating at the same speed as the transactions it manages.

The Missing Layer

Much of today’s policy discussion remains a level too shallow. Governments debate AI governance. Companies discuss technological expertise. Standards organisations debate formats and schemas. But governance without machine-speed evidentiary infrastructure is fragile, and expertise without semantics merely accelerates misunderstanding. A machine can process data without understanding it. Two systems can exchange records without agreeing on what has occurred. In a zero-trust environment, that is not resilience. It is vulnerability disguised as automation and speed.

This is why the future’s AI-powered NEO World will need a trust layer.

Such a layer must do more than just store records. It must ensure that when a meaningful event takes place between parties, that event produces a shared, verifiable, co-attested object that neither party can unilaterally alter afterwards. It must carry evidence, not merely reference it. It needs to be machine-readable and machine-interpretable. Additionally, it must allow authorised third parties – auditors, regulators, counterparties, courts, or AI agents themselves – to determine later, with high confidence, what happened and under which conditions.

This is the logic behind what we call NEO accounting. This is important for three reasons that extend far beyond accounting. Firstly, it means that the governance rules that apply to a transaction are embedded within the transaction record at the time of signing, not referenced from an external document that may later change. Secondly, it means that AI agents can be assigned cryptographically bounded mandates — a digital fence that specifies exactly what they are authorised to do and automatically triggers a downgrade if they breach it — without requiring human approval for each individual action. Thirdly, it means that every participant in a network builds a trust score based not on what they claim about themselves, but on what their transaction history demonstrates.

Cotrugli understood this last point intuitively, five centuries before it became an engineering problem. The merchant’s reputation, in his telling, was not a title or a credential. It was what the ledger proved, transaction by transaction, year by year.

What This Means for the Future

For business leaders, the concern is operational risk. As AI agents become standard participants in procurement, logistics, and financial transactions, the gap between what different systems believe to be true will widen faster than any manual audit can monitor. Organisations without a shared truth infrastructure will face compound error cascades at a speed that makes recovery exponentially harder.

For regulators, the message is equally clear. The EU AI Act, the Digital Identity Wallet, and AI governance frameworks from New Delhi all assume AI decisions will be traceable and auditable. But traceability requires capturing the trace at the moment of action — not reconstructing it from logs neither party independently trusts. Policy without the technical infrastructure to enforce it is not governance. It is simply an aspiration.

For architects of the Digital Single Market, the stakes are highest. Europe’s investment in digital identity will only realise its potential if credentials carry machine-interpretable meaning across borders — if a Spanish qualification is not merely displayed to a German system but understood by it. Without semantic interoperability, Europe risks building something that appears unified but functions as a collection of fundamentally opaque national systems.

The standards embedded in upcoming AI and digital frameworks will shape commerce for a generation. The window to include a semantic interoperability layer is closing — once specifications are finalised, extending them becomes a highly complex political and technical challenge. This is not a future problem. It is a present decision with long-term consequences.

Cotrugli wrote not only for merchants but also for the architecture of commerce as a whole. He understood that the system of shared truth he described was a vital choice: not just a tool for efficiency, but a decision about what kind of economy — and what kind of trust between strangers — a society wished to build. We face the same choice today as in Cotrugli’s time, only at a much greater scale and with things running at a speed he could not have imagined.

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About the Authors

Dražen Kapusta is the founder of COTRUGLI Business School and HashNET. He leads the COTRUGLI initiatives, focusing on AI-augmented Vanguard leadership, NEO Finance, blockchain, SDGs, and digital sovereignty. Dražen advises UN and EU bodies on AI and blockchain strategies.

Terence Tse is Professor of Finance at Hult International Business School and co-founder at the AI Native Foundation. He is also co-founder and Executive Director of Nexus FrontierTech.

Iran Appoints Mojtaba Khamenei as New Supreme Leader Amid Escalating War

March 8, 2026

Iran Appoints Mojtaba Khamenei Supreme Leader

Iran has named Mojtaba Khamenei as the country’s new supreme leader following the death of his father, Ali Khamenei, during the early stages of the war. Iranian state media confirmed the decision, according to reports cited by international news agencies.

The appointment places Mojtaba Khamenei at the top of Iran’s political and military hierarchy. As supreme leader, he now holds authority over institutions such as the Islamic Revolutionary Guard Corps and other powerful security bodies that shape Iran’s domestic and foreign policies.

The leadership change comes as fighting across the Middle East intensifies. Iran has launched missile and drone attacks across the Gulf region in response to ongoing strikes by U.S. and Israeli forces. Governments in several neighboring countries have reported damage to civilian infrastructure.

