IBC2026 is behind us, and after four days of conversations on the show floor, I’ve had some time to reflect on what I actually heard and saw, not just what we expected going in.
AI was not simply a theme at this year’s show. It was the defining conversation. Virtually every person who walked through our stand — customers, partners, even suppliers — wanted to talk about it. Where it’s headed, what it can realistically do, and what steps they need to take now. That level of engagement, across the board, tells you something important about where this industry is in its thinking.
Here are the three observations I’m carrying home.
AI-enabling your workflows is not the same as rebuilding them
One of the most important debates I had this week, and I had it more than once, was this: when organizations decide to embrace AI, should they refactor their workflows from the ground up, or should they AI-enable the workflows they already have?
A meaningful number of people I spoke with were leaning toward starting over entirely. The reasoning is understandable. AI feels transformative enough to warrant a clean slate. But I question whether that instinct, if acted on, leads organizations where they actually want to go.
Here is what I’ve come to believe: most media and broadcast operations are well-functioning. They are producing content, running channels, serving audiences. The pressure, and I heard this consistently throughout the week, is to do more with less. That pressure is real. But I’m not sure the answer to it is walking away from operational frameworks that already work.
A more effective approach, and one I found myself advocating for repeatedly, is to start with a clear-eyed view of what you are trying to accomplish, examine the workflows you already have, and identify where AI can make them faster, smarter, and more efficient. AI-enabling a workflow rather than replacing it. The demonstrations our team ran at IBC were designed with exactly that in mind: practical, grounded in real operations, delivering value without dismantling what already works. People could see a clear path from where they are today to where AI can take them. That felt like the right conversation to be having.
Getting clear on roles today is the foundation for what comes next
One of the more useful frameworks I found myself returning to throughout the week is simply this: AI has a job, and people have a job. Getting that distinction right seems to me like one of the most valuable things an organization can work through right now.
AI excels at processing vast amounts of data quickly, recognizing patterns, and surfacing anomalies — the kind of work that is operationally critical but genuinely difficult for humans to do at scale. Monitoring a playlist days in advance to catch and correct mis-formatted media. Watching signal and network traffic for early indicators of a problem before it becomes a failure. Scanning years of operational data in seconds to identify what does not belong. These are things AI is well suited to do, and offloading them creates space for teams to focus on the work that requires expertise, judgment, and creativity, the things that are still fundamentally human. The strategic decisions, the editorial instincts, the campaign-level thinking, the complex problem-solving that comes from years of experience in this industry. That is where human contribution is irreplaceable, and where people’s time and energy should be directed.
That role clarity matters for a reason beyond efficiency. I think it is the foundation for something more important. The longer-term goal, and I believe the industry will get there, is a genuine partnership between people and intelligent systems, where each is actively contributing what it does best. Getting clear on roles today is what makes that possible down the road.
“A meaningful number of people I spoke with were leaning toward starting over entirely. The reasoning is understandable. AI feels transformative enough to warrant a clean slate. […] But I’m not sure the answer to it is walking away from operational frameworks that already work.”
AI enablement may require a decision you’ve been putting off
Both of the points above assume something important: that your organization is already in a position to engage with AI. For many of the people I spoke with this week, that conversation needs to start one step earlier.
AI operates on data. If a facility is still moving video and audio as SDI signals rather than IP, it may be more difficult to access the AI-enabled capabilities that generated so much excitement at IBC this year. The AI operates on data it can see and process. Signals in their baseband form are not that.
The conversation around IP migration has often been framed as a choice between two equivalent options. What I heard this week suggests it may be worth rethinking that framing. Moving to IP is fundamentally a move into the data domain, and for organizations that want to pursue meaningful AI adoption, that transition appears to be an important precondition. I spoke with a number of people this week who arrived viewing IP migration as a longer-term consideration. Several of them left thinking about it differently. It is worth asking now: when your leadership team asks what the organization is doing to take advantage of AI, will your infrastructure support a credible answer?
For those who have already made the move to IP, that groundwork is in place. For those still weighing it, the conversation around AI may be worth factoring in.
Closing thought
One comment from a customer this week has stayed with me. After working through one of our AI demonstrations, they said: “You are the only company that is making this make sense.” I am proud of that, not because it reflects well on us, but because it reflects the approach I think is right. Practical. Grounded. Focused on what organizations can actually do, starting now.
That is the conversation I intend to keep having. IBC reinforced why it matters.
“AI has a job, and people have a job. Getting that distinction right seems to me like one of the most valuable things an organization can work through right now.”
IBC2026 Highlights
IBC2026 brought the industry together for four packed days of conversations, demonstrations and new ideas. We showcased a full portfolio of Make TV and Monetize TV solutions — from production and playout to monetization, orchestration and practical applications of AI.