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AI in Media & Broadcast – Professional Essentials Guide

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NEWSCASTSTUDIO.COM

Cover line

ARTIFICIAL

INTELLIGENCE

PROFESSIONAL ESSENTIALS

Smart ways

AI is reshaping

broadcasting

PAGE 17

PAGE 5

Using AI, machine

learning to fuel

content discovery

NAVIGATING THE FUTURE

OF BROADCASTING

MARCH

2025

Will AI kill

journalism?

Workforces adapting

to AI-powered workﬂows

PAGE 22

INDUSTRY INSIGHTS

VOICES

CONTENT

NEWSCASTSTUDIO.COM

By DAK DILLON

Editor in Chief, NewscastStudio

From sophisticated targeting in con-

nected TV to AI-driven predictive mod-

els that anticipate audience behavior, the

broadcast adtech landscape is undergoing

a reinvention driven by emerging technol-

ogy like artiﬁcial intelligence.

New research conﬁrms advertisers’

growing commitment to programmatic

strategies, while industry executives pre-

dict that AI will continue to unlock un-

tapped revenue potential. Here’s how it’s

playing out in practice.

Programmatic and CTV surge

A recent “2025 State of Programmatic

Report” by Proximic, a division of Com-

score, found that 72% of advertisers plan to

increase programmatic spending in 2025,

strongly emphasizing privacy-compliant

approaches. Connected TV is at the center

of this spending surge, now commanding

28% of ad budgets — double what it was in

2023. According to the report, nearly half

of marketers reallocating their program-

matic CTV budgets by shifting funds away

from linear TV.

“Connected TV emerged as a clear win-

ner, and privacy-focused strategies like

contextual targeting are becoming essen-

tial for marketers aiming to deliver highly

efective, privacy-centric campaigns,” said

Rachel Gantz, managing director at Proxi-

mic by Comscore.

This shift isn’t surprising given that

consumer viewing habits favor stream-

ing over traditional cable bundles. At the

same time, the appetite for more automat-

ed buying practices has grown, with data

from Advertiser Perceptions showing an

uptick in programmatic guaranteed deals

on subscription video-on-demand (SVOD)

platforms.

How this afects broadcasters

It suggests that ad budgets — historical-

ly the lifeblood of linear television — are

increasingly in play. Linear TV isn’t disap-

pearing overnight, but it’s facing renewed

competition from CTV and digital services

that can better target and measure audi-

ences. That shift, executives note, is where

AI can make a substantial diference.

“By analyzing viewer data, AI is able to

pinpoint content that resonates with au-

diences the most,” said Siddarth Gupta,

principal engineer at Interra Systems.

“Personalized ad insertion further max-

imizes revenue by matching ads to indi-

vidual preferences or the type of content

being viewed at the time.”

In other words, AI-driven personalization

is no longer a novelty; it’s a business impera-

tive, helping broadcasters capture attention

in a hyper-competitive ad market.

Personalization and contextual adver-

tising in broadcast

Amid privacy crackdowns and the slow

demise of third-party cookies, advertisers

are turning to new, “ID-free” solutions that

rely on contextual and ﬁrst-party data.

Proximic’s programmatic report noted

that 48% of marketers expect to rely pri-

marily on ID-free strategies by the end of

2025, and 52% plan to increase their use

of contextual data for targeting. These ﬁg-

ures underscore the importance of align-

ing ads with relevant content or themes

rather than just behavioral proﬁles.

“AI can enhance content monetization

… enabling dynamic ad insertion, ensuring

more relevant ads and driving higher en-

gagement and revenue,” said Yang Cai, CEO

and president of VisualOn. This personal-

ized approach is central to strategies like

contextual targeting, where AI scans video

or webpage content to place ads that mesh

seamlessly with the viewer’s experience.

Beyond simple text analysis, AI models

can detect visual cues, sentiment and even

brand safety issues within video content.

That granular understanding helps advertis-

ers avoid mismatches — like a children’s toy

ad running against adult-themed program-

ming — and allows them to place ads when a

viewer is most receptive.

Stefan Lederer, CEO and co-founder of

Bitmovin, said one of AI’s greatest strengths

is “to efciently and accurately search, tag

and categorize content … unlocking new ad-

vertising revenue potential through AI-pow-

ered contextual advertising.”

This means that archival footage or

niche programming can suddenly become

revenue-generating assets, provided the

right sponsors are matched to the right

content.

Forecasting and pricing beneﬁts

Amid this ﬂurry of AI-driven targeting,

there’s also a fundamental question of

how to price inventory. Linear TV once

NAVIGATING THE FUTURE

OF BROADCASTING

MICHAEL P. HILL

Founder and Publisher

DAK DILLON

Editor in Chief

JACOB BILLINGSLEY

Features Editor

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WELCOME

The

broadcast

industry

has always been shaped by

innovation, and today, artiﬁ-

cial intelligence and machine

learning are at the forefront

of that transformation. From

content recommendation en-

gines to automated produc-

tion workﬂows, AI is redeﬁn-

ing how television is created,

distributed, and consumed.

In this issue, we explore

how broadcasters, streaming

platforms and content cre-

ators can leverage AI to enhance audi-

ence engagement, streamline operations,

and push the boundaries of storytelling.

Whether it’s AI-driven sports highlights,

virtual production advancements, or re-

al-time analytics shaping ad

strategies, the impact is un-

deniable.

As with any technologi-

cal leap, AI brings both op-

portunities and challenges.

Ethical considerations, data

privacy, and the role of hu-

man creativity in an increas-

ingly automated industry are

just some of the discussions

shaping the future of TV.

Join us as we dive into the

world of AI-powered broad-

casting — where innovation meets story-

telling in ways we’ve never seen before. 

Michael P. Hill (with help from ChatGPT)

Founder and Publisher

HILL

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GET IN TOUCH

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had a relatively predictable schedule and a

smaller set of data inputs to consider. Now,

with dozens of streaming platforms and

overlapping audiences, understanding de-

mand levels becomes more complex and

critical.

“Broadcasters can leverage AI to learn

more about their viewers … helping them

create more accurate forecasts for both

viewer and advertiser demand, which can

help them create smarter pricing strate-

gies,” said Dave Dembowski, senior vice

president of global sales at Operative.

By crunching data from multiple touch-

points — CTV apps, linear ratings, social

media chatter — AI can give real-time in-

sights on how many eyeballs a speciﬁc

event or show might attract.

That insight is a big deal in a market

poised for massive growth. GroupM’s an-

nual forecast projects global advertising

revenue will surpass $1 trillion this year,

on track to reach $1.1 trillion by 2025.

Digital platforms, including CTV, are

fueling much of this growth, while linear

TV revenue is expected to soften. Even as

streaming ad loads remain relatively light

compared to traditional broadcasts, new

ad tiers, shoppable ad formats and ad-

vanced measurement tools quickly make

streaming a top priority for media buyers.

Advertiser Perceptions’ “CTV Land-

scape 2H 2024” study found that 75% of

surveyed ad buyers want a single partner

that can handle both linear and streaming

campaigns. AI-driven forecasting is pre-

cisely what can make that convergence

practical. By analyzing extensive volumes

of viewer behavior data, AI can tell mar-

keters how to distribute ad spend across

channels for maximum impact — whether

that’s election coverage, live sports or a

premium drama series.

More integration with more data

While AI presents a robust toolkit, chal-

lenges remain.

