AI Meets The Games Industry

How developers are using generative AI to
create a new generation of games

02
Introduction
The games industry is currently in the midst of profound changes, with development costs rising,
markets increasingly saturated, and players gravitating toward older games—all of which
underscore the need for studios to continuously innovate.
In this landscape, generative AI (gen AI) has emerged as a powerful ally. Currently, 97% of game
developers say that gen AI is reshaping the industry, leading to intense experimentation,
AI-integrated workflows, and enhanced player experiences.
But how are these innovations playing out for developers? What impact is AI having on the
industry? Is it opening up new opportunities for careers—or even companies? What types of
gameplay are being created? How is it impacting game development pipelines? Where are the
most promising avenues for growth? And what concerns is it raising?
To find the answers to these questions and more, Google Cloud and The Harris Poll conducted a
research study in late June and early July 2025 with 615 game developers in the United States,
South Korea, Norway, Finland, and Sweden. In the following pages, you can find the highlights of
this survey and their implications for both the current state of AI in the industry, and where it may
be heading next.
02

Executive summary
The study confirmed the massive impact of gen AI on game development, with respondents largely agreeing that it is having a positive influence
across a wide range of creative efforts, business settings, and internal workflows. However, it’s clear that game developers face some hesitancy
around the adoption of gen AI, particularly due to data and ownership rights. Key findings include:
AI is already ubiquitous in game development, playing a major role in streamlining repetitive tasks and enhancing creative workflows. This is helping to level the playing field, allowing innovative new startups to compete with larger, more established studios.
Universal adoption:
AI agents are also on the rise. Developers are building and deploying them for intelligent nonplayer character (NPC) behavior, dynamic gameplay balancing, and much more. Promising new trends:
New AI-based roles are emerging, while existing jobs are increasingly integrating AI into their workflows, with 90% of games developers already using it in their work. New roles and responsibilities:
89% of developers report that AI integration is changing player expectations, with 37% seeing gamers looking for more lifelike experiences. Rising player expectations:
While AI shows promise in addressing longstanding issues in the industry and in game development, 63% of developers also express concerns about data ownership, while 35% worry about player data privacy. Ownership considerations:
03

AI’s winning role
The games industry has long been ultra-competitive,
but in recent years, it has navigated a rising tide of
layoffs, studio closures, longer development cycles
for new games, and skyrocketing costs for major
titles. For smaller studios, standing out against a sea
of new releases has grown increasingly difficult. In this environment, developers overwhelmingly see
gen AI as a positive development, and one that is
leading to better outcomes. When it comes to general
impact, more than 90% of developers say it is helping
with an array of challenges, including driving innovation
and enhancing the player experience.
The survey finds AI is receiving a positive reception in the games
industry—and opening up new possibilities.
Most promising trends perceived by games professionals:
36%
AI-powered
testing and QA
40%
AI for balancing
gameplay
40%
AI-driven
game engines
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AI especially shines in its ability to automate cumbersome and
repetitive tasks, freeing developers to focus on more strategic
and creative concerns—not to mention reducing iteration
cycles and decreasing time-to-market. In particular, 47% of
developers report that it is speeding up playtesting and
balancing of mechanics, 45% say it is assisting in localization
and translation of game content, and 44% cite it for improving
code generation and scripting support. Developers in the
United States report this more so than those in South Korea,
especially when it comes to AI-driven playtesting, automated
content tagging, and enhanced code generation.And, some see AI as a transformative force in the broader
industry: driving democratization across studios and enabling
independent studios to level the playing field with more
established players.
29%
say it is democratizing
the games industry
see gen AI reshaping the industry
97%
say it is reducing repetitive tasks in workflows
95%
say it is driving innovation
94%

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The research revealed that a significant subset of developers is already
deploying AI agents in their games. For example, 44% are using AI agents
for content optimization, 38% for dynamic balancing and tuning of
gameplay, and 38% for in-game coaching and automated tutorials.
Developers in the United States are deploying agents at a faster rate than
other markets, with a particular focus on NPC behavior, automated testing,
and in-game coaching and advanced tutorials.
This signals a shift toward systems that respond in real time, reducing
the need for manual adjustments, and enabling more flexible and
dynamic game environments. For example, games today can feature
NPC agents that can intelligently collaborate with each other to attack
a player using complex strategies like flanking, weapon-sharing, and
even setting traps and modifying terrain features to gain an
advantage. AI agents can also vary the difficulty of the scenario to
match each playing style or ability of the player.
AI agents are software systems that use AI to pursue goals and
complete tasks on behalf of users. They can demonstrate
reasoning, planning, and memory, and have a level of autonomy to
learn, adapt, and make decisions.
These capabilities are made possible in large part by the multimodal
capacity of gen AI and AI foundation models. As a result, agents can
process information, such as text, voice, code, audio, and video,
enabling them to converse, reason, make decisions, and even learn
and improve in these capacities over time. Agents can also work with
other agents to coordinate and perform more complex workflows,
as well as facilitate transactions and business processes.
The rise of AI agents
87%
are using AI agents in their work

