AI adoption is creating more jobs than it eliminates in many organizations, but the real transformation isn't about employment numbers,it's about how work itself is being redesigned. A new international study from Snowflake and Omdia surveyed 2,050 business and technology leaders across 10 countries and found that 77% of organizations report AI-driven job creation, while 46% report job reductions linked to AI. Among companies experiencing both hiring and reductions, 69% say the net effect on employment has been positive.

What Does AI Actually Do to Jobs?

The headline numbers might suggest AI is a net job creator, but the deeper finding is more revealing: AI doesn't automate entire jobs. It automates tasks within jobs. This distinction matters enormously because it means organizations aren't simply shrinking; they're restructuring how work gets done.

The study identified the strongest job growth in technical and infrastructure-related roles. Organizations reported the largest increases in IT operations (56%), cybersecurity (46%), and software development (38%). These roles are expanding as companies deploy AI systems, manage data infrastructure, and strengthen security around AI-driven environments.

But here's where it gets interesting: the same functions experiencing the most growth are also seeing the most disruption. IT operations, customer service and support, and data analytics all reported significant reductions alongside growth. This dual effect suggests that AI is transforming tasks within functions rather than eliminating entire professions.

Why Is Data the Real Bottleneck?

One of the most striking findings in the report has nothing to do with jobs at all. It's about data readiness. Organizations report major challenges in preparing data for AI:

• Data Silos: 65% of organizations struggle with data silos that prevent AI systems from accessing the information they need
• Data Quality: 62% report significant challenges with data quality, which directly impacts AI accuracy and reliability
• AI-Ready Data: 62% struggle with preparing data for AI use, and the report estimates that only around 7% of unstructured data is currently AI-ready

For many companies, the real barrier to AI success isn't the technology itself but data infrastructure and governance. This suggests that organizations focusing solely on deploying AI tools without addressing data foundations may be missing the actual bottleneck.

How to Prepare Your Organization for AI-Driven Work Transformation

• Redesign Roles and Teams: Rather than asking which jobs AI will eliminate, ask which tasks within roles can be automated and how teams should be restructured to handle the remaining work alongside AI systems
• Invest in Data Infrastructure: Before deploying new AI tools, audit your data silos, assess data quality, and establish governance frameworks to make data AI-ready
• Measure AI Impact Systematically: Organizations that actively measure the impact of AI report an average return of $1.49 for every dollar invested in AI initiatives, but 96% still face major challenges scaling AI across the enterprise
• Rethink Workflow and Skill Requirements: When tasks change, organizations must redesign workflows and talent management strategies to ensure employees have the skills needed for transformed roles

What Does the Future of Work Look Like?

The research suggests that companies are still early in their AI maturity. While the findings show positive net employment effects in the short term, the large-scale organizational impact of AI may still lie ahead. At the same time, a separate analysis from Everest Group indicates that AI is moving beyond assisting employees with discrete tasks like drafting or summarizing. AI is beginning to act as the environment in which work is initiated, coordinated, executed, and monitored.

This shift carries significant implications. The critical question is no longer which AI tools to deploy, but which work should remain human-led, which should become AI-assisted, and which can be safely executed by AI agents. This represents a fundamental change in how organizations think about work design and digital workplace strategy.

The debate about AI and jobs may be asking the wrong question entirely. Instead of asking whether AI will destroy jobs, the better question is: How will organizations redesign work when AI can perform a growing share of tasks? That is where the real transformation of the labor market will happen.