Authorities in the United Arab Emirates said air defense systems intercepted incoming missiles and drones, while residents in major cities heard explosions as defenses responded. In Bahrain, officials reported damage to a water desalination facility and a university building after drone strikes. Kuwait also confirmed that drones hit fuel depots and damaged part of a government building near its international airport.

The conflict has also shaken global energy markets. Fighting near the Strait of Hormuz disrupted oil shipments from the Gulf, pushing crude prices above $100 per barrel for the first time in years.

Meanwhile, U.S. President Donald Trump previously suggested that Washington should influence Iran’s next leadership. Israeli military officials warned they would target individuals involved in selecting the new leader.

The conflict has already caused thousands of casualties and displaced large numbers of civilians across the region.

Related Readings:

Trump’s Iran Strategy Remains Unclear Amid Mixed Messaging

Global Leaders Respond After U.S. and Israeli Strikes on Iran

Iran Protests Turn Deadly As Witnesses Describe Widespread Violence In Tehran

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Investing vs Trading: How Tax, Costs, and Psychology Change the Math

March 6, 2026

The distinction between investing and trading extends beyond timeframe differences. Tax treatment, transaction costs, and psychological demands create mathematical realities that separate these approaches far more dramatically than most beginners recognize. Numbers reveal why one strategy produces consistent wealth while other destroys capital for overwhelming majority.

The Tax Differential That Changes Everything

Short-term trading profits are generally taxed at ordinary income rates (ranging from 10% to 37%), whereas long-term capital gains benefit from preferential rates of 0%, 15%, or 20%. For high earners, this spread can reach 17 percentage points, fundamentally altering net returns.

The difference between investing and trading becomes starkly clear when calculating the impact of this tax math. For example, a trader with a $100,000 salary who generates $50,000 in short-term gains may face a marginal federal rate of 24% to 32%, with state taxes potentially adding another 5% to 10%. This brings the combined tax burden to nearly 40% of all gains.

Investor holding positions over one year pays maximum 20% federal long-term capital gains tax, often 15% or even 0% for lower income levels. For identical $50,000 gain, investor keeps $40,000 to $50,000 after tax while trader keeps $30,000 to $35,000.

Compounded over decades, this tax differential produces hundreds of thousands in wealth difference even when gross returns are identical.

Transaction Cost Accumulation

Trading frequency multiplies costs that appear insignificant individually but compound devastatingly:

Commission costs: Even at $0 nominal commission, payment for order flow, wider spreads on frequent trades, and slippage during execution create hidden costs averaging 0.1% to 0.3% per trade.
Bid-ask spreads: Difference between purchase and sale price represents immediate loss. Stock with $0.05 spread on $50 price costs 0.1% each direction, totaling 0.2% round-trip.
Market impact: Larger orders move prices unfavorably during execution. This matters less for small retail traders but still creates slippage on volatile names.
Platform fees: Some brokers charge monthly fees, data fees, or margin interest that traders pay but long-term investors avoid.

Investor making 4 trades annually pays these costs 4 times. Trader making 200 trades annually pays 50 times more in transaction costs, even before considering tax differential.

Mathematical comparison shows impact clearly:

Long-term investing: Average annual return 7% to 10% inflation-adjusted, tax rate 0% to 20% on long-term capital gains, transaction costs low from infrequent trading
Active trading: Targeted annual return 10% to 20% rarely sustained, tax rate 10% to 37% on ordinary income, transaction costs high from commission multiplication

Trader targeting 15% gross must achieve approximately 22% to 25% gross return to match investor’s 10% net return after taxes and costs.

The Behavioral Tax Nobody Calculates

Traders sell winners 50% faster than they cut losers. This behavioral pattern, called disposition effect, creates invisible tax on returns that compounds damage from explicit costs.

This bias means traders systematically realize small gains quickly while holding losing positions hoping for recovery. Result is portfolio accumulating losers while eliminating winners, exact opposite of optimal strategy.

Mathematical impact exceeds obvious. Trader who cuts winners at 15% gain but holds losers to 30% loss before capitulating needs 75% win rate just to break even. Achieving 75% win rate consistently is essentially impossible.

Investor holding positions multiple years allows winners to compound while tax deferral adds additional benefit. Amazon investor who bought at $100 and holds to $3,000 over decade pays tax once on $2,900 gain. Trader who bought at $100, sold at $150, bought at $140, sold at $180, repeated pattern pays tax on every gain while never capturing full appreciation.

Behavioral costs don’t appear on brokerage statements but destroy wealth as effectively as explicit fees.

