World Cup 2026: When Events Outgrow Spreadsheets
- Chris Howell
- 3 hours ago
- 11 min read
In my previous article on AI and the 2026 FIFA World Cup, I explored how technologies such as AI-assisted officiating, smart footballs, and advanced analytics are changing the tournament itself.
This time, I want to look at something different.
Because beneath the goals, highlights, and headlines sits a challenge that most fans will never see.
The 2026 FIFA World Cup is not just bigger than previous tournaments. It is dramatically more complex.
The World Cup's Real Challenge Isn't Football
When people think about the FIFA World Cup, they naturally think about football. They picture iconic goals, fierce international rivalries, packed stadiums, passionate supporters, and unforgettable moments that become part of sporting history.
For fans, the tournament is about what happens on the pitch.
For organisers, however, the football itself is often the simplest part of the equation.
Behind every match sits an enormous operational machine that must function flawlessly for weeks at a time. The World Cup is not just a sporting event. It is one of the largest temporary logistical operations in the world, requiring the coordination of people, infrastructure, technology, transportation, security, hospitality, media, and public services across multiple countries.
The 2026 FIFA World Cup will be the largest tournament in the competition's history. It will feature 48 teams competing across 104 matches in 16 host cities spread throughout the United States, Canada, and Mexico.
At first glance, the expansion may not seem dramatic. The tournament has grown from 32 teams to 48 teams and from 64 matches to 104. Those numbers appear manageable when viewed in isolation.
The reality is far more complex.
Every additional team brings players, coaches, analysts, medical staff, administrators, sponsors, media representatives, and thousands of travelling supporters. Every additional match creates new demands on transport networks, accommodation providers, security teams, broadcasters, and local authorities.
The impact multiplies rapidly.
A single team could play one match in Vancouver before travelling thousands of kilometres to another host city for its next fixture. Broadcasters must coordinate production teams across multiple countries and four different time zones. Airports must handle surges in passenger traffic. Hotels must accommodate fluctuating demand. Local transport systems must move tens of thousands of supporters safely and efficiently before and after matches.
Each element depends on the others. If transport systems experience delays, stadium operations can be affected. If accommodation forecasts prove inaccurate, local infrastructure may come under unexpected pressure. If weather conditions change, crowd management plans may need immediate adjustment.
The challenge is not simply one of scale. It is one of coordination.
The larger the tournament becomes, the more interconnected every decision becomes. Small disruptions can quickly create wider operational consequences if they are not identified and addressed quickly.
This is why technology has become such a critical part of modern tournament management.
The growing use of AI, advanced analytics, and real-time monitoring is not primarily about replacing people. It is about helping people manage a volume of information that would be impossible to process manually.
As events become larger and more complex, technology becomes less of a competitive advantage and more of an operational necessity.
When Forecasts Meet Reality
One of the most interesting lessons emerging ahead of the tournament is that forecasting remains incredibly difficult, even when organisations have access to vast amounts of data.
Travel companies, hospitality providers, airlines, local governments, and event organisers have spent years attempting to estimate the tournament's economic impact. Forecasts influence staffing decisions, infrastructure planning, inventory management, pricing strategies, and investment decisions.
Some projections suggest that visitor spending across host cities could exceed $8 billion during the World Cup period.
Those forecasts are based on sophisticated models that analyse historical tournament data, travel patterns, ticket sales, accommodation demand, economic indicators, and consumer behaviour.
Yet despite all of this information, reality has already begun to challenge expectations.
Although more than five million tickets have reportedly been sold, many hotels in the United States have experienced booking levels below initial forecasts. Some host cities appear to be attracting stronger demand than expected, while others are seeing slower growth.
This highlights a fundamental challenge with forecasting.
Forecasting is ultimately an attempt to predict human behaviour. Human behaviour is rarely predictable.
Supporters do not always book travel when analysts expect them to. Economic conditions can change rapidly. Exchange rates can influence affordability. Visa requirements can affect travel decisions. Political developments can alter consumer confidence. Even the performance of national teams can influence supporter behaviour.
Fans often delay making travel arrangements until the final stages of planning. Some repeatedly search for flights and accommodation without ever completing a booking. Others wait until they know their team's schedule before committing to travel.
This highlights an interesting example involving Argentine supporters. While they represented a relatively small proportion of confirmed bookings, they accounted for a much larger share of travel searches.
This distinction matters.
Search activity may indicate interest, but interest does not always translate into action. Organisations that rely too heavily on early indicators can easily overestimate future demand.
For businesses, this serves as an important reminder.
Forecasting tools are extremely valuable. They help organisations identify trends, allocate resources, and prepare for likely scenarios. They reduce uncertainty and improve decision-making.
However, they do not eliminate uncertainty altogether.
No forecasting model can perfectly account for every variable that influences human behaviour. Unexpected events will always occur. Consumer preferences will always evolve. Market conditions will always change.
The objective of forecasting is not to predict the future with complete accuracy. The objective is to make better decisions based on the best information currently available.