Privacy regulations continue to evolve,

and ID-free environments demand rigor-

ous, transparent data practices. Market-

ers also note the difculty of measuring

performance marketing on CTV platforms,

where 80% see potential for brand-build-

ing, yet only 20% consider it ideal for driv-

ing direct sales. That mismatch may shrink

as AI-based attribution models get better

at linking ad exposures to downstream

conversions.

Additionally, some worry about data

fragmentation.

Even the best AI platform can’t magical-

ly unify data if the underlying infrastruc-

ture is siloed across multiple providers.

However, the push toward “cleanroom”

solutions — secure environments where

data can be shared without compromising

privacy — ofers a potential workaround. AI

will have more fuel to optimize campaigns

while respecting consumer privacy as

these environments mature.

The message for broadcasters look-

ing to thrive in this changing landscape is

clear: AI isn’t just about easing workﬂows

in the control room or the editing suite. It’s

also about enabling precision, efciency

and agility in ad operations.

“AI’s ability to efciently and accurate-

ly search, tag and categorize content can

help surface hidden assets,” Lederer said,

pointing to a key value driver. Pair that

with advanced forecasting capabilities,

and a broadcaster can proactively reprice

ad inventory, develop niche sponsorships

or respond in real time when a piece of

content suddenly goes viral.

The marriage of AI and advertising is no

passing fad. Programmatic is blossoming,

CTV is surging and the lines between digi-

tal and linear are blurring faster than ever

before.

For those who embrace the change, AI

could ofer a fast track to sustained rev-

enue growth. For everyone else, it’s a re-

minder that the old methods of selling

commercials at set times may no longer

cut it in a world fueled by data, personal-

ization and on-demand viewing.

Ultimately, the real impact of AI on mon-

etization and advertising is measured

in what it delivers: more relevant cam-

paigns for consumers, stronger returns

for marketers and new revenue streams

for broadcasters. And given the rapid ad-

vancements, it’s safe to say that this is just

the beginning of AI’s inﬂuence on the fu-

ture of advertising. g

Continued from previous page

By SAM PETERSON

Chief Operating Ofcer, BitCentral

Artiﬁcial intelligence (AI) and machine

learning (ML) are reshaping the media in-

dustry. According to Grand View Research,

the AI and ML market in media is project-

ed to grow at a compound annual growth

rate (CAGR) of 38.1% from 2022 to 2030.

For media organizations managing expan-

sive content libraries, these technologies

are essential for enhancing accessibility,

improving

work-

ﬂows, and seizing

new

opportuni-

ties.

integrating

AI tools into their

operations, media

companies

can

streamline

con-

tent

discovery,

accelerate

edi-

torial

processes,

and simplify col-

laboration across

teams and station

groups.

Overcoming the challenge

of content overload

The modern media landscape is inundat-

ed with content. Over years — sometimes

decades — organizations have amassed

vast archives, yet their ability to efectively

locate and utilize these resources remains

limited. Outdated search tools and manual

tagging systems force editorial teams to

waste valuable time searching for assets,

delaying projects and hampering creative

agility.

This inefciency does more than slow

workﬂows — it diminishes a team’s ability

to respond to breaking news, meet audi-

ence demands, and unlock the full value of

their archives.

AI as a catalyst for smarter

content discovery

AI-powered tools are transforming how

media companies manage content librar-

ies. By automating the generation of rich

metadata — such as contextual tags, de-

tailed transcripts, and content categoriza-

tion — AI enables precise, highly relevant

searches. Editorial teams can locate the

exact asset they need, whether it’s an in-

terview, archived footage, or a speciﬁc lo-

cation, in seconds rather than hours.

The real advantage of AI lies in its abil-

ity to analyze content at scale. Advanced

algorithms provide both speed and con-

text, surfacing assets that might otherwise

remain hidden. In practice, this capability

helps organizations turn sprawling ar-

chives into strategic resources — tools that

drive creativity, rather than slow it down.

Real-world applications: From

efciency to innovation

Media companies are already realizing

the beneﬁts of AI in their editorial work-

ﬂows. AI-driven metadata tools are im-

proving content retrieval by automating

transcripts and tagging content with un-

paralleled precision. This ensures assets

can be shared seamlessly across teams

and platforms.

For instance, the BBC’s The Juicer aggre-

gates and categorizes vast amounts of news

content using natural language processing

(NLP). By automating topic tag By By auto-

mating the generation of rich metadata —

such as contextual tags, detailed transcripts,

and content categorization — AI enables

precise, highly relevant searches. automat-

ing the generation of rich metadata — such

as contextual tags, detailed transcripts, and

content categorization — AI enables precise,

highly relevant searches. ging, it empowers

editorial teams to sift through massive data-

sets efciently and uncover the most rele-

vant stories.

AI also simpliﬁes creative workﬂows.

Tools capable of generating rough cuts from

raw footage are saving editors signiﬁcant

AI, ML fuel content discovery,

editorial efciency workﬂows

PETERSON

Continued on next page

MARKET SEGMENTS

By automating the

generation of rich

metadata — such as

contextual tags, detailed

transcripts, and content

categorization — AI

enables precise, highly

relevant searches.

Artiﬁcial intelligence is reshaping the

media and entertainment industry, with

NAB Show 2025 placing AI at the center of

discussions on content creation, distribu-

tion and audience engagement.

PropelME, NAB Show’s startup-focused

hub, is highlighting AI-driven solutions

in partnership with FBRC.ai, a company

known for connecting emerging AI inno-

vators with industry leaders.

The collaboration brings a dedicated

show ﬂoor destination featuring AI-pow-

ered tools and discussions. The new Start-

up Stage will host conversations on AI’s

role in hybrid production workﬂows, as

well as its impact on personalized audi-

ence experiences. Additionally, the Start-

up Showcase will provide rapid presenta-

tions from companies demonstrating AI

solutions, with audience members select-

ing a standout startup for an in-depth Fire-

side Chat.

NAB Show 2025 also includes hands-on

AI workshops, such as “Getting Started

with Generative AI,” designed to give cre-

ators practical experience with AI tools

used for content generation. Companies

exhibiting in PropelME include Advanced

Image Robotics, Anantadi, AudioShake

and others.

Beyond the startup space, AI will be a

key focus across NAB Show programming.

The AI Innovation Pavilion will show-

case advancements in AI-powered media

technology, while Post|Production World

expands its AI track to cover AI-driven

video editing, motion graphics and anima-

tion. Sessions such as “Safeguarding IP in

the Era of AI” and “DeepSeek and the New

Reality” will address AI’s implications for

intellectual property and media ethics.

Industry leaders are closely monitoring

AI’s economic impact. According to McK-

insey & Company, generative AI could

contribute between $380 billion and $690

billion to the global economy, while Straits

Research projects the AI media and enter-

tainment market will exceed $104.4 billion

by 2030.

“NAB Show brings together emerging

technologies and visionary creators to ex-

plore AI’s ability to enhance storytelling,”

said Karen Chupka, executive vice pres-

ident and managing director, NAB Global

Connections and Events.



NAB SHOW PREVIEW

NAB Show to feature AI-focused zones

NEWSCASTSTUDIO.COM

time by providing a starting point, enabling

them to focus on reﬁning narratives and

visuals rather than working from scratch.

This not only accelerates production but el-

evates the quality of the ﬁnal product.

