AI’s impact on the workforce is more nuanced than headlines suggest, with 77% of responding organizations experiencing increased hiring compared to 46% experiencing role reductions.
This is from a report released by Snowflake in collaboration with Omdia by Informa TechTarget. They surveyed 2,050 business and technology leaders that are influential in their organization’s future AI purchases across 10 different countries, including Singapore.
The others are Australia, New Zealand, Canada, France, Germany, India, Japan, the United Kingdom and the United States. Data were collected between August 13 and September 17 in 2025.
Of the organizations that have seen both hiring and cuts, 69% say the overall effect of AI on the workforce has been positive, signaling that as adoption accelerates, AI is driving overall job growth rather than consolidation.
Yet, turning this high-level ambition into measurable outcomes remains a hurdle. In Singapore, while 39% of organizations report using generative AI for many use cases—matching the global average—32% of local respondents cite identifying specific use cases as a top challenge, compared to just 19% globally.
“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 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,” said Tafvizi.
Singapore data
While Singapore matches the global average in the volume of AI activity—with 39% of local respondents reporting their organization has ‘many’ gen AI use cases today—the data reveals a significant gap when looking at actual penetration within departments. Across almost every major business function, Singaporean organizations are applying AI less widely than their global counterparts.
This narrower deployment across departments correlates with more muted downstream outcomes. Fewer Singaporean respondents report gains in operational efficiency (79% vs. 89% globally) and cost reduction (75% vs. 82% globally). Currently, only 33% of Singapore respondents report quantified ROI, compared to 49% globally.
This ongoing challenge of identifying viable use cases also appears to impact local investment. Budget allocations reflect a more cautious approach, with Singaporean respondents estimating generative AI will account for 15% of their tech budget over the next 12 months. This is the lowest globally, trailing the 23% global average and top markets like India (28%), the UK (23%), and the US (23%).
“With less than a third of local organizations reporting quantified ROI against half globally, it is clear that deploying AI and generating results are two different things,” said Jenny Koh, Snowflake country manager in Singapore.
“In my conversations with local leaders, the recurring challenge is not a lack of vision, but the need for a trusted data foundation to power it. The organizations that will lead are those building the right data foundations deliberately, bringing AI to their data to solve specific business missions rather than pursuing it broadly,” said Koh.
Impact on job market
As organizations scale AI across the enterprise, its impact on the workforce is becoming more clear. While AI is driving both job growth and role reductions, the overall trend is positive, particularly on technical teams.
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 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. 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.
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% report job gains); cybersecurity (46%) and software development (38%).
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 while 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 from AI-driven job loss include IT operations (40% report job losses); customer service and support (37%) and data analytics (37%).