Emotional Load and Decision Fatigue

Active trading demands constant attention, rapid decisions under pressure, and emotional resilience during drawdowns. This psychological burden represents real cost even when not financially quantifiable.

Trader monitoring positions throughout day experiences stress spikes with each adverse price movement. Cortisol elevation, sleep disruption, and mental exhaustion accumulate. Quality of life degradation has value even if not measured in dollars.

Decision fatigue from evaluating dozens or hundreds of trades monthly depletes mental resources needed for career advancement, relationship maintenance, and health management. Investor making quarterly rebalancing decisions preserves mental energy for higher-value activities.

Psychological sustainability matters enormously for long-term outcomes. Strategy requiring superhuman discipline and stress tolerance fails regardless of theoretical profitability because humans cannot maintain those standards indefinitely.

The Profitability Rate Differential

Only 1% of traders succeed over five years according to research tracking thousands of accounts. This contrasts sharply with long-term investors where majority achieve positive returns by simply holding diversified portfolios through market cycles.

This profitability differential doesn’t reflect intelligence or education differences but structural advantages favoring investors:

Time for compounding: Decades of uninterrupted growth allow small annual returns to become large absolute sums through exponential compounding.
Alignment with economic growth: Long-term investors capture economy’s productivity improvements as companies grow earnings and expand over years.
Reduced behavioral interference: Fewer decisions mean fewer opportunities for emotional mistakes that destroy capital.
Tax deferral benefits: Unrealized gains compound tax-free until eventual sale, providing mathematical advantage over realizing gains annually.
Lower stress enabling better decisions: When decisions are infrequent and low-pressure, quality improves compared to rapid-fire trading choices.

These structural advantages explain why passive investors achieve success rates inverse to active traders despite requiring less knowledge and effort.

When Trading Makes Sense

Rare scenarios exist where trading approach might be justified despite overwhelming statistical disadvantages:

Professional dedication with adequate capital: Treating trading as full-time career with $100,000+ starting capital, professional infrastructure, and accepting that 99% odds favor failure.
Specific expertise in niche market: Deep knowledge in particular sector or instrument creating legitimate informational advantage over other participants.
Hedging existing exposure: Business owner trading industry-related instruments to offset operational risks faces different calculus than speculative trader.
Small speculative allocation: Dedicating 5% of portfolio to active trading while maintaining 95% in long-term investments satisfies desire for activity without risking financial security.

For overwhelming majority, honest assessment reveals that trading appeal stems from entertainment value and ego gratification rather than genuine edge capable of overcoming structural disadvantages.

The Compounding Time Advantage

Tax treatment creating up to 17 % point differences between short-term and long-term rates fundamentally changes investing versus trading mathematics. With traders selling winners 50% faster than losers due to behavioral bias, transaction costs multiplying through frequency, and only 1% achieving five year profitability, structural disadvantages prove insurmountable for overwhelming majority. Long-term investors benefit from compounding over decades, alignment with economic growth, tax deferral, and reduced behavioral interference, explaining why passive approaches succeed where active trading systematically fails despite requiring less knowledge and effort.

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Amendments Strengthening South Africa’s Voluntary Exclusion System.

March 6, 2026

Close up of male hand holding smartphone with online sports bets on screen while watching football match at home,

Pretoria, South Africa — 06 March 2026 — Betting.za.com, a leading South African information site for online betting and gambling, has welcomed the publication of draft amendments to the National Gambling Regulations, 2004 in Government Gazette No. 54106 (10 February 2026), issued by the Department of Trade, Industry and Competition under Government Notice R. 7113.

The amendments focus on improving how South Africa’s Voluntary Exclusion Programme is administered and enforced through the National Register of Excluded Persons, alongside updates to technical rules related to gambling machine re-certification.

“Stronger, clearer processes around voluntary exclusion are an important part of player protection,” said Dennis Kumar, lead betting expert at Betting.za.com. “Anything that makes it easier to exclude, harder to bypass exclusion, and clearer for licensed operators to implement should be supported — because gambling should always stay safe, controlled, and within limits.”

What the Gazette Proposes

1) A clearer way to register for voluntary exclusion

Under the proposed wording, a person who wishes to be registered as an excluded person must submit a notice to the National Gambling Board (the “Board”) in hard copy or electronically using Form NGB 1/1. The notice must include, at a minimum, a recent passport-sized photograph or a digital colour photo with a stated minimum file size.