Another critical application of AI is in

content adaptation. As audiences consume

media across platforms — social media,

streaming, and mobile apps — AI tools can

automatically tailor content for speciﬁc dis-

tribution points. This ensures media orga-

nizations extend their reach while keeping

pace with diverse audience preferences.

A strategy for growth

AI’s value extends beyond streamlining

workﬂows. By automating time-consuming

processes, AI enables editorial teams to fo-

cus on what truly matters: creative storytell-

ing and audience engagement. The result is

a more agile production process that allows

teams to respond to fast-moving news cy-

cles and evolving audience demands.

In addition, AI maximizes the value of

existing content libraries by uncovering un-

derutilized assets. By making archives more

accessible and adaptable, media companies

can repurpose content across platforms

and uncover new revenue opportunities.

Looking ahead

As the media industry continues to

evolve, AI will play a critical role in shaping

its future. Companies that embrace AI for

content discovery and workﬂow efciency

will gain a clear competitive advantage —

creating higher-quality content faster and

engaging audiences more efectively.

Ultimately, AI is more than just a tool

for improving efciency; it’s a foundation

for innovation. By freeing editorial teams

from manual processes, AI empowers

them to tell better stories, reach wider

audiences, and unlock the full potential of

their content.

For media organizations willing to em-

brace its transformative power, AI rep-

resents a clear pathway to smarter, faster,

and more impactful content creation. 

Sam Peterson is the Chief Operating

Ofcer at Bitcentral, overseeing teams

that develop and support innovative media

workﬂow solutions used by broadcast

sites worldwide. With nearly 35 years of

industry experience, he is dedicated to

fostering collaboration, innovation, and

customer-focused solutions that empower

Bitcentral’s customers.

Continued from previous page

By DAK DILLON

Editor in Chief, NewscastStudio

Artiﬁcial intelligence continues to re-

shape broadcast technology, moving be-

yond theoretical applications to practical

implementations across production work-

ﬂows.

In this ﬁrst installment of a three-part

Industry Insights roundtable, technology

vendors and solutions providers examine

the current state of AI in broadcast.

The discussion explores real-world ap-

plications such as automated captioning,

content tagging and live production assis-

tance. Participants address the opportuni-

ties and challenges facing broadcasters as

they integrate AI tools, from infrastructure

requirements to staf training needs. The

conversation also looks ahead to emerging

AI applications in accessibility, language

translation and workﬂow optimization.

It’s been a wild year of AI advancements.

Where are we today? How do those apply

to broadcasters and production?

Siddarth Gupta, principal engineer,

Interra Systems: Over the past year, AI

has made remarkable strides in natural

language processing (NLP), image gener-

ation, and real-time analytics, all of which

continue to reshape how content is pro-

duced and delivered. Broadcasters can

now automate routine tasks like editing,

captioning, and highlight creation, freeing

staf to focus on higher-level storytelling.

As a result, production cycles are faster,

more data driven, and better aligned with

evolving audience preferences.

Bob Caniglia, director of sales oper-

ations, Americas, Blackmagic Design:

While AI was certainly a headline grab-

bing news item this year and has some

far reaching implications, it’s important to

look at how it has already been used for

years to see where it has potential to go. By

leveraging AI-driven tools in post produc-

tion, such as noise reduction, audio classi-

ﬁcation, smart reframing, and automated

transcription, broadcasters have achieved

faster edits, precision in storytelling, and

seamless multi-platform content repur-

posing for traditional and social media.

These advancements not only improve

operational efciency but also inspire cre-

ative possibilities, reshaping how broad-

cast teams approach content creation.

Zeenal Thakare, SVP, enterprise solu-

tions architecture, Ateliere: The appli-

cation of these technologies is going to

speed up workﬂows by automating script-

ing, generating content and dynamically

building programming slots. In addition,

live production will be revolutionized by

automating many technical aspects, mak-

ing content reach the audience in a faster

and more enhanced manner. Another big

part of broadcast production is accessibil-

ity — leveraging AI to generate real-time

transcriptions in multiple languages and

Where we stand now with AI

for broadcasting, production

Continued on next page

ROUNDTABLE

• Automation: AI technologies now handle

routine broadcast tasks including caption-

ing, metadata tagging, and content index-

ing, allowing staf to focus on creative work.

• Infrastructure: Organizations face signiﬁ-

cant barriers in AI adoption, including high

implementation costs, technical infra-

structure requirements, and the need for

specialized expertise.

• Live Production: AI enhances live broad-

casts through automated camera tracking,

real-time analytics, and automated quality

control systems.

• Integration: Successfully implementing

AI requires careful assessment of existing

system compatibility and comprehensive

staf training programs.

• Development: Future AI applications in

broadcasting focus on improving accessibil-

ity features, expanding language transla-

tion capabilities, and automating content

creation processes.

KEY TAKEAWAYS FROM ROUNDTABLE

Artiﬁcial intelligence was a focal point

at the International Broadcasting Con-

vention 2024, with industry profession-

als eager to explore its practical applica-

tions in media and entertainment.

As the technology matures, discus-

sions are shifting from potential use

cases to real-world implementations

that deliver tangible beneﬁts across the

broadcast ecosystem. With AI spend in

media projected to reach $13 billion by

2028, according to Omdia, the industry

is seeking clarity on how to harness AI’s

potential most efectively.

From hype to reality

The buzz around AI at trade shows has

been building, but 2024 marks a turning

point. Industry professionals are eager

to move beyond hypothetical use cases

and see tangible results.

The transition from theory to prac-

tice is not just a matter of curiosity but

a business imperative. As media com-

panies face pressure to deliver more

content across multiple platforms while

controlling costs, AI ofers a potential

solution to enhance efciency and pro-

ductivity.

Practical applications across

the media supply chain

As AI technology evolves, its applica-

tions in media and entertainment are be-

coming more diverse and sophisticated.

These applications span the entire

content lifecycle, from creation to dis-

tribution and audience engagement.

In content creation, AI tools enhance

creative processes by assisting with

scriptwriting, storyboarding and even

generating realistic visual efects. In

post-production, AI algorithms stream-

line editing workﬂows, automate color

correction and improve audio quality.

These applications represent just

the tip of the iceberg. As AI technology

continues to evolve, its potential uses in

broadcasting are expanding rapidly.

From hype to implementation

These AI-powered tools are particu-

larly valuable in news production envi-

ronments, where speed and accuracy

are paramount. Automated transcription

and content search capabilities enable

journalists and producers to quickly sift

through large volumes of footage and

identify relevant clips, signiﬁcantly re-

ducing production time.

This shift toward implementation

brings with it new challenges and con-

siderations for broadcasters. As they

move from pilot projects to full-scale

deployments, issues of integration, scal-

ability and return on investment come to

the fore.

Balancing innovation, practicality

As AI technology evolves rapidly, me-

dia companies face challenges in efec-

tively adopting these tools. The fast pace

of development in AI raises concerns

about investing in solutions that may

quickly become obsolete.

Efciency and cost-efectiveness

One of the key drivers behind AI adop-

tion in the broadcast industry is the

potential for increased efciency and

cost-efectiveness,

AI-powered automation can signiﬁ-

cantly reduce manual labor in content

tagging, quality control and compli-

ance-checking tasks. This speeds up

workﬂows and allows human resources

to be redirected towards more creative

and strategic tasks.

