VCs, Family Offices and Celebrities Increase Investment in AI Startups Across Media, Entertainment and Sports
Artificial intelligence investment is expanding beyond foundational models and enterprise software as venture capital firms, family offices and celebrities increasingly back startups applying AI to media, entertainment and sports, creating a new investment category around content production, localisation, digital intellectual property and fan engagement.
The emerging investment wave includes capital from:
Premji Invest, Peak XV Partners, IAN Alpha Fund, celebrity-backed family offices and individual actors and sports personalities.
Recent transactions illustrate the breadth of the trend.
Premji Invest participated in generative-video company Runway's $315 million Series E round.
Peak XV led a $13 million Series A investment in Dashverse, an AI-powered entertainment company operating across India and the US.
IAN Alpha Fund led a ₹33 crore funding round in Mumbai-based SportVot, which uses artificial intelligence for automated sports production, streaming and analytics.
Celebrity capital is also entering the market.
Shah Rukh Khan's family office is among the investors in Mythik, a technology-led entertainment company focused on bringing Eastern mythology, history and folktales to global audiences.
Former Indian cricketer and coach Ravi Shastri is backing Smartan FitTech, which uses AI and computer vision to analyse athlete movement and help reduce injury risk.
Meanwhile, actors are moving beyond investing and becoming founders themselves.
Bhumi Pednekar has founded Maya, which uses AI-enabled production workflows across music videos, advertising and films, while Ajay Devgn has founded Prismix, a generative-AI storytelling venture serving filmmakers, brands and creators.
The common investment thesis is increasingly clear:
AI can dramatically lower the cost and time required to create, localise, distribute and monetise media while simultaneously generating new forms of intellectual property and audience engagement.
AI Investment Is Moving From Infrastructure to Applications
The first phase of the generative-AI investment boom concentrated heavily on:
large language models,
foundation models,
chips,
cloud computing,
and enterprise AI infrastructure.
Those areas continue to attract substantial capital.
But investors are increasingly searching for:
application-layer businesses.
These companies use existing AI models and infrastructure to solve specific commercial problems.
Media, entertainment and sports provide particularly attractive testing grounds because all three industries involve enormous quantities of:
video,
audio,
images,
data,
and intellectual property.
Media Has Three Expensive Bottlenecks
Traditional media businesses face three particularly expensive challenges:
content creation,
localisation,
and:
distribution.
Generative AI can potentially affect all three.
Video can be created or edited more quickly.
Dialogue can be dubbed into additional languages.
Marketing material can be automatically adapted for different audiences.
Content libraries can be searched, classified and repackaged more efficiently.
This creates a powerful economic proposition for investors.
AI Can Reduce Content Production Costs
Professional content creation has historically required large teams.
A production may involve:
writers,
directors,
editors,
visual-effects artists,
animators,
voice actors,
designers,
and production staff.
AI does not necessarily eliminate these roles.
But it can automate portions of their workflows.
A creator can potentially move from:
concept
to:
prototype
much faster.
That allows media companies to test more ideas without committing conventional production budgets to every experiment.
Runway Demonstrates Scale of Generative Video Investment
One of the largest examples is:
Runway.
The New York-headquartered generative-AI company develops technology for:
video generation,
video editing,
and world modelling.
Premji Invest participated in Runway's:
$315 million Series E financing.
The investment demonstrates that Indian capital is participating not only in domestic AI startups but also in globally significant companies developing foundational tools for:
next-generation media production.
Premji Invest Extends AI Exposure Into Creative Technology
Premji Invest is the investment organisation associated with:
Azim Premji.
Its participation in Runway reflects growing institutional interest in AI's impact on:
creative industries.
Generative video could eventually influence:
films,
advertising,
gaming,
social media,
education,
and corporate communications.
That gives the technology a market far larger than conventional filmmaking alone.
Dashverse Raises $13 Million
Dashverse represents a different part of the AI entertainment stack.
The company operates across the:
US
and:
India
and was founded by:
Sanidhya Narain,
Lalith Gudipati,
and:
Soumyadeep Mukherjee.
Peak XV Partners led its:
$13 million Series A round.
Dashverse uses AI to support the creation and distribution of:
short-form mobile dramas
and:
digital comics.
Short-Form Drama Is Emerging as Major Format
Short-form episodic entertainment is growing rapidly as consumers increasingly watch content on:
smartphones.
