Snowflake’s global research of 2,050 business leaders tells a different story than the headlines. 77% of organisations report workforce gains from AI adoption, not losses.
Snowflake and Omdia surveyed 2,050 business leaders across 10 countries. The headline finding: 77% of organisations are experiencing increased hiring because of AI, compared to 46% seeing role reductions. Organisations earn roughly $1.49 for every $1 invested in AI. 48% of all code is now AI-generated. The data suggests AI is creating net job growth, but the jobs being created require different skills than the ones being eliminated. Here is what that means for your career.
If you’ve been following AI news this month, you’ve probably seen the scary headlines: “AI will replace 40% of jobs,” “Your role is at risk,” and the usual doomsday fare. Then, on March 10, Snowflake quietly dropped a research report that tells a very different story. [1]
The report, titled “The ROI of Gen AI and Agents,” was produced in collaboration with Omdia by Informa TechTarget. It surveyed 2,050 business and technology leaders across 10 countries. That’s not a Twitter poll or a startup’s marketing survey. It’s a substantial global dataset. [1]
The core finding: 77% of organisations are experiencing increased hiring because of AI, compared to 46% experiencing role reductions. And among companies that have seen both hiring and cuts, 69% say the overall effect on the workforce has been positive. [1]
Let that sink in. The majority of organisations that have adopted AI are hiring more people, not fewer. The narrative that AI is a job destroyer doesn’t match what’s actually happening inside companies.
Beyond the headline 77% figure, the Snowflake report contains several data points that paint a clearer picture of what’s actually happening.
ROI is real and measurable. Organisations report earning roughly $1.49 for every $1 invested in AI. That’s not a massive return, but it’s positive and consistent enough to justify continued investment. It also means the “AI is all hype” argument is getting harder to sustain. [1]
More AI adoption = more positive workforce impact. Here’s a finding that surprised me: 75% of organisations with multiple AI use cases report a net positive workforce impact, compared to only 56% of those still in early stages. In other words, the companies that go deeper with AI are more likely to see job growth, not less. [1]
48% of code is now AI-generated. Nearly half of all code being written uses AI assistance. That doesn’t mean developers are being replaced. It means they’re producing more output per hour. The same dynamic is playing out across other knowledge work: AI amplifies output rather than replacing people. [1]
Experience creates a significant divide. The report highlights that experienced AI users significantly outperform newcomers. This isn’t just about having access to the tools. It’s about knowing how to use them well. And that gap, between the people who have invested time in learning AI and those who haven’t, is becoming a real career differentiator. [2]
This is where the conversation gets practical. The research shows net job growth, but it’s not the same jobs being created as the ones being cut. Understanding that shift is essential for anyone thinking about their career trajectory.
Jobs being reduced: routine data entry, basic report generation, first-level customer support, manual data categorisation, and repetitive administrative tasks. If your job involves doing the same structured task hundreds of times per day, AI is genuinely competitive with you.
Jobs being created: AI implementation specialists, prompt engineers, data quality managers, AI trainers and evaluators, ethics and compliance roles for AI systems, and hybrid roles that combine domain expertise with AI skills. [3]
The common thread in the jobs being created: they require human judgment, contextual understanding, and the ability to work alongside AI tools. You don’t need to become a programmer. You need to become the person who knows how to use AI effectively within your specific field.
Microsoft’s own research supports this pattern. Their Work Trend Index found that AI proficiency is becoming a requirement across roles, not just in tech. [4] Hiring managers are increasingly looking for candidates who can demonstrate practical AI fluency, regardless of the job title.
If the data shows net job creation, why do the headlines keep saying the opposite? Three reasons.
Fear gets clicks. “AI will destroy your job” generates ten times more engagement than “AI is gradually changing how work gets done.” Media incentives favour catastrophic framing. The actual research is more nuanced, but nuance doesn’t trend on social media.