This vision of AI-augmented creativity

raises intriguing questions about the fu-

ture of content production and the role

of human creators in an increasingly au-

tomated landscape. It also points to the

potential for AI to democratize content

creation, enabling smaller production

companies and individual creators to

produce high-quality content at scale. 

IBC ROUNDUP

IBC explores how

AI hype can lead to

practical solutions

NEWSCASTSTUDIO.COM

aimed at a diverse demographic is going to

certainly add speed and scale to the busi-

ness model.

Jordan Thomas, marketing manager,

QuickLink: For broadcasters and produc-

tion organizations, we have seen an inno-

vative approach in which manufacturers

and solution providers are utilizing these

AI advancements and applying them to

both existing and new solutions. These

advancements are not only streamlining

workﬂows but also allowing us to elevate

video and audio quality. The ability to re-

move video artifacts, correct eye con-

tact, and automatically frame the shot of

remote guests is revolutionary when it

comes to creating high-quality content

that engages audiences.

Costa Nikols, strategy advisor, media

and entertainment, Telos Alliance: In au-

dio, AI is unlocking new creative options

and helping make the unmanageable more

manageable — from improving sound clari-

ty in challenging environments to enhanc-

ing dialogue normalization at scale for

global audiences. These advancements

can reduce the manual workload for pro-

duction teams, enabling them to focus on

storytelling and creative processes rather

than the mundane. Automating the mun-

danity is where AI thrives — and where it

can deliver most impact today.

Sam Bogoch, CEO, Axle AI: AI has ma-

tured into a critical tool for broadcasters,

enabling real-time applications such as

scene understanding with semantic search,

automated tagging, speech-to-text tran-

scription, and metadata generation. These

advancements simplify media asset man-

agement, streamline workﬂows, and en-

hance production speed, allowing teams to

deliver high-quality content faster.

Noa Magrisso, AI developer, TAG Video

Systems: For broadcasters, this means ac-

cess to tools that automate captioning, en-

hance audience analytics, and streamline

video editing. AI agents are revolutioniz-

ing workﬂows by autonomously managing

tasks like scheduling, content tagging, and

even real-time audience interactions. The

rise of multimodal AI is also a game-chang-

er, enabling seamless integration of text,

images, and audio within a single model.

Simon Parkinson, managing director,

Dot Group: Within broadcasting, there are

many competitive advantages that AI can

help businesses to realize, be it through

video editing, content generation, or auto-

mating industry-agnostic challenges that

free up employees to work on being cre-

ative. The possibilities are endless.

How is AI actively being used in broadcast

production workﬂows? In real applications,

not just as a proof of concept?

Peyton Thomas: AI is being used in

auto-tracking/auto-framing of robotics

and robotic cameras. During the election

broadcast we saw AI being used to trig-

ger graphics via voice prompts. AI is trig-

gering back-end automation to encode

and tag data during and after a produc-

tion is complete.

Yang Cai, CEO and president, Visua-

lOn: AI is actively used in broadcast pro-

duction workﬂows to enhance efciency

and quality. It automates repetitive tasks

like transcription, metadata tagging, and

content indexing, signiﬁcantly speed-

ing up production timelines. Addition-

ally, AI-driven tools optimize live video

streams by increasing compression ra-

tio through technologies such as con-

tent-adaptive encoding, enable real-time

language translation, and improve visual

quality through upscaling, color correc-

tion, and noise reduction.

Bob Caniglia: AI is being actively utilized

to enhance efciency and simplify complex

tasks. For example, by using smart reframe

for social media, broadcasters can easily

create square or vertical versions of their

footage for Instagram and other apps, with

AI technology automatically identifying ac-

tion and repositioning the image inside a

new frame so the team doesn’t have to do

it manually. Additionally, there’s real-world

applications of AI-powered facial recogni-

tion that streamline footage organization by

sorting clips based on people in the shot.

Steve Taylor, chief product and technol-

ogy ofcer, Vizrt: From a Vizrt perspective,

we have been using AI ML for a long time as

a key advantage for our sports and graph-

ics solutions. This includes to support color

keying on any background, without the need

for a green screen. AI ML have also been

used at Vizrt to make augmented reality and

virtual reality more realistic, as well as to

quickly process live sports content to iden-

tify players.

Sam Bogoch: Our company has seen mul-

tiple real-world uses of our Axle AI Tags plat-

form, ranging from large national broadcast-

ers using AI (including RTM, in Malaysia) to

make their news content searchable, to Hol-

lywood promo houses (including MOCEAN,

in Hollywood) using AI to sift through the

massive amount of dailies footage they re-

ceive. In both these cases, AI makes it prac-

tical to search the large amount of relevant

footage for the ﬁrst time.

Beyond real-world implementation, what is

likely next to use AI or ML?

Stefan Lederer, CEO and co-founder,

Bitmovin: Something we’re exploring and

developing is an AI-powered solution that

translates American Sign Language (ASL)

text into client-side sign-language signing

avatars. Currently, this is strictly an innova-

tion piece that we’re collaborating with the

deaf community on to understand how and

if the technology could help make video

streaming more inclusive. Beyond that, I ex-

pect companies to explore diferent ways to

make content more accessible for all view-

ers. For example, AI could be used to ana-

lyze video content and narrate key visual el-

ements, such as facial expressions, settings,

and actions, in real-time, which will help to

automate the creation of audio descriptions

for visually impaired viewers.

Steve Taylor: The use of AI to auto gen-

erate subtitles and captions, as well as to

translate languages is deﬁnitely an area

that is growing. This is also true for AI’s

use in identify workﬂow optimizations,

through studio automation. In a produc-

tion environment, it can optimize work-

ﬂow by automating repetitive tasks, en-

abling the team to conﬁdently focus on

other areas of the production.

Noa Magrisso: The next phase of AI

and ML involves advancing collaboration,

personalizing content, and seamlessly le-

veraging multimodal AI to integrate text,

images, and audio. Emerging applications

include adaptive learning tools, healthcare

diagnostics, and immersive media experi-

ences.

How can emerging technologies improve

efciency in news gathering and reporting?

Siddarth Gupta: Emerging technologies

let reporters quickly ﬁlter vast data sets

to help them pinpoint the most relevant

information. Automated tools help reduce

Continued from previous page

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 efciency 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 staf 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

staf. 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 efciency

with human creativity, establish responsi-

ble frameworks, and uphold transparency

to maintain trust and content efcacy.

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,

ofered 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

efciency. 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

For broadcasters, this

means access to tools

that automate captioning,

enhance audience

analytics and streamline

video editing.

Continued on next page

Adopting AI in broadcast

production often requires

extensive infrastructure

and specialized talent,

both of which drive up

implementation costs.

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of possibility by empowering productions

with new tools that aid creativity while be-

ing efcient.

Ken Kobayashi: AI-enabled camera

tracking facilitates the operation of mul-

tiple cameras at an event location or stu-

dio with minimal camera operators. AI is

a cost-efective technology for creating

efciencies, and when embedded in pan-

tilt-zoom cameras it enables consistency

and quality that can seamlessly scale to

multiple cameras.