Episodes can be only a few minutes long.
The format is designed around:
vertical video,
fast storytelling,
and frequent releases.
But producing a large volume of episodes conventionally can be expensive.
AI can potentially improve the economics by accelerating:
writing,
visual creation,
editing,
localisation,
and promotional content.
AI Could Industrialise Microdrama Production
Microdramas require:
high content velocity.
A platform may need hundreds or thousands of episodes to maintain user engagement.
AI-assisted workflows can allow companies to create and test stories much faster.
Successful concepts can then receive:
larger budgets
or:
human-led production investment.
This creates a content model that increasingly resembles:
software experimentation.
AI Is Also Changing Sports Production
Sports represents another large opportunity.
Major professional leagues already have sophisticated:
broadcasting,
analytics,
and production infrastructure.
But thousands of smaller sporting events do not.
Regional competitions,
school tournaments,
amateur leagues,
and grassroots sports
may not have the economics to support:
professional camera crews
and:
production teams.
AI can change that equation.
SportVot Raises ₹33 Crore
Mumbai-headquartered:
SportVot
raised approximately:
₹33 crore
in a funding round led by:
IAN Alpha Fund
in April 2026.
The company was founded by:
Sidhhant Agarwal,
Shubhangi Gupta,
and:
Yash Bhagwatkar.
SportVot uses AI across:
sports production,
streaming,
analytics,
and athlete discovery.
SportVot Automates Match Highlights
SportVot's technology can identify important moments in sporting events.
These might include:
a football goal
or:
a decisive basketball play.
The system can then:
clip the footage,
format it,
tag it,
and make it available
without waiting for conventional manual editing.
That substantially shortens the gap between:
an event happening
and:
content reaching viewers.
AI Can Make Grassroots Sports Broadcastable
The economics are important.
Professional production teams are expensive.
For smaller competitions, broadcasting costs can exceed:
commercial revenue.
Automated production can reduce that barrier.
If a local sports tournament can be streamed economically, organisers can potentially create:
advertising inventory,
sponsorship opportunities,
audience data,
and digital archives.
This turns previously unmonetised sporting events into:
media assets.
Athlete Discovery Is Another Opportunity
AI sports systems can also analyse:
individual players.
Computer vision can track:
movement,
positioning,
and specific actions.
Player-specific clips can then be generated for:
coaches,
scouts,
teams,
and athletes.
This could be particularly useful in India, where talented athletes may participate in regional competitions far from:
major professional scouting networks.
Ravi Shastri Backs Smartan FitTech
Former India cricketer and coach:
Ravi Shastri
is among the investors in:
Smartan FitTech.
The Chennai-based company uses:
artificial intelligence
and:
computer vision
to analyse athlete movement.
Its technology is designed partly around:
sports performance
and:
injury prevention.
The investment demonstrates how sports personalities can bring more than capital to AI startups.
Athletes Can Provide Domain Expertise
A professional athlete or coach understands problems that conventional technology investors may not immediately recognise.
These can include:
training load,
movement patterns,
injury risk,
scouting,
performance analysis,
and coaching workflows.
That makes athletes potentially valuable:
strategic investors.
Their industry networks can also help startups reach:
teams,
academies,
leagues,
and other customers.
Shah Rukh Khan Family Office Backs Mythik
Celebrity investment is also moving into:
AI-enabled entertainment intellectual property.
Shah Rukh Khan's family office has invested in:
Mythik
alongside other investors.
The company was founded by:
Jason Kothari,
who previously held senior leadership positions at businesses including FreeCharge and Housing.com.
Mythik is building an entertainment platform around:
Eastern mythology,
history,
and folktales.
Mythik Targets Global Audiences
The underlying opportunity is enormous.
Asia contains thousands of years of:
mythology,
historical narratives,
folklore,
and cultural characters.
Yet only a relatively small proportion has been transformed into:
globally distributed entertainment franchises.
Technology can potentially lower the cost of turning these stories into:
visual media,
interactive experiences,
and other intellectual property.
AI Could Unlock Large Cultural Libraries
Traditional entertainment economics limit the number of stories that can receive:
large production budgets.
AI-assisted workflows can change this.
A company could potentially experiment with many more:
characters,
stories,
visual styles,
and formats
before deciding which concepts justify significant investment.
