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Snowflake, in collaboration with Omdia by Informa TechTarget, has released "The ROI of Gen AI and Agents," a global research report surveying 2,050 business and technology leaders across 10 countries. The findings reveal that AI's impact on the workforce is more nuanced than headlines suggest, with 77% of organizations experiencing increased hiring compared to 46% experiencing role reductions, and among those experiencing both, 69% say the net impact has been positive.
Snowflake research finds 77% of organizations report AI-driven job creation, compared to 46% reporting job losses, with a net positive workforce impact.
Organizations report earning approximately $1.49 for every dollar invested in AI, with 92% of early adopters reporting positive ROI.
Technical roles see the strongest job gains: IT operations (56%), cybersecurity (46%), and software development (38%).
Data readiness remains the primary bottleneck, with 96% facing significant challenges and only 7% reporting majority of unstructured data is AI-ready.
Nearly half (48%) of all code is now AI-generated, with 82% reporting improvements in code testing and bug detection.
Organizations plan to allocate 22% of technology budgets to AI in the coming year as adoption accelerates.
As organizations scale AI across the enterprise, its impact on the workforce is becoming clearer. Among respondents, 42% say AI has created jobs across their organizations, 11% say it has eliminated roles, and 35% report a mix of both—netting to 77% reporting job creation versus 46% reporting job loss. The data also shows that maturity matters: 75% of organizations with multiple AI use cases report a net positive workforce impact, compared to 56% of those still in early stages of adoption. In other words, the more embedded AI becomes, the more likely organizations are to see overall employment gains.
"AI's impact won't be uniform — some roles will dramatically amplify their influence and productivity, while others risk being left behind. The difference comes down to how effectively it's used: breaking down problems with first-principles thinking and guiding AI agents like high-performing teams," said Anahita Tafvizi, Chief Data Analytics Officer, Snowflake. "The strongest ROI isn't coming from experimentation alone, it's coming from embedding AI into core operations while strengthening data readiness and governance policies. The future of work will be shaped by companies that pair AI ambition with trusted infrastructure, and the right skills to turn it into lasting impact."
The functions benefiting from workforce gains are primarily technical roles, with the strongest net gains concentrated in IT operations (56% report job gains), cybersecurity (46% report gains), and software development (38% report gains). Notably, the teams furthest along in AI deployment are also seeing the most workforce change—both gains and reductions—suggesting that as productivity increases, organizations are restructuring teams, automating certain tasks while adding new capabilities in other areas.
The teams most impacted by AI-driven job loss include IT operations (40% report losses), customer service and support (37% report losses), and data analytics (37% report losses). This indicates that AI is reshaping these functions rather than uniformly expanding or shrinking them.
Workforce outcomes such as employee productivity and operational efficiency also strengthen as AI adoption matures. 75% percent of organizations deploying AI across many use cases report a net positive impact on their jobs, compared to 56% of those using AI in more limited, early-stage deployments.
As AI adoption accelerates, organizations are finding that their primary constraint is not the technology itself, but the state of their data. While AI is delivering strong returns—organizations report earning roughly $1.49 gained for every dollar invested—96% say they continue to face significant challenges in scaling their initiatives.
When asked about specific challenges preventing AI from scaling, nearly eight in 10 respondents report experiencing technical or data-related hurdles. In particular, 65% say it is challenging to break down AI data siloes, 62% say it is challenging to measure and monitor AI data quality, and 62% say it is challenging to prep data to be AI-ready. Only 7% say more than half of their unstructured data is actually AI-ready. Among the 10 countries surveyed, India leads with 14%, followed by Australia and New Zealand at 12%, Canada at 10%, and the United States at 8%, close to the global average.
Governance is emerging as an equally pressing concern. 57% of employees, including 66% of C-level leaders, report using nonapproved AI tools, while 60% say their organizations need greater investment in data infrastructure and monitoring software. Additionally, 22% of middle managers and individual contributors cite data governance as "very challenging" to enforce. The findings indicate that while AI's value is increasingly clear, data readiness and governance will determine how effectively organizations can scale it.
While some widely cited studies claim that AI pilots fail to deliver value, this research tells a different story. As AI moves from pilot programs into production, organizations are seeing measurable value. Among early AI adopters, 92% report positive ROI, and businesses plan to allocate 22% of their technology budgets to AI in the coming year. This signals that investment is accelerating, not slowing, and that organizations are leaning into AI as a proven driver of measurable business impact.
According to respondents, AI is already embedded in core enterprise functions: 62% of IT operations teams report active AI use, 59% of data analytics teams, 53% of cybersecurity teams, and 50% of software development teams. By contrast, functions such as procurement, sales, and marketing are the slowest to adopt AI, with around 30% of each reporting active use. At the industry level, advertising and media leads with 42% of organizations reporting AI in production today, followed by healthcare and life sciences at 34%, and both manufacturing and technology at 32%.
Additionally, nearly half of all code, approximately 48%, is reported to be AI-generated, highlighting how deeply the technology is embedded in day-to-day workflows. Organizations are also seeing measurable benefits from AI coding tools and apps, with 82% reporting improvements in code testing, bug detection, and resolution, and 80% citing gains in overall code quality.
"The data shows that AI is delivering tangible returns, but scaling it successfully requires a strong data foundation and governance framework," said Adam DeMattia, Senior Director of Research, Omdia by Informa TechTarget. "Organizations that can unify their data, improve quality, and operationalize AI responsibly will be best positioned to sustain ROI and workforce gains. With its focus on secure, governed data and AI integration at scale, Snowflake is well positioned to help enterprises move from experimentation to enterprise-wide impact."
Methodology
The ROI of Gen AI and Agents is based on responses from 2,050 respondents from 10 countries (Australia/New Zealand, Canada, France, Germany, India, Japan, Singapore, United Kingdom, United States) that are influential in their organization's future AI purchases. The survey was conducted in collaboration with Omdia by Informa TechTarget between August 13, 2025, and September 17, 2025. All figures are rounded to the nearest whole number, with values below .5 rounded down and .5 and above rounded up.
About Snowflake
Snowflake is the platform for the AI era, making it easy for enterprises to innovate faster and get more value from data. More than 13,300 customers around the globe, including hundreds of the world's largest companies, use Snowflake's AI Data Cloud to build, use and share data, applications and AI. With Snowflake, data and AI are transformative for everyone.
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