Costa Nikols: From an audio perspec-

tive, emerging AI-driven algorithms can

help optimize audio levels, crowd noise,

and enhance speech clarity in real time,

empowering broadcasters to ofer more

reﬁned live event experiences for TV

viewers. Personalization is another poten-

tial game-changer. Through a mix of new

AI-supported methodologies and Next

Generation Audio technologies, broad-

casters can more easily ofer tailored au-

dio streams, such as alternative commen-

tary, language tracks or ampliﬁed dialogue

based on device and viewer preferences.

Sam Bogoch: AI can enhance live pro-

duction by automating tasks such as cam-

era angle selection, logo and face rec-

ognition, scene switching, and real-time

analytics. This allows production teams

to focus on creative decision-making

while ensuring seamless and dynamic live

broadcasts.

Noa Magrisso: It automates camera

switching, directs cameras to the most en-

gaging scenes, and improves audio quali-

ty through real-time noise reduction for

clearer sound. AI also generates real-time

graphics or overlays for stats, live updates,

and interactive polls, boosting audience

engagement. Additionally, it enables seam-

less multilingual support with real-time

translation and automates captioning for

accessibility.



By NIKKI PERUGINI

UX and Design Director, Accedo

The video industry has had a difcult

time of it over the last few years. We’ve

seen continued hard churn as consum-

ers tightened their belts, which naturally

led to providers focusing on cost cutting

over growth. It seems that the industry

may now be turning a corner, however

video service success moving forward

will depend on providers pulling out all

the stops to engage users and prevent

churn. And as any provider worth its salt

knows, this means continually improving

user experience and enhancing personal-

ization. After all, a happy, engaged user is

more likely to watch for longer and stick

around.

However,

efective

personaliza-

tion is difcult to get right and can be

both time-consuming and costly. Huge

amounts of data need to be analyzed to

determine what shows and movies the

viewer will enjoy the most, and what

works best to engage the user and get

them to press play. AI, with its ability to

quickly analyze enormous datasets and

make data-driven decisions, is the ideal

tool to support personalization. Conse-

quently, it’s hardly surprising that vid-

eo services, certainly the big streamers

anyway, are already using AI to analyze

users’ viewing habits and other relevant

data, and have been for some time. Global

players like Netﬂix have been using Ma-

chine Learning tools for years to provide

relevant recommendations and even per-

sonalise thumbnails based on user pref-

erences. AI provides the next step in ad-

vancing these types of features.

Why personalization matters

Streaming services typically have a

massive catalogue of available content,

which makes it difcult for viewers to ﬁnd

the content they want to watch quickly.

And if users can’t quickly ﬁnd something

to watch, the likelihood is that before

long, they’ll get bored with searching and

promptly switch of. I’m sure we’ve all

been there and done that with one service

or another. When done well,

personalization saves view-

ers lots of time and efort, and

improves the overall viewing

experience

tremendously.

Instead of endlessly search-

ing through a huge catalogue

of content to ﬁnd something

that appeals, viewers are of-

fered a tailored collection of

shows and movies that close-

ly matches their unique tastes

and preferences.

And of course, it’s not just

content recommendations that can be per-

sonalized. The home page layout is also

a key part of personalization, designed to

improve the user experience by making

content discovery seamless and engaging.

Personalizing the layout means that each

user sees an interface tailored to their pref-

erences, behaviors, and viewing habits, en-

hancing both convenience and satisfaction.

This can be achieved by understanding

which rails a user prefers to interact with

and giving them higher promi-

nence on the home page, or fea-

turing their favourite content in

the hero.

Efective personalization in-

creases engagement so that

viewers watch for longer and

keep coming back for more.

It’s also a great tool to promote

new and existing content and

aid discovery, because it can

encourage users to explore

new genres that they may oth-

erwise not consider, as well as

uncover hidden treasures, and expand the

scope of their viewing.

Understanding nuances around

personalization

Engaging viewers and keeping them en-

gaged is an art form and personalization is

the key to success. Successful video pro-

viders collect huge amounts of data about

Continued on next page

Continued from previous page

Leveraging AI for faster and

more efective personalization

CONTENT PERSONALIZATION

PERUGINI

Efective personalization challenging to get

right thanks to huge amount of data needed

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viewers which is often used alongside the

viewers preferences when they ﬁrst on-

boarded, to curate personalized content

recommendations. This includes what

the viewer searched for, what videos they

played and at what time of day, whether

they watched to the end, how long it took

them to watch, how long each viewing ses-

sion lasted, as well as video ratings and

popularity. Put all of this together and mix

in some clever algorithms, and video ser-

vices then know which movies and shows

the viewer will enjoy watching the most.

Unfortunately, it’s not quite that sim-

ple because the way that viewers engage

with content is incredibly nuanced. Difer-

ent viewers like diferent things, and this

goes much deeper than diferent genres

or types of content. For example, out of an

audience who all like a certain genre, let’s

say, action and adventure, the same trail-

er may not necessarily hook in all view-

ers. What appeals to one consumer may

not necessarily appeal to another. Video

providers can attract a wider variety of

viewers to a particular show if the trailer

is personalized to appeal to their individ-

ual tastes. This is an area that AI is driving

forward, with new software able to create

custom images, videos and trailers to sup-

port the decision making process.

For example, if a viewer sees a trailer

featuring their favorite actor, that will ap-

peal to them most, while another viewer

may not be interested in that actor but may

prefer shows that have a strong female

lead, so a diferent trailer may work bet-

ter for them. By showing diferent viewers

trailers that are personalized to appeal to

their individual preferences, providers are

much better able to encourage viewers to

watch content. Similarly, thumbnails can

also be personalized in much the same

way as trailers can, in order to have the

most impact. This process involves choos-

ing the single frame from a show or movie

that is most likely to resonate with the in-

dividual viewer and using it as the thumb-

nail. By selecting the frame that best cap-

tures their interest, the platform increases

the chances that viewers will click on the

title and start watching.

Impact of AI on personalization

Before the advent of AI, video services

relied heavily on static user proﬁles, lim-

ited metadata, and manual tagging of con-

tent for personalization. With AI, the pro-

cess is faster and more accurate, which

makes it both more efcient and efective.

Using AI and ML, providers can identify

nuanced patterns in user behavior, which

enable dynamic and adaptive personaliza-

tion that evolves with the user’s preferenc-

es in real time.

AI vastly speeds up the processes that

enable personalization. Let’s consider

tagging as an example. For content rec-

ommendations to be accurate, video pro-

viders need to understand and know the

content of shows and movies down to the

minutia detail. In the past, this would have

involved teams of staf, some in-house and

some freelance, sitting down and watch-

ing every show in detail then accurately

tagging it.

Yet these days, with AI, the entire key-

word tagging process can be automated.

And additionally, it can also add a great

deal of detail which would not have been

practical when the process was done man-

ually. Detailed keyword tagging helps vid-

eo services to better identify similarities

between content so that recommenda-

tions can be more diverse but still be ac-

curate and appeal to viewers. In this use

case, it’s easy to see that AI not only saves

time and efort, but also makes the process

more efective.

Beyond personalization, AI plays a cru-

cial role in enhancing the user experience

by optimizing streaming quality. Take Net-

ﬂix, for instance, which leverages machine

learning algorithms to monitor network

conditions in real time and dynamically

adjusts video quality. By assessing factors

such as bandwidth, device type, and geo-

graphic location, Netﬂix ensures the best

possible video resolution while reducing

bufering and interruptions. This seam-

less performance not only keeps users

engaged but also encourages them to stay

on the platform because loading times are

fast and playback is smooth.

