By Jefferson Dafydd
Twenty years ago, information was one of the greatest competitive advantages in sports business.
Executives who consistently outperformed their peers often knew something others didn’t. They maintained stronger industry relationships, possessed deeper institutional knowledge, understood emerging market trends before they became obvious, or simply had access to better information. Experience and information were closely intertwined, and together they shaped everything from sponsorship strategy and ticket pricing to expansion planning and media negotiations.
That world no longer exists.
Today, information has become abundant. Artificial intelligence can summarize research reports in seconds. Competitive sponsorship activity can be monitored in real time. Consumer behavior is tracked across countless digital touchpoints. Industry databases provide benchmarking that once required months of manual research, while sophisticated analytics platforms generate dashboards that measure nearly every aspect of a sports organization’s commercial performance.
For the first time in sports industry history, access to information is no longer the differentiator.
That reality represents one of the most significant shifts in sports business since the widespread adoption of customer relationship management platforms more than two decades ago. While much of the industry’s attention has focused on the rapid evolution of artificial intelligence, AI itself is not the transformation. It is simply accelerating a much larger change already underway.
The real transformation is that information has become increasingly commoditized.
This distinction matters because organizations continue to approach technology as though the objective is collecting more data. New software promises better dashboards. AI promises faster research. Customer platforms promise richer fan profiles. Every technology investment generates another stream of information, yet many organizations continue to struggle with the same strategic questions they faced years ago. How do we grow revenue? Which sponsors represent the greatest opportunity? Where should we invest? Which markets deserve expansion? Why are comparable organizations outperforming us despite operating under similar conditions?
Technology has made it dramatically easier to gather answers.
It has not necessarily made organizations better at asking the right questions.
That may sound counterintuitive at a time when artificial intelligence dominates nearly every technology conversation. Yet history suggests that transformative technologies rarely create lasting competitive advantage on their own. Instead, they fundamentally change where competitive advantage is found.
The internet made information universally accessible. Mobile technology placed that information into everyone’s pocket. Cloud computing eliminated barriers to collaboration. Artificial intelligence is now democratizing analysis itself.
Each technological leap has followed a similar pattern. As access expands, scarcity disappears. And when scarcity disappears, value shifts somewhere else.
Sports organizations are now entering precisely that moment.
The organizations that create the greatest enterprise value over the next decade will not simply be those with the newest technology or the largest software budgets. Nor will they necessarily be those employing the largest analytics departments. Increasingly, competitive advantage will belong to organizations that can transform information into consistently better commercial decisions.
That requires something fundamentally different than simply buying another platform.
It requires building an organizational capability that connects technology, market intelligence, operational experience, and strategic judgment into a single decision-making process. Artificial intelligence becomes one component of that ecosystem—not the centerpiece. Data becomes the raw material rather than the finished product. Technology evolves from a collection of software subscriptions into the infrastructure that supports smarter leadership.
For emerging leagues and Growth Sports organizations, this shift matters even more. Unlike established major league properties, they cannot afford disconnected systems, duplicated technology, or lengthy experimentation. Every investment must contribute directly to commercial progress because resources are finite and the margin for error is considerably smaller.
Ironically, that constraint may become their greatest advantage.
Without decades of legacy systems and entrenched operating practices, many Growth Sports organizations can build modern commercial infrastructure from the ground up. Rather than replicating the technology environments of larger organizations, they can design integrated operating models that combine data, artificial intelligence, market intelligence, and experienced leadership from the very beginning.
The future of sports business will not belong to the organizations that simply collect the most information.
It will belong to those who understand how to transform information into intelligence—and intelligence into action.
If information is no longer scarce, then the obvious question becomes: What replaces it as the source of competitive advantage?
The answer is not artificial intelligence. Nor is it another software platform.
Competitive advantage increasingly depends on an organization’s ability to turn information into coordinated commercial action. That may sound like a subtle distinction, but it represents a profound shift in how sports organizations should think about technology.
For years, organizations largely measured digital transformation by implementation. Organizations invested in CRM systems, ticketing platforms, sponsorship software, marketing automation, data warehouses, and business intelligence dashboards. Success was often defined by whether the technology had been deployed, integrated, and adopted by staff.
Today, that is merely the starting point.
Modern sports organizations possess an unprecedented volume of information. They understand who their customers are, how frequently they attend events, what they purchase, how they interact with digital content, and increasingly, how those behaviors change over time. Sponsorship teams can monitor category activity across the industry. Marketing departments can segment audiences with extraordinary precision. Ticketing executives can forecast demand with increasing confidence. Artificial intelligence now accelerates nearly every stage of research, planning, and execution.
Yet despite these advances, technology often remains organized by department rather than by decisions.
The ticketing department has its systems. Sponsorship has its own tools. Marketing maintains separate platforms. Finance builds independent reporting models. Valuable insights exist throughout the organization, but they frequently remain disconnected from one another. Executives receive more reports than ever before, yet many still struggle to answer the questions that matter most: Where should we invest? Which revenue opportunities deserve greater attention? Which commercial initiatives will generate the greatest long-term enterprise value?
Technology alone cannot answer those questions because software doesn’t set priorities.
Leadership does.
That is why the next generation of successful sports organizations will increasingly resemble intelligence organizations rather than simply data-driven organizations. Instead of viewing technology as a collection of independent applications, they will begin treating it as a connected operating environment where every platform contributes to a broader understanding of the business.
Imagine the difference.
A sponsorship executive is preparing for a meeting with a prospective partner. Rather than relying solely on personal research, the organization draws upon sponsorship intelligence, first-party fan data, attendance trends, demographic insights, competitive partnerships, AI-assisted market research, historical activation performance, and internal benchmarking. What once took days of preparation is now available in minutes—not because AI replaced the executive, but because the organization’s technology ecosystem assembled the relevant intelligence in a meaningful way.
