AI in Media & Broadcast – Professional Essentials Guide

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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

Continued on next page

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