What will personalization mean in

tomorrow’s world?

Efective personalization is fundamen-

tal to a video provider’s success. Without

it, the viewer won’t be able to easily ﬁnd

content they want to watch, and addition-

ally the content that they may enjoy may

not appeal to them at ﬁrst glance. AI is en-

abling video services to deliver faster and

more precise recommendations with an

improved user experience. Already AI can

help providers to infer mood and deliver

emotionally and situationally appropriate

recommendations. The question is, how

might this develop and improve as time

goes on and AI technology continues to

advance?

It will most likely become even more pre-

cise and intuitive as AI systems are used to

analyze subtle behavioral cues like voice

tone and biometrics to understand the us-

er’s mood and anticipate their preferenc-

es. I expect the content creation function-

ality of AI will continue to advance, even

being able to create unique content expe-

riences, such as diferent opening scenes

or alternate endings, designed to provide

each viewer with the experience that they

will enjoy the most. I have a feeling that we

are only at the beginning of what AI-driven

personalization can deliver — it’s going to

be an exciting ride for sure.



A customer experience expert, Nikki

has been with Accedo for more than 8

years and has driven some of our largest

UX engagements across the APAC region.

She is skilled in UX & UI, Strategy and

Research. She leads Accedo’s team of

designers in Asia Paciﬁc. When not at

Accedo you can ﬁnd her on the Rugby

League ﬁeld, passionate about playing and

coaching young women in the sport.

Continued from previous page

Yet these days, with AI, the entire keyword tagging

process can be automated. And additionally, it can

also add a great deal of detail which would not have

been practical when the process was done manually.

By DAK DILLON

Managing Editor, NewscastStudio

From sophisticated targeting in con-

nected TV to AI-driven predictive mod-

els that anticipate audience behavior, the

broadcast adtech landscape is undergoing

a reinvention driven by emerging technol-

ogy like artiﬁcial intelligence.

New research conﬁrms advertisers’

growing commitment to programmatic

strategies, while industry executives pre-

dict that AI will continue to unlock un-

tapped revenue potential. Here’s how it’s

playing out in practice.

Programmatic, CTV surge ahead

A recent “2025 State of Programmatic

Report” by Proximic, a division of Com-

score, found that 72% of advertisers plan to

increase programmatic spending in 2025,

strongly emphasizing privacy-compliant

approaches. Connected TV is at the center

of this spending surge, now commanding

28% of ad budgets — double what it was in

2023. According to the report, nearly half

of marketers reallocating their program-

matic CTV budgets by shifting funds away

from linear TV.

“Connected TV emerged as a clear win-

ner, and privacy-focused strategies like

contextual targeting are becoming essen-

tial for marketers aiming to deliver highly

efective, privacy-centric campaigns,” said

Rachel Gantz, managing director at Proxi-

mic by Comscore.

This shift isn’t surprising given that

consumer viewing habits favor stream-

ing over traditional cable bundles. At the

same time, the appetite for more automat-

ed buying practices has grown, with data

from Advertiser Perceptions showing an

uptick in programmatic guaranteed deals

on subscription video-on-demand (SVOD)

platforms.

What does all this mean

for broadcasters?

It suggests that ad budgets — historical-

ly the lifeblood of linear television — are

increasingly in play. Linear TV isn’t disap-

pearing overnight, but it’s facing renewed

competition from CTV and digital services

that can better target and measure audi-

ences. That shift, executives note, is where

AI can make a substantial diference.

“By analyzing viewer data, AI is able to

pinpoint content that resonates with au-

diences the most,” said Siddarth Gupta,

principal engineer at Interra Systems.

“Personalized ad insertion further max-

imizes revenue by matching ads to indi-

vidual preferences or the type of content

being viewed at the time.”

In other words, AI-driven personaliza-

tion is no longer a novelty; it’s a business

imperative, helping broadcasters capture

attention in a hyper-competitive ad mar-

ket.

Personalization and contextual

advertising in broadcast

Amid privacy crackdowns and the slow

demise of third-party cookies, advertisers

are turning to new, “ID-free” solutions that

rely on contextual and ﬁrst-party data.

Proximic’s programmatic report noted

that 48% of marketers expect to rely pri-

marily on ID-free strategies by the end of

2025, and 52% plan to increase their use

of contextual data for targeting. These ﬁg-

ures underscore the importance of align-

ing ads with relevant content or themes

rather than just behavioral proﬁles.

“AI can enhance content monetization

… enabling dynamic ad insertion, ensur-

ing more relevant ads and driving higher

engagement and revenue,” said Yang Cai,

CEO and president of VisualOn. This per-

sonalized approach is central to strategies

like contextual targeting, where AI scans

video or webpage content to place ads that

mesh seamlessly with the viewer’s experi-

ence.

Beyond simple text analysis, AI models

can detect visual cues, sentiment and even

brand safety issues within video content.

That granular understanding helps adver-

tisers avoid mismatches — like a children’s

toy ad running against adult-themed pro-

gramming — and allows them to place ads

when a viewer is most receptive.

Stefan Lederer, CEO and co-founder of

Bitmovin, said one of AI’s greatest strengths

is “to efciently and accurately search, tag

and categorize content … unlocking new

advertising revenue potential through

AI-powered contextual advertising.”

This means that archival footage or

niche programming can suddenly become

revenue-generating assets, provided the

right sponsors are matched to the right

content.

Monetizing content with AI: Going beyond

traditional advertising to unlock new value

ADVERTISING

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Forecasting and pricing beneﬁts

from new AI tools

Amid this ﬂurry of AI-driven targeting,

there’s also a fundamental question of

how to price inventory. Linear TV once

had a relatively predictable schedule and a

smaller set of data inputs to consider. Now,

with dozens of streaming platforms and

overlapping audiences, understanding de-

mand levels becomes more complex and

critical.

“Broadcasters can leverage AI to learn

more about their viewers … helping them

create more accurate forecasts for both

viewer and advertiser demand, which can

help them create smarter pricing strate-

gies,” said Dave Dembowski, senior vice

president of global sales at Operative.

By crunching data from multiple touch-

points — CTV apps, linear ratings, social

media chatter — AI can give real-time in-

sights on how many eyeballs a speciﬁc

event or show might attract.

That insight is a big deal in a market

poised for massive growth. GroupM’s an-

nual forecast projects global advertising

revenue will surpass $1 trillion this year,

on track to reach $1.1 trillion by 2025.

Digital platforms, including CTV, are

fueling much of this growth, while linear

TV revenue is expected to soften. Even as

streaming ad loads remain relatively light

compared to traditional broadcasts, new

ad tiers, shoppable ad formats and ad-

vanced measurement tools quickly make

streaming a top priority for media buyers.

Advertiser Perceptions’ “CTV Land-

scape 2H 2024” study found that 75% of

surveyed ad buyers want a single partner

that can handle both linear and streaming

campaigns. AI-driven forecasting is pre-

cisely what can make that convergence

practical. By analyzing extensive volumes

of viewer behavior data, AI can tell mar-

keters how to distribute ad spend across

channels for maximum impact — whether

that’s election coverage, live sports or a

premium drama series.

More integration with more data

While AI presents a robust toolkit, chal-

lenges remain.

