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based content. To navigate these issues,
the industry must balance AI’s efficiency
with human creativity, establish responsi-
ble frameworks, and uphold transparency
to maintain trust and content efficacy.
Jordan Thomas: Often, a lack of tech-
nical expertise and concerns about job
displacement may hinder full-scale adop-
tion, however, this can be overcome by
preparing and providing insightful training
to workforces. One misconception is often
the barrier of cost and complexity of inte-
grating AI-driven tools. However, this isn’t
always the case. Solutions like QuickLink
StudioEdge utilizes AI-technology pow-
ered by Nvidia to enhance video and au-
dio quality of remote guest contributions,
offered at no additional cost, and can be
seamlessly integrated into workflows.
Ken Kobayashi: One of the biggest bar-
riers in camera operation is the “skills
transfer.” Customers already have their
own established or inherited skills, and
sometimes they don’t want to use auto-
mated features such as auto-focusing. If AI
cameras have room to train or implement
customer’s skills about PTZ speed/fram-
ing etc. through deep-learning algorithms
in the future, they would be more widely
used in broadcast production.
How can collaboration between tech
developers and broadcasters drive
innovation?
Stefan Lederer, CEO and co-founder,
Bitmovin: Collaboration across the media
technology space is the key to identifying
the unique challenges and opportunities
that AI can bring the industry. Always a
firm believer in the power of collaboration
to drive the industry forward, Bitmovin
launched the AI Accelerator Community in
November 2024 to help advance AI-led in-
novations in the media and entertainment
technology sector. The initiative provides
industry professionals with a collaborative
space where they can come together to
exchange ideas, share insights, and break
new ground in media technology.
Bob Caniglia: Direct feedback and col-
laboration spurs innovation by combining
technical expertise with real-world pro-
duction insights to create meaningful solu-
tions. When broadcasters share hands-on
feedback, developers can incorporate that
feedback into their product design pro-
cess to better address industry challenges
and enhance workflow productivity. This
joint effort enables the creation of ad-
vanced technologies tailored specifically
to evolving broadcast needs, driving prog-
ress and creativity.
Costa Nikols: Collaboration thrives
when broadcasters and technology part-
ners work hand in hand to address re-
al-world production challenges. Technolo-
gy for technology’s sake never really solves
the issues that matter. Enabling greater
scale, creativity or efficiency, and having a
pinpoint use-case focus, are always more
important than inventing something brand
new and hoping it sticks.
Steve Taylor: I would say that collabo-
ration between users and technology ex-
perts is absolutely vital for any product
ideation and creation process in any in-
dustry. It is very rare that the requirements
for a new product or workflow are so well
defined in advance that a tech developer
can go away, build it, and then present it as
a fait accompli. Experimentation, iteration
and openness to failure, which is a learn-
ing experience, is crucial to help produce
the best outcome for a customer’s needs
in a more effective way.
Sam Bogoch, CEO, Axle AI: It’s an amaz-
ing time for tech developers in this indus-
try, as there is an unprecedented tidal
wave of AI and machine learning technol-
ogy occurring which can be funneled into
making video workflows better. If any-
thing, it takes a new approach focused on
filtering the almost unlimited possibilities
into focused solutions targeting real-world
problems that broadcasters face. It’s the
collaboration between broadcasters and
tech developers that will ensure a payoff
today, as well as faster and more efficient
innovations tomorrow.
Noa Magrisso: By working closely, de-
velopers gain a deeper understanding of
broadcasters’ specific challenges, enabling
them to create tailored AI solutions. De-
velopers bring specialized technical skills,
such as expertise in AI and data analytics,
which can address broadcasters’ unique
challenges in ways they may not have the
resources to explore independently. Com-
bining developers’ technical knowledge
with broadcasters’ insights, allows them to
co-create tailored solutions that enhance
workflows and content delivery.
What is missing in the conversation
on AI in broadcast?
Zeenal Thakare, SVP, enterprise solu-
tions architecture, Ateliere: We must con-
sider ethical implications and bias in algo-
rithms, especially since there is a lack of
transparency in how AI algorithms make
decisions. In the world of “fake news” pre-
serving integrity and trust is paramount,
especially with news networks. On those
lines, security and data concerns become
critical issues that need attention. Overall,
the conversation must shift from short-
term benefits to the more long-term struc-
tural impact of this technology on the in-
dustry and the business model itself.
Jordan Thomas: In the conversation
of AI in broadcast, the focus is often on
technical capabilities, overlooking the
human aspect, such as preparing staff for
AI-driven workflows or addressing ethical
concerns. Tools that utilize AI-technology,
like QuickLink StudioEdge and Studio-
Pro, need to be complemented by indus-
try-wide discussions on governance, fair-
ness and inclusivity.
Costa Nikols: AI offers tremendous po-
tential but many practical questions are
still to be addressed. Broadcasters need to
invest in robust data governance to ensure
accuracy and ethical usage, particularly
when dealing with generative models. The
industry also needs clear standards and
frameworks for handling intellectual prop-
erty and copyright issues surrounding
AI-generated content. Expect grounded
debate, more practical discussions — and
modest, use-case driven adoption in 2025.
Steve Taylor: I would say there is defi-
nitely a lot of conversation about AI in
broadcast, but perhaps still largely on how
it can present risks. We need more posi-
tive examples that start to build a trusted
foundation for the technology. Whilst we
are still talking about AI specification, it
will remain the focus rather just another
tool for the solution.
Continued from previous page
It’s an amazing time for tech developers in this
industry, as there is an unprecedented tidal wave
of AI and machine learning technology occurring
which can be funneled into making
video workflows better.