Snowflake, in collaboration with Omdia by Informa TechTarget, has released a global research report surveying 2,050 business and technology leaders across 10 different countries, all of whom influence their organization’s current and future AI purchases. The findings reveal that AI’s impact on the workforce is more nuanced than headlines suggest, with 77 per cent of organizations experiencing increased hiring compared to 46 per cent experiencing role reductions.

Of the organizations that have seen both hiring and cuts, 69 per cent say the overall effect of AI on the workforce has been positive, signalling that as adoption accelerates, AI is driving overall job growth rather than consolidation.

“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 at Snowflake. “The strongest [return on investment] 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.”

Key findings from Canadian respondents include:

In the last 12 months, 42 per cent of Canadian organizations report that AI-powered automation has both created and eliminated jobs. Of the remainder, 31 per cent say AI-powered automation has created jobs, while smaller shares report either job elimination (14 per cent) or no effect on jobs (13 per cent).
Canadian enterprises report earning $1.45 for every dollar invested, an increase over last year’s reported $1.43 for every dollar invested.
Over half (53 per cent) of Canadian organizations say they have quantified a positive ROI on their gen AI initiatives.
Nearly one-third (31 per cent) of Canadian respondents say they are already leveraging agentic AI in production today and 32 per cent say they are interested but early in the adoption process.
Canada is outpacing the world on customer-facing gen AI, with 45 per cent of Canadian organizations putting it in customers’ hands, compared to 36 per cent of organizations globally.

Global outlook: AI drives job loss and creation, with a net positive impact on technical roles

As organizations scale AI across the enterprise, its impact on the workforce is becoming clearer. While AI is driving both job growth and role reductions, the overall trend is positive, particularly on technical teams.

Among respondents, 42 per cent say AI has created jobs across their organizations, 11 per cent say it has eliminated roles, and 35 per cent report a mix of both — netting to 77 per cent reporting job creation versus 46 per cent reporting job loss.

The data also shows that maturity matters: 75 per cent of organizations with multiple AI use cases report a net positive workforce impact, compared to 56 per cent of those still in the early stages of adoption. In other words, the more embedded AI becomes, the more likely organizations are to see overall employment gains.

Workforce outcomes such as employee productivity and operational efficiency also strengthen as AI adoption matures. Seventy-five per cent of organizations deploying AI across many use cases report a net positive impact on their jobs, compared to 56 per cent of those using AI in more limited, early-stage deployments.

The functions benefiting from these workforce outcomes are also those seeing the greatest job growth, primarily within technical roles. The strongest net gains are concentrated in:

IT operations: 56 per cent report job gains
Cybersecurity: 46 per cent report gains
Software development: 38 per cent report gains

Notably, the teams furthest along in AI deployment are also seeing the most workforce change: both gains and reductions. This suggests that as productivity increases, organizations aren’t simply cutting roles; they’re restructuring teams, automating certain tasks, and adding new capabilities in other areas. In other words, AI is reshaping these functions rather than uniformly expanding or shrinking them. This is seen through IT operations, which saw both the highest amount of job gains and losses. The teams most impacted by AI-driven job loss include:

IT operations: 40 per cent report job losses
Customer service and support: 37 per cent report job losses
Data analytics: 37 per cent report job losses

AI’s bottleneck is data readiness and governance

As AI adoption accelerates, organizations are quickly finding that their primary constraint to deploying AI at scale 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 per cent say they continue to face significant challenges in scaling their initiatives.

When asked about the specific challenges preventing AI from scaling, nearly eight in 10 respondents report experiencing technical or data-related challenges, with data emerging as the primary barrier to scaling AI initiatives. In particular:

65 per cent say it is challenging to break down AI data siloes
62 per cent say it is challenging to measure and monitor AI data quality
62 per cent say it is challenging to prep data to be AI-ready

Only seven per cent say more than half of their unstructured data is actually AI-ready. Among the 10 countries surveyed, India leads, with 14 per cent reporting that the majority of their unstructured data is AI-ready, followed by Australia and New Zealand at 12 per cent, and Canada at 10 per cent. The United States comes in at eight per cent, close to the global average of seven per cent.

Governance is emerging as an equally pressing concern. Fifty-seven per cent of employees, including 66 per cent of C-level leaders, report using non-approved AI tools, while 60 per cent say their organizations need greater investment in data infrastructure and monitoring software. Additionally, 22 per cent of middle managers and individual contributors cite data governance as “very challenging” to enforce, and 19 per cent of C-suite leaders share the same view. Together, the findings indicate that while AI’s value is increasingly clear, data readiness and governance will determine how effectively organizations can scale it.

AI delivers real returns and rewires operations

While some widely cited studies claim that AI pilots fail to deliver value, Snowflake’s research tells a different story. As AI moves from pilot programs into production, organizations are seeing measurable value. Among early AI adopters, 92 per cent report positive return on investment (ROI), and businesses plan to allocate 22 per cent 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, rather than treating it as a speculative experiment.

According to the respondents, AI is already embedded in core enterprise functions:

62 per cent of IT operations teams report active AI use
59 per cent of data analytics teams report active AI use
53 per cent of cybersecurity teams report active AI use
50 per cent of software development teams report active AI use

By contrast, functions such as procurement, sales, and marketing are the slowest to adopt AI, with around 30 per cent of each reporting active use. At the industry level, advertising and media leads, with 42 per cent of organizations reporting AI in production today, followed by healthcare and life sciences at 34 per cent, and both manufacturing and technology at 32 per cent.

Additionally, nearly half of all code, approximately 48 per cent, 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 per cent reporting improvements in code testing, bug detection, and resolution, and 80 per cent citing gains in overall code quality. As AI-generated code becomes embedded in everyday workflows, enterprises will increasingly look towards coding agents that operate on trusted enterprise data.

For more information, see The ROI of Gen AI and Agents research report.

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 A...

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