For culturally rich markets such as India, this could unlock enormous archives of:
underutilised intellectual property.
Celebrity Investors Have a Unique AI Thesis
Celebrity participation in AI entertainment differs from conventional angel investing.
Actors, musicians and athletes already own valuable intangible assets:
their likeness,
voice,
audience,
creative identity,
and fandom.
AI can potentially extend these assets into:
new formats,
languages,
markets,
and digital experiences.
This creates a direct strategic reason for celebrities to understand and invest in AI.
AI Can Multiply Celebrity IP
A celebrity's economic value has historically been constrained by:
time.
An actor can only shoot a limited number of advertisements.
A musician can record only so much material.
An athlete can attend only a limited number of events.
Digital technologies reduce some of those constraints.
AI-generated or AI-assisted experiences can potentially allow celebrity intellectual property to appear across:
more content,
more languages,
and more personalised interactions.
Digital Likeness Is Emerging as an Asset
This has contributed to a new investment category around:
digital identity.
A celebrity's authorised digital likeness can potentially be licensed for:
advertising,
interactive entertainment,
virtual appearances,
games,
and personalised media.
The commercial opportunity is substantial.
But so are the legal and ethical questions.
Consent Becomes Critical
The same technology that can monetise an authorised likeness can also produce:
deepfakes.
This makes:
consent,
ownership,
licensing,
and authentication
critical.
Entertainment companies will increasingly need clear contracts governing:
how a person's image,
voice,
and performance data
can be used.
Without strong rights management, AI could create major disputes between:
talent,
studios,
platforms,
and technology providers.
Bhumi Pednekar Moves From Investor to Founder
Actor:
Bhumi Pednekar
has taken a more direct approach by founding:
Maya.
The venture focuses on AI-enabled production workflows for:
music videos,
advertising campaigns,
and:
feature-length films.
This places a working actor directly inside the emerging AI production ecosystem.
The model illustrates how creative professionals may increasingly become:
technology entrepreneurs.
Maya Targets Production Workflows
AI production companies can assist with several stages of the creative process.
These include:
pre-visualisation,
concept development,
storyboarding,
visual generation,
post-production,
and localisation.
The value proposition is not necessarily to produce every frame without humans.
It is to reduce:
production friction.
Faster workflows can make projects economically viable that previously would have been:
too expensive
or:
too time consuming.
Ajay Devgn Founds Prismix
Actor and producer:
Ajay Devgn
has founded:
Prismix.
The company specialises in:
generative-AI storytelling
for:
filmmakers,
brands,
and creators.
The move is significant because Devgn already has extensive experience across:
film production
and:
visual effects.
Generative AI adds another layer to the technology-driven transformation of entertainment production.
Filmmakers Are Becoming Technology Entrepreneurs
Film producers have historically invested in:
studios,
cameras,
editing systems,
and visual-effects infrastructure.
AI represents the next technological layer.
Creative entrepreneurs can now build businesses around:
generative video,
synthetic characters,
automated post-production,
and virtual production.
The boundary between:
film studio
and:
technology company
is becoming less clear.
Brands Could Become Major Customers
Advertising may be one of the fastest commercial markets for generative media.
Brands constantly require:
campaigns,
product images,
social-media videos,
regional adaptations,
and personalised creative.
Traditional production can become expensive when the same campaign must be recreated across:
multiple languages
and:
audiences.
AI can dramatically increase the number of variations produced from a single creative concept.
Localisation Is Particularly Important in India
India is an unusually attractive market for AI localisation because of its:
linguistic diversity.
A successful video may need versions in:
Hindi,
Tamil,
Telugu,
Bengali,
Marathi,
Kannada,
Malayalam,
and other languages.
Traditional dubbing and localisation require:
time
and:
money.
AI-assisted voice and video technology can reduce both.
Localisation Can Expand Addressable Markets
The economics extend beyond India.
A successful Indian entertainment property can potentially be translated into:
dozens of languages.
Similarly, global content can be adapted for Indian audiences.
AI therefore changes localisation from a:
cost centre
into:
a growth tool.
The easier content becomes to localise, the larger its potential audience becomes.
Distribution Is Also Being Automated
Creating content is only one part of the problem.
Media companies must also decide:
where,
when,
and to whom
content should be distributed.
AI can analyse:
audience behaviour,
engagement,
content characteristics,
and platform performance.