2) Tighter timelines for handling exclusion notices

The Gazette sets out specific timelines for processing and implementation:

Operators must submit the notice to the Board on the day they receive it.
The Board must capture the form within five days (excluding weekends and public holidays) and transmit a copy to licence holders and provincial licensing authorities.
Operators must prepare and implement administrative processes within five days (excluding weekends and public holidays) after receiving the notice.
A notice takes effect 10 days after the date it is submitted to the Board.

3) Stronger internal control expectations for enforcement

The draft amendments add explicit duties related to internal controls, including that licence holders must submit internal control measures to their provincial licensing authority within 90 days after the regulations come into operation, aimed at effectively enforcing exclusion measures within gambling venues and controlling non-participation by excluded persons. Provincial licensing authorities must then submit provincial registers and these internal control measures to the Board.

4) Updated re-certification timing for gambling machines and devices

The Gazette also proposes changes to the timing rules for re-certification of technical amendments to gambling machines and devices, tied to the letter of certification timeline, including a 24-month window in specified circumstances.

5) Updated forms substituted into the Regulations

The Gazette substitutes Forms NGB 1/1 and NGB 1/2, with the updated forms included in the annexure.

What This Means for Players

For players, the most important takeaway is clearer access to voluntary exclusion and stronger enforcement once a person chooses to self-exclude.

Voluntary exclusion is a formal “opt-out” from gambling

If someone feels they are at risk — or they want a firm barrier in place — voluntary exclusion is a formal way to have their details added to the National Register of Excluded Persons, which is accessible to provincial licensing authorities and licensed operators for enforcement.

What happens after you register

The updated Form NGB 1/1 explains that once accepted:

You are excluded from designated gambling areas nationally
Your name is included on the Register used by regulators and licensed operators
You are not permitted to gamble while you remain on the Register.

If you gamble while excluded

The form also notes that gambling during exclusion is in contravention of the exclusion procedures, and any winnings accrued during that period may be forfeited and remitted to the Board.

Support is referenced directly in the official forms

The annexure references the National Responsible Gambling Programme (NRGP) and includes the toll-free helpline 0800 006 008, as well as an SMS/WhatsApp line shown on the form.

What This Means for Licensed Operators and Regulators

While voluntary exclusion begins with an individual’s decision, the Gazette places emphasis on how quickly and consistently the system is implemented across the market:

Same-day escalation by operators to the Board after receiving a notice.
A defined capture-and-distribution timeline for the Board (five days, excluding weekends and public holidays).
Mandatory operator administration within five days, reinforcing that exclusion is not only recorded but operationalised.
Formal internal control measures are submitted through provincial licensing authorities, strengthening accountability and auditability of enforcement.

Betting.za.com: Supporting Safer, Secure Gambling in the Legal Market

Betting.za.com publishes independent, plain-language guidance across betting and online casinos topics and focuses coverage on licensed operators as part of its broader commitment to safer play and informed decision-making.

“Our mission is to be South Africa’s most reliable and complete source of online betting and casino information,” said Kumar. “That includes making regulatory updates understandable, highlighting practical player protections like exclusion tools, and ensuring readers know where to find help when gambling stops being fun.”

About Betting.za.com

Betting.za.com is South Africa’s trusted source for honest, expert betting and casino information. Led by betting expert Dennis Kumar, the site publishes independent reviews, guides, and industry updates designed to help South Africans make informed choices and prioritise safety.

Responsible gambling support: NRGP toll-free helpline 0800 006 008

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New NZ Gambling Laws, Launches ‘Fair Play’ Audit to Protect Kiwis

March 6, 2026

WELLINGTON, NEW ZEALAND – March 6, 2026 – As New Zealand prepares for the most significant regulatory overhaul in its digital gambling history, the nation’s leading independent casino comparison site, PlayCasino.co.nz, has announced a sweeping “Fair Play” audit of its entire platform. The initiative is designed to protect Kiwi players from predatory offshore promotions as the country transitions to a strict 15-license regulated market.

Under the new Online Casino Gambling Bill, the unregulated offshore “grey market” will officially end on December 1, 2026. From that date, only 15 government-approved operators will be legally permitted to offer services to New Zealanders. In response, PlayCasino.co.nz is actively updating its platform to ensure players are shielded from desperate offshore operators trying to lock in users with deceptive sign-up offers before the deadline.

Navigating the End of the Unregulated ‘Grey Market’

The incoming legislation introduces stringent harm-minimization rules overseen by the Department of Internal Affairs (DIA), including a strict $100 cap on inducements, plain-language terms and conditions, and a mandated 4% Gross Gaming Revenue (GGR) community funding guarantee.