Successful organisations understand this distinction.
Rather than treating forecasts as fixed predictions, they treat them as informed estimates that must be continuously reviewed and updated as new information becomes available.
World Cup organisers appear to be taking exactly this approach. They are investing heavily not only in predictive capabilities but also in systems that allow them to monitor changing conditions and adapt quickly when reality differs from expectations.
Why Static Plans Break Down
Many organisations believe that creating a plan is the most difficult part of managing a complex operation.
In reality, maintaining the relevance of that plan is often far more challenging.
A plan represents a snapshot of assumptions at a particular moment in time. As circumstances change, those assumptions can quickly become outdated.
This is especially true during an event as large and dynamic as the FIFA World Cup.
A transport schedule that appears perfectly designed six months before the tournament may require significant adjustments once actual travel patterns emerge. A hotel demand forecast may become inaccurate following changes to visa policies or airline capacity. Crowd-management strategies may need to be revised because of weather conditions, public demonstrations, transport disruptions, or unexpected supporter behaviour.
The larger the operation becomes, the faster plans can lose relevance.
This creates a significant challenge for organisers. Traditional planning approaches often assume that enough preparation can eliminate uncertainty. Modern event management increasingly recognises that uncertainty cannot be eliminated entirely.
Instead, organisations must become better at responding to change.
This is one reason why real-time operational monitoring has become such an important component of major events.
Tournament organisers are not attempting to predict every possible issue before it occurs. That would be impossible. Instead, they are building systems that allow them to identify emerging problems quickly, assess their potential impact, and coordinate responses before those problems escalate.
This represents an important shift in thinking. The goal is no longer perfect prediction; the goal is operational awareness.
Organisers need visibility into what is happening across transport networks, venues, accommodation providers, security operations, and public infrastructure at any given moment. They need accurate information that allows them to make informed decisions quickly.
In many situations, understanding current conditions is more valuable than relying on assumptions made months earlier. A forecast may suggest what should be happening. Real-time data reveals what is actually happening.
As the scale and complexity of global events continue to increase, that distinction becomes increasingly important.
The organisations that perform best are often not those with the most detailed plans. They are the ones that can adapt most effectively when reality inevitably diverges from those plans.
The 2026 FIFA World Cup is likely to provide one of the clearest examples yet of this principle in action. Behind the excitement of the matches themselves will be a vast network of people, processes, and technologies working continuously to keep one of the world's most complex events running smoothly.
The football may capture the headlines, but the real story may be the operational intelligence required to make the tournament possible.
The Rise of the Digital Twin
One of the more interesting technologies supporting the 2026 World Cup is something most fans will never see.
Every host venue has been digitally scanned to create what is known as a digital twin.
In simple terms, a digital twin is a virtual version of a real-world environment. It combines a digital model of a physical location with live operational data, allowing organisations to monitor, analyse, and simulate events before they happen.
For World Cup organisers, this means every stadium can effectively exist in two places at once: in the real world and inside a software environment.
This creates some powerful possibilities.
Organisers can model crowd movements before supporters arrive. They can test how different entry routes affect congestion. They can identify potential bottlenecks around transport hubs, food concessions, security checkpoints, and exits. They can even simulate emergency scenarios to understand how people are likely to move through a venue under different conditions.
The value is not that the simulation perfectly predicts reality. The value is that it exposes weaknesses before they become real-world problems.
Think of it like a flight simulator for operations.
Pilots use simulators to prepare for situations they hope never occur. Tournament organisers are increasingly doing the same thing with stadiums, transport systems, and crowd-management plans.
What makes this particularly interesting is that the principle is no longer limited to organisations with World Cup-sized budgets.
Most small businesses will never create a digital replica of a stadium.
However, many businesses already use simplified versions of the same idea. A sales forecast, a staffing model, and a customer journey map are all forms of simulation. Even something as simple as asking, "What happens if demand increases by 25% next month?" is effectively a small-scale digital twin exercise.
The technology may differ, but the objective is identical: test assumptions before reality tests them for you.
As AI tools become more accessible, the gap between enterprise-level planning and small-business planning continues to narrow. The World Cup may represent the most advanced version of this concept, but the underlying principle is becoming increasingly available to organisations of every size.
Moving Millions of People
One of the greatest challenges facing organisers is surprisingly simple: getting people from one place to another.
The 2026 World Cup spans three countries, sixteen host cities, and thousands of kilometres of geography. Unlike previous tournaments held within a relatively compact area, this World Cup stretches across a significant portion of North America.
For teams, media personnel, sponsors, and supporters, travel is not a side issue. It is a core operational challenge.
A team could potentially travel from Vancouver in Canada to Monterrey in Mexico between matches. Supporters may fly between multiple cities during the tournament. Broadcasters and logistics teams must coordinate equipment, personnel, and resources across four time zones.
The complexity increases even further when multiple matches take place within a short period.