The growing adoption of AI agents has important implications for
game studios and developers, as the technology is poised to
redefine several areas:
44%
38% 38%
37%
37%
36%
35%
34%
34%
33%
How developers are using AI agents
Asset or content optimization
that adapts to in-game needs
In-game coaching or automated tutorialW
Dynamic balancing and tuning of gameplay
Procedural world or environment
generation that reacts to player actions
Automated content moderation
or community management
Adaptive difficulty or personalized
player challenges
Automated testing and bug reporting
Advanced NPC behavior
Internal studio functions
Real-time voice or audio enhancements
AI agents and the future of game development
01
02
03
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Strategic resource allocation
Studios will likely need to re-evaluate how they allocate resources. They will
increasingly need talent capable of designing, implementing, and overseeing
AI-driven systems. This requires a greater emphasis on roles like AI architects,
prompt engineers, and data scientists—and a shift away from manual asset
creation or scripting in certain areas. Enhanced player experiences
For players, this translates directly to more realistic and responsive gameplay.
Currently, games are adapting seamlessly to individual skill levels, deploying
NPCs with truly intelligent behaviors, and personalizing tutorials. This level of
dynamic interaction elevates immersion and replayability, setting a new standard
for the next generation of games. Accelerated development cycles
AI agents can automate repetitive or complex tasks, such as content generation,
testing, and balancing. This can significantly reduce development time and costs,
allowing studios to iterate faster, experiment more freely, and bring new game
concepts to market more efficiently.
New creative horizons
Beyond efficiency, AI agents open up entirely new creative possibilities.
Developers can design emergent gameplay scenarios, unpredictable
narratives, and environments that evolve in response to player actions, pushing
the boundaries of what’s possible in interactive entertainment.

When it comes to their daily work, developers report that gen AI is having a
significant and generally positive impact on workflows. In particular, 40% see
AI-driven game engines and tools for balancing gameplay as the most promising
development, signaling a significant shift toward AI’s integration in the
fundamental aspects of game creation.
As a result, teams are adding new roles, such as AI engineers and AI content designers. Existing roles are also changing, with 56% of
respondents noting that some have evolved to include AI-related tasks. As a result, large majorities see AI changing how their team
collaborates on key tasks, such as:
AI is upending norms in developers’ daily lives and work processes.
Transforming workflows
Problem-solvingSpeed of
prototyping
and iterationQuality control
and testing
Brainstorming
and ideationIntegration
and user
feedback Collaboration
across different
departments
84% 83% 83% 81%81% 80%
say existing roles have evolved
to include AI-related tasks
56%
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This shift is helping address a number of
major industry challenges, including
improving analytics for player retention and
engagement (41%), speeding up projects and
delivery (40%), and updating or maintaining
older games (38%), while freeing up time to
focus on innovation (38%). How developers see AI changing the games industry
Emergence of new genres or gameplay types 27%
Greater player expectations for personalization 27%
Increased competition and innovation from new entrants 28%
More reliance on data-driven decision-making 28%
Faster iteration and development cycles 28%
Democratization of game development (e.g., tools accessible to smaller studios) 29%
Better graphics and immersive environments 30%
say new AI-focused
roles have emergedsay AI is helping
improve analytics
for player retention
and engagement
41%
report enhanced
experimentation
37%
62%

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AI is also becoming an ally in creative workflows.
36% of respondents are using AI for dynamic level design, animation and rigging, and dialogue writing. But it’s not just
practical tasks where AI is beginning to shine: 37% of developers report that they have enhanced experimentation with
new gameplay or narrative concepts, while 36% note increased flexibility in creative exploration. And 36% report AI has
encouraged more iterative approaches to creative work.
This signals a shift in how developers are using AI, not just for coding and internal workflows, but now
into the fundamental aspects of game creation.
Redefining creativity
29%
are using AI for
narrative design
36%
are using AI for dialog
writing support
36%
say AI increases flexibility
in creative exploration

As consumers are enjoying new, AI-driven features
like adaptive difficulty, more realistic animations,
and dynamic worlds, their expectations for games
have risen. Players now expect games to not only
respond to their skill level, but also their playing
style and individual preferences. This is already
evident in the market, with 37% of developers
noting that players are seeking out games that feel
more “alive” and dynamic. Additionally, 35% say
players now expect to get into the game faster,
thanks to more intuitive, AI-driven tutorials.
Player expectations are changing thanks to innovative uses of AI.
Enhancing player
experiences
expect games that feel
more “alive” and dynamic
37%
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expect to get into games
faster with AI-driven tutorials

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In fact, the survey found that 89% of
respondents are observing changes in
consumer expectations due to AI integration,
especially around smarter and more
responsive games. They reported the following
top opportunities for the future: dynamic
world changes in response to gameplay (23%),
NPCs that learn and adapt (23%), personalized
marketing or in-game recommendations
(22%), and automated moderation of
player-generated content (22%).
These heightened expectations are a direct
result of how creatively developers are
already leveraging AI. For instance, 33% say AI
is helping them create AI-enhanced live
events or seasonal content updates, 29% are
using AI-driven accessibility features for
diverse player needs. An equal number are
using AI to create personalized content for
individual players.
23%
AI for realistic character animations and gestures
Dynamic world changes in response to gameplay
NPCs that learn and adapt
Personalized marketing or in-game recommendations
Automated moderation of player-generated content 23%
23%
22%
22%
Where AI enhances player experiences
see the use of AI changing
what players expect
89%