While these changes are a massive win for consumer protection and local grassroots sports, the transition period has left many Kiwi players confused about which platforms are safe to use right now. PlayCasino.co.nz’s new audit bridges this gap by highlighting only the operators that are already demonstrating a commitment to these incoming 2026 regulatory standards.

Protecting Players Seeking a No Deposit Bonus

A no deposit bonus remains the most sought-after incentive for New Zealanders looking to trial a new online casino without risking their own funds. However, in the dying days of the grey market, some unregulated offshore platforms are weaponizing these offers. They attract players with seemingly generous cash drops, only to bury impossible 100x wagering requirements, hidden withdrawal limits, or fast-expiring time limits deep within the fine print.

Through the “Fair Play” audit, PlayCasino.co.nz guarantees that any no deposit bonus featured on the site is evaluated for absolute clarity. The review team manually tests these bonuses to ensure players understand exactly what is required to clear their funds, flagging any operator that utilizes the hidden regulatory traps the NZ government is actively trying to eliminate.

Securing Fair Free Spins in a Mobile-First Market

As mobile gaming continues to dominate the local market, promotional offers tied to digital pokies have skyrocketed. Free spins are frequently bundled into welcome packages, but not all spins are created equal. Many offshore casinos restrict these spins to low-RTP (Return to Player) games or cap the maximum winnings at frustratingly low amounts.

PlayCasino.co.nz’s audit rigorously scrutinizes these mobile-specific promotions. The platform actively verifies that any free spins awarded to players come with reasonable, wager-friendly terms and are eligible for high-quality games. This ensures the promotions align with the consumer protection spirit of the incoming government legislation, rather than acting as a deceptive lure.

Strict New Structure and Content Requirements for Casino Reviews

To enforce these new protections, PlayCasino.co.nz has proactively overhauled the strict structure and content requirements for all of its online casino reviews. Moving forward, every review published on the platform must adhere to a standardized format that forces transparency. Operators are now graded heavily on the clarity of their bonus terms, their responsible gambling tools, and their readiness to comply with the DIA’s new licensing framework.

“The days of offshore casinos hiding predatory wagering requirements deep in their terms and conditions are over,” said Terri Radford, Head of Content at PlayCasino.co.nz. “With the grey market closing, some overseas operators are making aggressive last-ditch efforts to lock in players. We fully support the government’s new framework, which is why our new review standards ensure we only highlight casinos that treat Kiwis fairly right now.”

PlayCasino.co.nz is urging all New Zealanders currently playing on offshore sites to review their active accounts, cash out pending balances from non-compliant platforms, and utilize the new “Fair Play” review hub to find operators actively preparing for local licensure.

For more information, to access the “Fair Play” approved casino list, or to read the updated review guidelines, visit https://www.playcasino.co.nz/.

About PlayCasino.co.nz: PlayCasino.co.nz is New Zealand’s premier destination for independent, expertly crafted online casino reviews and industry news. Dedicated to player safety and transparent gaming, the platform equips Kiwis with the data, guides, and trusted operator recommendations needed to navigate the digital gambling landscape securely.

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Spain Rejects Trump Trade Threat Amid Dispute Over Military Bases

March 5, 2026

Spanish Prime Minister Pedro Sánchez criticized the ongoing U.S. and Israeli strikes on Iran, calling the escalating conflict in the Middle East a “disaster” and warning against repeating past military mistakes.

Sánchez spoke after U.S. President Donald Trump threatened to cut off trade with Spain. The warning came after Madrid refused to allow two jointly operated air bases in Spain to be used for the strikes against Iran.

During a White House news conference, Trump sharply criticized Spain’s position, saying the country had been “terrible” and suggesting the United States could halt trade ties in response.

In a televised address, Sánchez defended Spain’s stance and urged caution. He warned that wars often begin through a chain of miscalculations and unforeseen events, arguing that leaders must avoid decisions that could trigger wider conflict. Spain’s government summarized its position with a clear message: “No to war.”

Sánchez also drew parallels to the early 2000s invasion of Iraq, saying Europe must learn from past conflicts and avoid repeating similar mistakes.

The dispute has also revived tensions within the alliance led by the North Atlantic Treaty Organization. Trump again criticized Spain for failing to meet NATO’s defense spending target of 5% of gross domestic product.

Meanwhile, Scott Bessent, the U.S. Treasury secretary, accused Spain of being uncooperative during the launch of the U.S. military operation against Iran and argued that delays in using the bases could put American lives at risk.

The European Union has since expressed support for Spain, with António Costa reaffirming the bloc’s solidarity and commitment to international law.

Related Readings: