AI in Media & Broadcast – Professional Essentials Guide

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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.

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‘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

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