Privacy regulations continue to evolve,

and ID-free environments demand rigor-

ous, transparent data practices. Market-

ers also note the difculty of measuring

performance marketing on CTV platforms,

where 80% see potential for brand-build-

ing, yet only 20% consider it ideal for driv-

ing direct sales. That mismatch may shrink

as AI-based attribution models get better

at linking ad exposures to downstream

conversions.

Additionally, some worry about data

fragmentation.

Even the best AI platform can’t magical-

ly unify data if the underlying infrastruc-

ture is siloed across multiple providers.

However, the push toward “cleanroom”

solutions — secure environments where

data can be shared without compromising

privacy — ofers a potential workaround. AI

will have more fuel to optimize campaigns

while respecting consumer privacy as

these environments mature.

The message for broadcasters look-

ing to thrive in this changing landscape is

clear: AI isn’t just about easing workﬂows

in the control room or the editing suite. It’s

also about enabling precision, efciency

and agility in ad operations.

“AI’s ability to efciently and accurate-

ly search, tag and categorize content can

help surface hidden assets,” Lederer said,

pointing to a key value driver. Pair that

with advanced forecasting capabilities,

and a broadcaster can proactively reprice

ad inventory, develop niche sponsorships

or respond in real time when a piece of

content suddenly goes viral.

The marriage of AI and advertising is no

passing fad. Programmatic is blossoming,

CTV is surging and the lines between digi-

tal and linear are blurring faster than ever

before.

For those who embrace the change, AI

could ofer a fast track to sustained rev-

enue growth. For everyone else, it’s a re-

minder that the old methods of selling

commercials at set times may no longer

cut it in a world fueled by data, personal-

ization and on-demand viewing.

Ultimately, the real impact of AI on mon-

etization and advertising is measured

in what it delivers: more relevant cam-

paigns for consumers, stronger returns

for marketers and new revenue streams

for broadcasters. And given the rapid ad-

vancements, it’s safe to say that this is just

the beginning of AI’s inﬂuence on the fu-

ture of advertising.



Continued from previous page

‘Upskilling,’ new roles created

by use of artiﬁcial intelligence

WORKFORCE

While AI has proven its ability to auto-

mate mundane tasks, it will likely also re-

shape how broadcast teams work — and

the skill sets they need to thrive.

“The goal of AI-powered technology

should be to empower creativity, not re-

place creatives,” said Bob Caniglia, direc-

tor of sales operations, Americas, Black-

magic Design.

“By using AI and machine learning to

streamline workﬂows and eliminate re-

petitive tasks, production teams will have

more bandwidth to learn new skills and

focus on the creative aspects of the job,

including storytelling. Time is a scarce

resource in broadcasting, and these tools

help make it more plentiful,” said Caniglia.

Many vendors in our recent Industry

Insights roundtable see AI as a tool that

can relieve skilled professionals of routine

tasks such as repetitive editing, transcrib-

ing or tagging footage. However, the larger

shift calls for new proﬁciencies.

To capitalize on AI’s potential, organi-

zations need staf who understand both

traditional production practices and the

intricacies of AI-driven processes — rang-

ing from machine learning models to data

ethics and algorithmic bias.

“The rise of AI and machine learning

places new skills demands on production

professionals,” said Costa Nikols, strategy

advisor for media and entertainment at Te-

los Alliance.

“While traditionally manual-intensive

processes like quality control can be as-

sisted by machine learning tools, users

are beginning to take on more data-driv-

en tasks that require them to engage with,

and understand, new data outputs and

manage automated workﬂows. This evolu-

tion demands a blend of digital-ready intu-

ition and deep technical expertise,” added

Nikols.

Yet the fear of displacement persists. As

more tasks become automated, there is an

expectation that some roles could be ren-

dered obsolete.

Jordan Thomas, marketing manager at

QuickLink, ofered a balanced perspec-

tive, noting that while AI will likely make

certain positions redundant, “new oppor-

tunities will emerge in areas like AI man-

agement, content optimization, data ana-

lytics and virtual production.”

In this sense, AI is less about job elimi-

nation and more about job evolution.

Instead of diminishing the size of the

workforce, it can push employees to adopt

specialized roles.

Upskilling for the AI era

Because new technology often ampliﬁes

the gap between the technologically ad-

ept and those tied to older methods, many

organizations are investing in training

programs that address both the technical

and creative dimensions of AI and other

emerging technology.

Peyton Thomas, product manager at

Panasonic Connect, said broadcasters

should begin preparing their workforce

now “by adopting software-deﬁned plat-

forms and new transport protocols,” en-

suring that future AI innovations will more

easily slot into existing environments.

For some employees, upskilling could

mean learning to operate automated cam-

era systems that use AI for tracking and

framing. For others, it might mean under-

standing how to manage advanced meta-

data tagging or AI-driven analytics that

guide decisions about content production

and distribution.

Simon Parkinson, managing director of

Dot Group, emphasized that “technology

must shrink the skill gap rather than widen

it” if businesses are to gain real value from

their AI investments.

“Many technologies, especially within

AI, are focused on the user,” he said, “thus

designed to work alongside the colleague,

rather than instead of them.”

Building a culture of continuous learn-

ing

Beyond technical know-how, developing

a broader culture of adaptability is critical.

Constant advances in AI — particularly in

areas such as language models, real-time

analytics and generative content — make it

essential for workers to keep reﬁning their

skills.

“Promoting continuous education en-

sures teams can keep pace with techno-

logical advances and the latest updates,

building conﬁdence and expertise in

adopting these solutions,” said Caniglia.

Companies ﬁnd that hands-on demon-

strations and trial runs can quickly quell

apprehension and show proof of concept

for these new tools.

Continued on next page

NEWSCASTSTUDIO.COM

By DAK DILLON

Editor in Chief, NewscastStudio

The narrative surrounding artiﬁcial in-

telligence in journalism has oscillated

between doomsday predictions and uto-

pian promises. Headlines warn of “robot

reporters,” while some tech evangelists

paint pictures of newsrooms liberated

from all mundane tasks. At a recent U.S.

Senate hearing, media executives de-

scribed generative AI as an “existential

threat” to journalism’s future.

This alarmist storyline resonates in an

industry battered by budget cuts and de-

clining trust.

Yet the reality is far less dystopian and

far more nuanced.

“You do not automate people out of

their jobs. You actually automate tasks

that they hate doing,” noted Claudia Qui-

nonez, Bloomberg’s managing editor for

news automation. CNN’s VP

of data science similarly main-

tains that AI exists “to enable

journalists to do what they do

best,” though the claim that

“creativity will never be re-

placed by machines” deserves

scrutiny rather than blind ac-

ceptance.

In practice, AI currently

serves as a productivity tool

with speciﬁc applications rath-

er than a wholesale replace-

ment for journalistic judg-

ment.

The bottlenecks

in modern newsrooms

Many newsrooms operate with legacy

systems and workﬂows that create genu-

ine bottlenecks. Journalists often function

as “human middleware,” man-

ually transferring content be-

tween disconnected systems.

Breaking news alerts can be

delayed by multiple approv-

al layers designed initially for

deadlines.

Reporters

spend valuable time refor-

matting stories for diferent

platforms instead of reporting.

Analytics

frequently

arrive

too late to inform timely edi-

torial decisions. These inef-

ciencies drain resources and

contribute to journalists’ high-

er-than-normal burnout rate.

The industry’s “doing more with less”

approach has created unsustainable work-

loads that technology could alleviate.

