Reflections from IBC2026 on AI, Edge Infrastructure, and the Future of Digital Inclusion
By Dajiang Li
Today at IBC2026, I had the opportunity to join a panel discussion titled “AI-Powered Live Sports for the Mobile Generation,” where we explored how artificial intelligence is transforming the way sports content is produced, personalized, and monetized. AI is rapidly reshaping the media industry, turning what once required large production teams into software-driven workflows capable of generating highlights, localized versions, personalized feeds, and vertical video experiences at unprecedented scale.
As I left the stage, one thought stayed with me:
AI is making content creation easier than ever. But reaching users is becoming the new bottleneck.
For the past twenty years, the digital industry has largely focused on building more powerful compute, bigger clouds, and smarter algorithms. Today, we can generate almost unlimited content. Yet a more fundamental question remains unanswered:
Who actually receives that content? And perhaps even more importantly: Who gets left behind?
When people talk about AI, discussions often center around Silicon Valley, London, Singapore, Beijing, or other highly connected technology hubs.
Yet the next billion internet users will not come from these places.
They will come from cities and towns across Africa, the Middle East, South Asia, and other emerging regions where connectivity remains fragmented, expensive, or unreliable.
For years, the internet industry operated under an assumption that continental coverage equaled user coverage.
It does not.
A network map may show a CDN node in Johannesburg, Dubai, Singapore, or Frankfurt and declare an entire continent “covered.” But real users experience something very different.
A football fan in inland Africa. A gamer in a secondary Bangladeshi city. A student accessing AI-powered education platforms from a regional ISP in the Middle East.
Their experience is often determined not by continental presence, but by local connectivity.
The next phase of internet infrastructure will not be defined by how many countries appear on a coverage map. It will be defined by how deeply we reach into each market.
One of the privileges of working at EdgeNext is witnessing what it truly takes to build infrastructure in emerging markets.
Over the years, our engineers have spent countless hours travelling across the Middle East, North Africa, Sub-Saharan Africa, and South Asia.
Not just to major capitals. But to places many infrastructure vendors rarely visit.
While AI discussions often happen in conference centers, the real work frequently happens in carrier hotels, ISP facilities, data centers still under construction, and long meetings with local network operators.
Infrastructure is ultimately a human business. It is built through relationships, patience, and local commitment.
At EdgeNext, we have spent years investing in direct connectivity, local deployment, and ISP partnerships across emerging markets. These efforts have resulted in particularly deep coverage in regions such as MENA, Southeast Asia, and Africa, where traditional global internet architectures often have gaps. EdgeNext publicly states that its network includes more than 1,500 points of presence globally and extensive ISP partnerships aimed at improving last-mile performance in emerging markets.
This matters because the future internet will not be won by adding more compute in a few metropolitan regions. It will be won by reducing the distance between intelligence and users.
One of the key themes discussed during our IBC panel was the rise of mobile-native sports experiences.
The industry is moving from producing one feed to producing hundreds of content variants simultaneously.
However, each new content variant creates a new delivery challenge. A goal scored in a football match may trigger:
Within seconds. The real challenge becomes distribution.
AI can create the moment. Infrastructure determines whether users actually experience it.
This is why edge architecture becomes increasingly important. Not only for content delivery. But for real-time decision making. Routing traffic dynamically. Monitoring quality of experience. Optimizing delivery paths. Protecting content rights. And increasingly, executing AI inference closer to users.
The implications extend well beyond media.
Many people still associate AI primarily with chatbots or content generation. I believe the bigger opportunity lies ahead.
As inference moves closer to the edge, entirely new categories of applications become possible.
Imagine:
An autonomous factory where AI continuously analyzes equipment data in real time.
A large-scale IoT deployment where millions of devices make local decisions without depending on distant cloud regions.
A next-generation online game where every NPC behaves like an intelligent digital character rather than following scripted paths.
A retail environment where personalization happens instantly within the local market rather than through centralized processing.
Or healthcare systems that can analyze data locally while respecting data residency requirements.
These applications will require something different from today’s cloud-centric architectures.
They will require intelligence distributed across thousands of edge locations. Not merely connected. But embedded.
Throughout technology history, every major wave has moved closer to users.
Mainframes gave way to personal computers. Data centers gave way to cloud. Now AI is pushing us toward the next stage: distributed intelligence.
The greatest opportunity of the AI era may not be building the smartest model. It may be ensuring that intelligence can reach every market, every network, and every user. Including those that have historically been underserved.
Because when we talk about the next billion users, we are really talking about something larger than growth. We are talking about digital inclusion.
The ability for someone in Nairobi, Dhaka, Casablanca, Riyadh, Lagos, or a remote provincial town to access the same experiences, opportunities, and innovations as someone in New York, London, or Shanghai.
That is not merely a technology problem. It is an infrastructure challenge.
And in the AI era, infrastructure is once again becoming strategic. Not because it delivers content. But because it delivers opportunity.
The next billion users are already online. The question is whether our infrastructure is ready to reach them.
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