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Top opportunities for
AI adoption
While AI’s transformative potential in game development is
widely acknowledged, the survey highlights several key
challenges developers face in successfully integrating it into
their workflows.
Roughly one in four developers find it challenging to
precisely measure the return on investment (ROI) and overall
success of their AI implementations. A significant barrier is
the cost associated with integrating AI tools, including the
setup and ongoing maintenance.
94%
expect AI to reduce overall
development costs in the
long term (3+ years)
40%
say it is creating
new business
models or strategies

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Practical limitations play a role, as well, with a quarter of developers lacking sufficient AI training data. In addition, developers recognize the
need for upskilling and AI training to keep pace with the continuous evolution of the technology.
Despite these challenges, the long-term outlook for AI’s business impact remains overwhelmingly positive. A striking 94% of developers
expect AI to reduce overall development costs in the long term (3+ years). Furthermore, 40% of developers believe AI is already creating
new business models or strategies, signaling its role as a powerful catalyst for innovation and new revenue streams.
23%
Limited AI
training data
24%
Cost of AI
integration
25%
Difficulty measuring
success of AI
implementations
23%
Data privacy
or IP concerns
23%
Need for upskilling
or training staff
in AI tools
Top challenges in using AI

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The ownership dilemma
The survey also reveals a number of potential risks and legal challenges.
For example, 35% of respondents have concerns about player data
privacy. Some also show uncertainty around who exactly owns
AI-generated content, with 32% saying that licensing is unclear for
AI-generated content, while 32% said ownership is unclear.
Similar to many industries, AI has raised concerns over concepts
like originality and attribution. Games are no exception, with 63%
of respondents expressing concerns regarding data ownership
with AI applications and games.
63%
expressed concern about
data ownership and IP
AI raises IP issues, while providing guarded
optimism for healthier game environments.
have concerns about player data privacy
have concerns about unclear licensing
have concerns over ownership of AI-generated content
35%
32%
32%

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When it comes to content moderation and community management, some
also see AI as helping lower toxicity levels and providing a more supportive
environment. In fact, 37% are currently using AI for this in their workflows.
And 22% of them see it as the single area where AI might most enhance the
player experience.
On the other hand, developers are also seeing
AI helping support responsible games. Roughly
one in three see possibilities for AI helping with
the following tasks:
Making monetization systems more transparent
Enhancing accessibility for players with diverse needs
Personalizing content pacing to avoid fatigue or frustration
Providing real-time player support or mental health resources
Improving moderation of user-generated content 32%
32%
31%
31%
30%
Opportunities in creating responsible games
Can AI foster more responsible games?
Making monetization
systems more transparent
Enhancing accessibility for
players with diverse needs
Providing real-time player support
and mental health resources
Improving the moderation
of user generated content
01
02
04
03

When it comes to the implementation of AI, developers selected a number of best practices for moving forward:
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Next steps
38% recommend establishing
clear criteria for evaluating the
success of AI implementations.
Make sure you have agreed-upon success metrics so that you can
understand what’s working, what
isn’t, and quickly iterate to ensure that things go according to plan.
39% stressed the importance of
providing training or upskilling for staff on AI tools.
39% emphasized making sure
that AI use reflected the creative vision and goals.
40% recommend using
small-scale pilots or testing
before full implementation. Such an approach allows teams to
identify potential challenges and refine processes before
committing significant resources.
01 02 03 04
Measure effectively
Start small Align with creative vision Invest in people

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Conclusion
Overall, the research found widespread adoption of gen AI in the
games industry—and a surprising level of optimism for it. AI is
already making a big difference in developer workflows, including
productivity and creative tasks.
Developers also see promising possibilities with AI agents and other
emerging AI tools to accelerate game development and enhance
player experiences.
And while developers raise important concerns about IP issues and
the ownership of AI-generated content, the overall feedback on
how AI can impact the holistic games industry is trending positive —
with some even expressing that a more inclusive and democratic
future lies ahead.
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Methodology
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The research was conducted online in the United States, South Korea, Finland, Norway,
and Sweden by The Harris Poll on behalf of Google Cloud among 615 adults age 18+
working in game development. The survey was conducted June 20, 2025 – July 9, 2025.
Raw data were not weighted and are therefore only representative of the individuals
who completed the survey. The sampling precision of Harris online polls is measured by
using a Bayesian credible interval. For this study, the sample data is accurate to within ±
3.9 percentage points using a 95% confidence level. This credible interval will be wider
among subsets of the surveyed population of interest.
All sample surveys and polls, whether or not they use probability sampling, are subject
to other multiple sources of error which are most often not possible to quantify or
estimate, including, but not limited to coverage error, error associated with
nonresponse, error associated with question wording and response options.