Kansas City, for example, expects hundreds of thousands of visitors and began transportation planning well in advance of the tournament. Dallas-Fort Worth authorities have already developed match-day traffic management strategies and encouraged flexible working arrangements to reduce pressure on transport networks.
These examples highlight an important reality. Transport planning is not simply about moving people; it is about managing demand.
Roads, railways, airports, and public transport systems all have finite capacity. When large numbers of people attempt to use those systems simultaneously, congestion becomes inevitable unless demand can be predicted and managed effectively.
This is where AI and data analytics become particularly valuable.
Travel patterns can be analysed in near real time. Traffic flows can be monitored continuously. Signal timings can be adjusted. Resource allocation can be modified based on actual demand rather than historical assumptions.
The goal is not perfection. The goal is to reduce friction. This lesson applies surprisingly well to business operations.
Many organisations face their own versions of transport bottlenecks. Customer enquiries arrive faster than teams can respond. Orders arrive faster than they can be processed. Projects compete for limited staff resources.
The underlying challenge is often the same: demand exceeds capacity.
The World Cup demonstrates how data can help organisations identify those pressure points earlier and respond more effectively.
Mission Control for the World's Biggest Football Tournament
Perhaps the clearest example of how modern operations are evolving is Lenovo's Intelligent Command Centre.
The easiest way to think about it is as a mission control centre for the entire tournament. Instead of relying on individual teams working in isolation, the Command Centre brings together operational data from all sixteen venues and surfaces information that decision-makers need to see quickly.
Crowd density, transport disruption, security alerts, venue issues, and operational bottlenecks can all be monitored from a single operational view.
Rather than forcing people to manually sift through huge volumes of information, the system summarises what matters most and highlights emerging risks before they become major problems.
This reflects a broader shift taking place across many industries.
Historically, organisations often collected large amounts of data without having an effective way to act upon it. Today, the challenge is less about obtaining information and more about filtering it.
Most organisations already have access to plenty of data, including sales reports, customer records, website analytics, operational metrics, and support tickets. The problem is rarely a lack of information. The problem is understanding which information requires attention right now.
The Intelligent Command Centre exists because tournament organisers cannot afford to wait for problems to become obvious.
The same principle applies to businesses.
A delayed project, declining sales trend, customer-service issue, or operational bottleneck is usually easier to resolve when detected early. Good monitoring systems do not eliminate problems. They shorten the time between a problem emerging and somebody noticing it.
That reduction in response time can often make the difference between a minor issue and a major disruption.
What Small Businesses Can Learn
At first glance, the technology supporting the 2026 World Cup may seem far removed from the reality of running a small business.
Most organisations do not need digital twins, continent-wide transport coordination, or command centres monitoring sixteen venues simultaneously.
However, the underlying lessons are remarkably transferable.
The first lesson is that forecasting is valuable but imperfect. The World Cup's organisers have access to sophisticated forecasting tools and vast amounts of data, yet they still face uncertainty. Small businesses should expect the same. Forecasts should inform decisions, not replace judgement.
The second lesson is that visibility matters. Many businesses focus heavily on planning while investing relatively little in monitoring. Yet the ability to identify problems quickly is often more valuable than creating increasingly detailed plans.
The third lesson is that complexity grows faster than expected. As organisations expand, the number of interactions between customers, staff, suppliers, systems, and processes increases rapidly. What worked perfectly at one stage of growth may become ineffective at the next.
Finally, the tournament demonstrates that AI works best as decision support.
Throughout the World Cup's operational ecosystem, technology is helping people process information, identify patterns, and surface risks. Human beings remain responsible for making decisions and accepting accountability for the outcomes.
That principle scales surprisingly well.
Whether you are managing a global sporting event or a growing local business, the goal is not to replace human judgement. The goal is to give people better information so they can make better decisions.
In many ways, that may be the most important lesson of all.
The 2026 World Cup is not becoming more AI-driven because people are fascinated by AI. It is becoming more AI-driven because the tournament has become too operationally complex to manage efficiently without it.
Increasingly, the same is becoming true for businesses of all sizes.
Final Thought
You do not need to run a World Cup to have a data problem.
You just need enough moving parts that instinct and spreadsheets are no longer giving you a clear picture.
That is when better data starts to matter.
And that is often where businesses begin their AI journey.
Many organisations know they want to use AI, but struggle to identify where it will create genuine value. They have data, processes, and operational challenges, but no clear roadmap for turning those into measurable outcomes.
Our AI Strategy Builder service is designed to solve exactly that problem.
Rather than jumping straight into tools and technology, it helps businesses identify opportunities, prioritise use cases, assess readiness, and build a practical AI roadmap aligned to their goals. The result is a clear strategy focused on solving real business challenges, not simply adopting AI for the sake of it.
Because whether you are coordinating a global sporting event or managing a growing business, success rarely comes from having more data.
It comes from knowing what to do with it.
If you're looking to move beyond spreadsheets, assumptions, and disconnected systems, AI Strategy Builder can help you create a structured plan for using AI where it matters most.