AI in Media & Broadcast – Professional Essentials Guide

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tedious tasks such as transcription, trans-

lation, and summarization. This not only

speeds up production but allows news

teams to focus more deeply on research

and improve accuracy and turnaround

time.

Bob Caniglia: Innovative AI-driven tech-

nologies are driving greater efficiency in

news gathering and reporting by automat-

ing repetitive tasks and optimizing work-

flows. AI tools, like automatic transcrip-

tion and smart sorting, enable journalists

to manage content faster and improve ac-

curacy under tight deadlines. This allows

news teams to dedicate more time to in-

depth reporting and delivering compelling

stories to their audiences.

What are the potential challenges of

integrating AI in newsroom workflows?

Peyton Thomas: While many may ar-

gue that integrating AI in the newsroom

removes human-manned jobs, I believe it

can be used to automate repetitive tasks

while creating an opportunity for end-us-

ers to be more creative and try things they

haven’t been able to do before.

Yang Cai: From a newsroom perspec-

tive, integrating AI can be challenging due

to concerns about maintaining journalis-

tic integrity and ensuring the accuracy of

AI-generated content. Compatibility with

existing newsroom systems and work-

flows may require significant technical

adjustments. There’s also apprehension

among journalists about balancing auto-

mation with editorial oversight and pre-

serving the human element in reporting.

Jordan Thomas: Adopting AI driven

technology within newsroom workflows

requires overcoming resistance to change

and ensuring seamless integration with

existing systems. Another fundamental

challenge is addressing ethical use of AI

and ensuring that it is not misleading view-

ers. This is particularly the case when it

comes to video and audio content that may

be altered by AI tools.

Steve Taylor: There are certainly two big

challenges that we hear about a lot. One is

the trust factor for the content workflow

— the question of whether information is

coming from a legitimate source or if it

was generated by AI? Second is whether

the output of AI is breaking any copyright

or licensing contracts, such that it is not

legally seen as new content owned by the

person who requested AI to generate it.

This this will keep lawyers busy for a long

time!

Sam Bogoch: Challenges include adapt-

ing legacy systems to integrate with AI

tools, although increasingly the AI tools

can catalog existing media and storage

repositories (both on-premise and cloud).

Training staff to take full advantage of rap-

idly-evolving AI capabilities is also critical;

even the best technical solutions have lim-

ited value if there isn’t buy-in and adoption

from the wider team.

What are the biggest barriers to adopting

AI in broadcast production?

Siddarth Gupta:  Adopting AI in broad-

cast production often requires extensive

infrastructure and specialized talent, both

of which drive up implementation costs.

Models trained on limited or non-rep-

resentative data can often struggle with

real-time scenarios, leading to out-of-dis-

tribution (OOD) errors. These compound-

ing technical and financial hurdles have

forced broadcasters to rigorously scruti-

nize and justify their potential ROI before

committing to AI implementation.

Yang Cai: The biggest barriers to adopt-

ing AI in broadcast production include

high implementation costs, the complexity

of integrating AI with existing workflows,

and a lack of technical expertise among

staff. Additionally, concerns about data pri-

vacy, reliability, and resistance to change

within organizations can hinder adoption.

Overcoming these challenges requires in-

vestment in training, infrastructure, and

building trust in AI solutions.

Kathy Klinger: Ensuring quality and au-

thenticity remains a challenge, as AI lacks

the nuanced understanding and emotional

depth of human creators. Ethical and legal

concerns, including intellectual property,

data privacy, and bias, further complicate

its adoption, particularly in news and fact-

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, business manager,

Sony Electronics: 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.

What role does AI play in improving live

event production and broadcasting?

Yang Cai: AI enhances live event pro-

duction and broadcasting by enabling re-

al-time analytics, automated camera con-

trol, and intelligent content curation. It

improves viewer experience with features

like real-time language translation, per-

sonalized recommendations, and adaptive

bitrate streaming. AI also assists in de-

tecting and correcting errors during live

broadcasts, ensuring seamless delivery

and high-quality output.

Kathy Klinger:  AI enhances live event

production and broadcasting by optimiz-

ing workflows and enabling real-time ad-

justments to improve both quality and

efficiency. It can automate tasks such as

camera switching, highlight detection, and

audience analytics, allowing production

teams to focus on creativity and storytell-

ing. This combination of automation and

insight elevates the viewing experience

and ensures events reach audiences with

greater impact.

Zeenal Thakare: Broadcasters and live

event productions are going to focus on

creating more refined and engaging con-

tent. What that means is faster reaction

times during live events, as well as im-

mersive and interactive experiences. AI

is helping push the boundaries in the art

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Adopting AI in broadcast

production often requires

extensive infrastructure

and specialized talent,

both of which drive up

implementation costs.