AI isn’t killing journalism

but it could kill inefciency

DAK’S TAKE

New roles, new responsibilities

As AI becomes further embedded in pro-

duction workﬂows, employees will likely

manage tasks related to data curation, sys-

tem monitoring and ethics compliance.

This shift invites the creation of new job

titles such as AI content analysts or data

asset managers, positions that blend tradi-

tional broadcast knowledge with modern

data skills.

According to Thomas, these new roles

require “adapting legacy systems to inte-

grate with AI tools” and training staf to

capitalize on rapidly evolving capabilities.

Some organizations are also hiring ded-

icated AI specialists — people with back-

grounds in computer science and machine

learning — to work alongside content cre-

ators and production teams. This collabo-

rative approach can ensure that AI imple-

mentations remain grounded in real-world

broadcast needs rather than becoming

purely theoretical exercises.

Overcoming resistance and concerns

Even with clear beneﬁts, resistance to AI

can run high among employees who worry

about job security or distrust algorithmic

decision-making.

“Seeing it as more of an enabler, or

‘time generator’—speeding up the less in-

teresting or repetitive parts of the creative

process—can help teams focus on compel-

ling storytelling,” said Steve Taylor, chief

product and technology ofcer at Vizrt,

acknowledging the challenges.

Industry leaders argue that when staf

realize AI can eliminate tedious tasks like

repeatedly logging or searching video

footage, they’re more inclined to embrace

it. A key talking point is that AI-powered

workﬂows allow human teams to dedicate

more attention to the high-level storytell-

ing and editorial judgments that artiﬁcial

intelligence cannot replicate — at least not

yet.

While the AI transformation in broad-

casting is already underway, the speed and

extent of adoption will vary across organi-

zations.

One certainty is that jobs will continue to

evolve as technology does. Experts agree

that embracing AI does not mean losing

the human element; instead, it means el-

evating it by creating space for creativity,

deeper insights, and more thoughtful con-

tent.

“We’re entering a time where mundane,

repetitive tasks can be quickly automat-

ed,” said Parkinson. “The real question for

broadcasters is how to harness the tech-

nology to empower teams, keep audiences

engaged, and fuel sustainable growth.”

In the coming years, broadcast em-

ployees will need to understand AI well

enough to guide and control it — whether

that’s in studio automation, post-produc-

tion analytics or personalized content rec-

ommendations. As AI becomes integrated

into day-to-day operations, the most suc-

cessful teams are likely to be those that

combine technological ﬂuency with the

timeless craft of storytelling.



Continued from previous page

Continued on next page

DILLON

VOICES

Artiﬁcial intelligence is reshaping the me-

dia and entertainment industry, with NAB

Show 2025 placing AI at the center of dis-

cussions on content creation, distribution

and audience engagement.

PropelME, NAB Show’s startup-focused

hub, is highlighting AI-driven solutions

in partnership with FBRC.ai, a company

known for connecting emerging AI innova-

tors with industry leaders.

The collaboration brings a dedicated

show ﬂoor destination featuring AI-pow-

ered tools and discussions. The new Start-

up Stage will host conversations on AI’s role

in hybrid production workﬂows, as well as

its impact on personalized audience expe-

riences. Additionally, the Startup Showcase

will provide rapid presentations from com-

panies demonstrating AI solutions, with au-

dience members selecting a standout start-

up for an in-depth Fireside Chat.

NAB Show 2025 also includes hands-on

AI workshops, such as “Getting Started with

Generative AI,” designed to give creators

practical experience with AI tools used for

content generation. Companies exhibiting

in PropelME include Advanced Image Ro-

botics, Anantadi, AudioShake and others.

Beyond the startup space, AI will be a key

focus across NAB Show programming.

The AI Innovation Pavilion will show-

case advancements in AI-powered media

technology, while Post|Production World

expands its AI track to cover AI-driven vid-

eo editing, motion graphics and animation.

Sessions such as “Safeguarding IP in the Era

of AI” and “DeepSeek and the New Reality”

will address AI’s implications for intellectual

property and media ethics.

Industry leaders are closely monitor-

ing AI’s economic impact. According to

McKinsey & Company, generative AI could

contribute between $380 billion and $690

billion to the global economy, while Straits

Research projects the AI media and enter-

tainment market will exceed $104.4 billion

by 2030.

“NAB Show brings together emerging

technologies and visionary creators to ex-

plore AI’s ability to enhance storytelling,”

said Karen Chupka, executive vice presi-

dent and managing director, NAB Global

Connections and Events.

Registration for NAB Show 2025 is now

open. Media professionals can sign up for

updates on AI-focused programming and

exhibitors.



NAB SHOW PREVIEW

NAB Show planing AI speakers, sessions

NAB Show 2025 returns to the Las

Vegas April 5 to 9, 2025, with exhibits

running April 6 to 9, 2025.

NAB Show has evolved to embrace

artiﬁcial intelligence, the creator

economy, sports and streaming.

Sports Summit: A two-day event

that will explore trends, tech and

opportunities that are transforming the

fan experience, remodeling the business

with new licensing opportunities and

redeﬁning the media rights landscape.

Expanded Creator Lab: A dedicated

marketplace for all brands, creators

and inﬂuencers to learn and conduct

business on the show ﬂoor in this

evolving media universe.

Artiﬁcial Intelligence: From

enhancing storytelling to personalizing

viewer experiences and increasingre

venue opportunities, AI technologies will

permeate the show ﬂoor and dedicated

tracks for all leaders.

To register: https://nca.st/nabvegas

NEWSCASTSTUDIO.COM

Cloud adoption and streaming technol-

ogy investments lead broadcast industry

priorities, while concerns about artiﬁcial

intelligence and workﬂow challenges per-

sist, according to NewscastStudio’s annual

industry survey.

The survey gathered responses from 312

broadcast and media professionals. Among

respondents, 30% make ﬁnal purchasing

decisions, while 52% contribute to product

research and speciﬁcations. Sixty-seven

percent identify as long-term Newscast-

Studio readers, having followed the publi-

cation for over a year.

Digital transformation progress

Sixty percent of broadcast profession-

als report implementing cloud production

tools, though implementation challenges

remain. Cost emerged as the primary bar-

rier, cited by 33% of respondents, followed

by workﬂow complexity (25%), security

concerns (17%), lack of technical expertise

(15%) and uncertain return on investment

(9%).

Two-thirds of organizations report in-

vesting in streaming, FAST or OTT delivery

tools, highlighting the industry’s continued

shift toward digital distribution.

“A big question for my newsroom is

how to translate what we make for TV to

third-party, online platforms. The work-

ﬂows for this are slow and clunky... just to

get one broadcast segment published on-

line,” a survey respondent noted.

Industry innovation

and adaptation

Sixty percent of respondents agree

the industry is adapting to technological

change, while 44% believe the broadcast

industry is innovating in coverage. Regard-

ing workﬂow solutions, 51% agree current

broadcast production solutions meet their

needs.

One respondent addressed the state

of local news: “The mindset in local news

needs to shift to survive in a new time when

content is more accessible and local news

isn’t as necessary as it once was.”

Artiﬁcial intelligence emerges as both a

tool and concern for broadcast profession-

als. Forty-four percent report their orga-

nizations are implementing AI or machine

learning tools in everyday workﬂows. How-

ever, 51% express concern that AI technol-

ogy could eventually replace their position.

“AI and viewers getting information from