It can then help determine which content should be promoted to:
specific audience segments.
Personalised Entertainment Could Expand
Recommendation engines already personalise:
what people watch.
Generative AI could eventually personalise:
the content itself.
Different viewers could receive variations in:
language,
length,
presentation,
or even narrative.
This would represent a major shift from traditional mass media, where every viewer receives essentially:
the same product.
India’s Wider AI Funding Pool Is Expanding
The media and sports investment trend is occurring within a much larger increase in:
Indian AI funding.
Indian AI startups raised approximately:
$928 million across 153 deals in 2025.
That represented an increase of around:
27%
from approximately:
$728 million
across 148 deals in 2024.
The number of venture funds explicitly focusing on AI has also risen sharply.
Sixteen AI-Focused Funds Raised $1.87 Billion
During 2025:
16 India-focused venture funds
that either specialised in AI or identified it as a major investment theme raised approximately:
$1.87 billion.
That compared with only:
five funds
raising approximately:
$358 million
in 2024.
The increase substantially expands the pool of capital available to:
AI-native founders.
Early-Stage Deals Dominate AI Investment
AI funding in India remains heavily concentrated in:
early-stage companies.
Seed through Series A transactions represented close to:
80% of AI deals in 2025.
Early-stage funding value rose approximately:
70%
to:
$538 million
from $316 million a year earlier.
This suggests investors are trying to establish positions before:
category leaders
have fully emerged.
Major VC Firms Are Ring-Fencing AI Capital
Large venture firms operating in India are increasingly treating AI as a:
core investment theme.
Investors active in the ecosystem include:
Bessemer Venture Partners,
Nexus Venture Partners,
Accel,
Lightspeed Venture Partners,
Stellaris Venture Partners,
Peak XV Partners,
and Elevation Capital.
Some are allocating significant portions of new funds specifically toward:
AI-first businesses.
Stellaris Has Earmarked Half of Fund III for AI
Stellaris Venture Partners' approximately:
$300 million Fund III
has earmarked around:
half of its corpus
for AI investments.
This illustrates the scale of the shift.
AI is no longer being treated simply as one technology category among many.
It is increasingly becoming a layer through which investors evaluate:
almost every new business model.
Family Offices Are Becoming More Important
Family offices represent another increasingly significant source of capital.
Indian family-office assets were estimated at approximately:
₹70,000 crore in 2024
and are projected to increase by roughly:
1.5 times over the following three years.
This growing capital base is becoming more sophisticated in how it invests.
Alternatives Account for 40–45% of Some Family-Office Portfolios
Many Indian family offices now allocate approximately:
40–45%
of their portfolios to alternative assets.
These can include:
private equity,
venture capital,
private credit,
AIFs,
REITs,
and InvITs.
They are also increasingly pursuing:
direct investments
and:
co-investments.
AI has emerged as one of the sectors receiving greater attention.
Family Offices Can Invest With Longer Horizons
Family offices can have an advantage when investing in emerging technology.
Unlike conventional venture funds, they may not always face the same:
fund-life
or:
exit-timing constraints.
That can allow them to support businesses requiring:
longer development periods.
Media intellectual property and advanced AI products may benefit from:
patient capital.
Celebrities Add Distribution as Well as Capital
Celebrity investors offer another advantage:
distribution.
A famous actor or athlete can instantly expose a startup to:
millions of potential customers.
Their participation can provide:
credibility,
media attention,
brand partnerships,
and industry access.
This means the economic value of a celebrity investor can extend well beyond the size of the cheque.
But Celebrity Capital Requires Governance
Celebrity involvement does not automatically create:
a successful company.
Startups still require:
product-market fit,
financial discipline,
strong management,
technology,
and scalable economics.
Celebrity-led companies also need clear separation between:
brand visibility
and:
business fundamentals.
Investors will ultimately judge these ventures on sustainable revenue and intellectual-property creation.
AI Media Startups Face High Computing Costs
Generative media is computationally expensive.
Video generation requires substantially more:
processing power
than many text applications.
That can create high:
cloud
and:
GPU costs.
A startup may attract users quickly but still struggle to generate attractive margins if the cost of producing each video remains high.
Unit economics will therefore be a critical factor.
Model Dependence Creates Another Risk
Many application-layer companies do not build their own foundational models.