The executive’s role changes dramatically.
Less time is spent gathering information.
More time is spent interpreting it.
The same transformation is occurring throughout commercial operations.
Ticketing professionals are moving beyond historical sales reports toward predictive demand modeling and dynamic pricing recommendations. Marketing teams are evolving from mass communication to individualized engagement driven by behavioral signals. Partnership departments are identifying emerging categories before they become saturated. Executive leadership is beginning to evaluate commercial performance not simply against last year’s budget, but against comparable organizations, evolving consumer trends, and broader market conditions.
In every case, technology is shifting from an administrative function to a strategic capability.
Artificial intelligence accelerates that evolution, but it does not complete it.
The organizations creating the greatest value combine four distinct forms of intelligence.
The first is operational intelligence—internal information generated daily through ticketing systems, CRM platforms, sponsorship sales, digital engagement, and financial reporting.
The second is market intelligence—an understanding of what is happening outside the organization, including sponsorship activity, participation trends, consumer behavior, media consumption, investment patterns, and competitive positioning.
The third is benchmarking intelligence—the ability to compare performance against similar organizations, identify best practices, and distinguish temporary fluctuations from meaningful structural trends.
Finally, there is human intelligence—the experience, judgment, creativity, and strategic thinking that no software platform can replicate. It is the ability to recognize nuance, understand relationships, evaluate risk, and make decisions in environments where perfect information will never exist.
Artificial intelligence strengthens each of these forms of intelligence, but it does not replace them. In fact, as AI reduces the time required to gather and organize information, the value of experienced leadership increases rather than declines. When information becomes abundant, judgment becomes scarce.
That may be the defining paradox of the AI era.
The organizations that thrive will not be those that automate the greatest number of tasks. They will be those who create better decision-making environments for the people leading their businesses.
Technology, in other words, is no longer the destination.
It is the infrastructure that allows a better strategy to emerge.
This evolution extends well beyond the front offices of sports organizations. It is also reshaping the way expertise itself is delivered.
For decades, the consulting industry has operated under a relatively straightforward model. Clients hired experienced advisors who gathered information, conducted interviews, analyzed the business, and returned weeks later with recommendations. The quality of the engagement largely depended on the consultants’ experience and the time they could dedicate to research and analysis.
That model produced valuable work, but it was built for a world in which information was difficult to obtain.
Today, information is abundant.
Artificial intelligence can synthesize thousands of pages of research in minutes. Industry databases provide unprecedented visibility into sponsorship activity, audience behavior, participation trends, investment patterns, and competitive landscapes. Benchmarking that once required months of manual analysis can now be generated almost instantly. Commercial diagnostics can be standardized without becoming generic, allowing organizations to spend less time assembling facts and more time interpreting them.
The implication is significant.
The future of consulting will not belong to the firms that simply accumulate the most information. It will belong to those who organize information into repeatable frameworks, combine it with experienced judgment, and help clients make better decisions more quickly than ever before.
In many ways, the consulting profession is experiencing its own Moneyball moment.
When Moneyball challenged conventional baseball thinking more than two decades ago, it did not argue that scouts no longer mattered. Quite the opposite. It demonstrated that experienced evaluators became even more valuable when they had access to better information and better analytical tools. The organizations that consistently outperformed the market were not those that relied exclusively on intuition or exclusively on analytics. They succeeded because they combined both.
Commercial strategy is following the same path.
The most successful advisors of the next decade will not be those who know the most facts. They will be those who know how to ask better questions, interpret increasingly complex information, and apply decades of operating experience to situations where algorithms alone cannot provide the answer.
That philosophy has shaped how we built Team Advisory Group.
Rather than viewing technology as a replacement for experienced operators, we see it as an amplifier of their expertise. We developed our Growth Sports Intelligence™ platform, the Growth Sports Index™, commercial diagnostics, benchmarking methodologies, and AI-assisted research processes around a single objective: enabling experienced sports executives to spend less time gathering information and more time helping organizations make smarter commercial decisions.
Technology accelerates preparation.
Experience provides context.
Judgment creates value.
That distinction matters more as Growth Sports matures. Emerging leagues, governing bodies, and new sports properties often operate with lean staffs, compressed timelines, and limited resources. They cannot afford lengthy discovery processes or disconnected technology investments. They need practical insights that are informed by data, strengthened through benchmarking, and refined by people who have built commercial organizations before.
The opportunity is not to replicate the operating models of the major leagues.
It is to build something more agile from the very beginning.
Growth Sports organizations have a unique advantage because they are not burdened by decades of legacy systems or entrenched business practices. They can design modern commercial infrastructure around integration rather than fragmentation, creating organizations where technology, data, and leadership work together from day one.
As artificial intelligence becomes increasingly accessible, one reality will become impossible to ignore: technology itself is rapidly becoming a commodity. Every organization will have access to similar AI tools. Every organization will be able to generate reports, automate workflows, summarize research, and analyze data faster than ever before.
Those capabilities will become the baseline—not the differentiator.
The organizations that separate themselves will cultivate superior judgment, build stronger commercial frameworks, and create cultures that turn information into action.
That is the next frontier of sports technology.
Not artificial intelligence.
Intelligent organizations.
The conversation over the next decade should not center on which software platform is the most powerful or which AI model produces the fastest output. Those questions will keep evolving as technology advances.
The more enduring question is far simpler:
How do we build organizations that consistently make better decisions?
The answer will define the next generation of winners across the sports industry.
Jefferson Dafydd is a senior sports business executive and Senior Advisor, Growth Sports at Team Advisory Group (TAG). His work directly supports the commercial development of emerging sports, fan ecosystems, and the business infrastructure needed to build sustainable sports properties.