Instead, they rely on technology supplied by:
third-party AI companies.
This can accelerate product development.
But it creates dependency.
If a model provider changes:
pricing,
access,
terms,
or capabilities,
the startup's economics can change rapidly.
Successful companies may therefore need proprietary:
data,
workflows,
distribution,
or IP
to build defensibility.
Copyright Remains Major Challenge
Generative AI creates unresolved questions around:
copyright.
Models can be trained on enormous amounts of:
text,
images,
music,
and video.
Rights holders increasingly want clarity over:
consent,
compensation,
and attribution.
Media startups need robust approaches to:
training data,
licensing,
and ownership
if they want to work with major studios, brands and celebrities.
Sports Data Has Similar Rights Questions
Sports also contains valuable intellectual property.
Leagues and federations may control rights relating to:
broadcast footage,
statistics,
logos,
and competitions.
AI companies building analytics or automated media products need clear access to:
underlying data
and:
video rights.
Technology does not eliminate traditional sports-rights economics.
It creates new ways to extract value from them.
Human Creativity Remains Central
AI can make content production faster.
But investors are increasingly recognising that technological capability alone is not enough.
Entertainment depends on:
stories,
characters,
emotion,
taste,
and cultural relevance.
The strongest companies may therefore combine:
AI efficiency
with:
human creative judgement.
The same applies in sports, where technology must ultimately serve athletes, fans and organisations.
Investors Are Looking for Proprietary IP
One of the strongest potential competitive advantages is:
intellectual property.
An AI tool can be copied or displaced.
A successful character,
sports dataset,
entertainment franchise,
or creator network
can be more durable.
Investors are therefore increasingly interested in businesses that use AI not merely to:
produce content
but to:
own valuable content and audiences.
AI Is Changing the Economics of Experimentation
Perhaps the biggest structural shift is the cost of:
trying an idea.
Traditional entertainment requires substantial capital before audiences can respond.
AI can allow creators to produce:
concepts,
trailers,
short episodes,
visual prototypes,
and marketing material
at far lower cost.
Audience response can then determine which ideas deserve:
larger investment.
This reduces the financial cost of failure.
Media Could Become More Data-Driven
As production becomes cheaper, media companies can test more ideas.
That generates more:
audience data.
Creative decisions could increasingly combine:
human instinct
with:
real-time analytics.
This may change how studios decide:
which stories to develop,
which characters to expand,
and which markets to target.
Sports Can Unlock Long-Tail Content
Professional sports broadcasting focuses naturally on:
major leagues
and:
star athletes.
AI makes it possible to monetise the:
long tail.
Thousands of smaller games can potentially be:
recorded,
analysed,
clipped,
and distributed.
That can create new audiences for:
regional sports,
young athletes,
and amateur competitions.
For India, with its enormous population and diverse sporting ecosystem, the opportunity could be substantial.
Conclusion
Venture capital firms, family offices and celebrities are increasingly moving into AI startups across media, entertainment and sports as investment attention shifts from foundational technology toward applications capable of solving expensive real-world problems.
Recent transactions illustrate the breadth of the trend. Premji Invest participated in Runway's $315 million Series E round, Peak XV led a $13 million investment in AI entertainment company Dashverse, and IAN Alpha Fund led SportVot's ₹33 crore funding round.
Celebrity participation is adding another dimension. Shah Rukh Khan's family office has backed Mythik, Ravi Shastri is investing in Smartan FitTech, while Bhumi Pednekar and Ajay Devgn have moved directly into entrepreneurship through Maya and Prismix.
The broader capital environment is also becoming more supportive. Indian AI startups raised approximately $928 million across 153 transactions in 2025, while 16 AI-focused or AI-heavy venture funds raised about $1.87 billion, substantially increasing available investment capital.
Family offices are simultaneously allocating more money toward private markets and emerging sectors such as AI, while celebrities bring something conventional investors cannot easily replicate:
audience, intellectual property, industry knowledge and distribution.
The opportunity is particularly significant because AI directly addresses three of the most expensive challenges in entertainment:
creating content, localising it and distributing it.
In sports, the same technology can automate production, analyse athletes and turn previously uneconomic grassroots competitions into digital media.
The next phase of AI investing may therefore be determined less by who builds the largest underlying model and more by which companies can use those models to create valuable intellectual property, sustainable audiences and commercially defensible businesses.