Individual displacement is visible; aggregate creation is invisible. When a company lays off 500 customer support agents, it makes the news. When the same company hires 600 people for AI-adjacent roles over the following year, those hires happen quietly across multiple departments. The cuts are sudden and dramatic. The creation is gradual and distributed.
The timeline mismatch. Job elimination happens faster than job creation. A company can deploy an AI chatbot in weeks. But creating new roles, training people for them, and building new workflows takes months. There’s a real gap between when the old jobs disappear and when the new ones fully materialise. That gap creates genuine anxiety, even if the long-term trend is positive.
None of this means you should be complacent. The transition is real, and the people most at risk are those who assume their current skills will be enough forever. But panicking isn’t the right response either.
The Snowflake data makes one thing clear: AI fluency is no longer optional for knowledge workers. Here’s what to actually do about it.
1. Pick one AI tool and get genuinely good at it. Don’t try to learn ChatGPT, Claude, Gemini, and Copilot simultaneously. Choose the one that’s most relevant to your daily work and spend 30 minutes a day using it for real tasks. Competence comes from consistent use, not from watching tutorials. Our AI workflow guide walks you through selecting and integrating the right tool.
2. Document your AI-augmented results. Start tracking how AI changes your output. “I used Claude to cut my report writing time from 4 hours to 90 minutes” is a concrete, quantifiable statement you can put on a CV or bring to a performance review. Employers are looking for this.
3. Learn to prompt well, not just to prompt. The gap between experienced and inexperienced AI users in the Snowflake data isn’t about access. It’s about skill. Invest time in learning how to write effective prompts: give context, specify format, iterate on results. Our anti-hallucination toolkit covers the verification side of this.
4. Build a “human + AI” portfolio. Whatever your field, start creating examples of work where you’ve combined human expertise with AI capability. A consultant who can show a client “I used AI to analyse 10,000 data points, then applied my industry experience to identify these three actionable insights” is demonstrating exactly the hybrid skill set that’s in demand.
5. Stay current, but stay calm. Follow AI developments monthly, not hourly. The people who consume AI news obsessively often end up more anxious than informed. A monthly review of what’s changed, what tools are worth trying, and what’s just hype is plenty. Our weekly AI roundup can help you stay informed without the noise.
If you’re not in tech, you might be wondering whether any of this applies to you. It does. Possibly more than you think.
The Snowflake data shows that AI’s workforce impact is strongest in roles that involve routine knowledge work: creating reports, processing information, managing communications, analysing data. That describes most office jobs in HR, finance, marketing, operations, and consulting. [1]
But here’s the part that should actually encourage you: the jobs being created don’t require a computer science degree. They require someone who understands their domain deeply and can use AI tools to do their domain work better and faster. An HR director who can use AI to screen 500 applications and surface the best 20 candidates is more valuable than before, not less.
The professionals most at risk aren’t the ones with “wrong” skills. They’re the ones who refuse to adapt. And in our experience training 2,000+ non-technical professionals at Future Factors, the learning curve is far less steep than most people expect. Most people go from “I’m intimidated by AI” to “I can’t imagine working without it” within a few weeks of consistent practice.
No single study tells the full story, and it’s worth being honest about what the Snowflake research doesn’t cover.
It’s a snapshot, not a trend line. The survey captures what’s happening right now. It doesn’t predict what will happen in 2028 or 2030 when AI capabilities are significantly more advanced. The net positive job impact could shift as AI gets better at more complex tasks.
Geographic and industry variation isn’t broken out in detail. The 77% figure is a global average across 10 countries. Some industries and regions are likely seeing more displacement than creation. If you work in a heavily automatable sector, the average may not reflect your specific situation.
It’s self-reported data from leaders, not employees. The 2,050 respondents are business and technology leaders. The people being hired and the people being let go might have a different perspective on whether the overall impact is “positive.”
These caveats don’t invalidate the research. They contextualise it. The directional finding, that AI adoption is generating net job growth right now, is supported by multiple other sources including Microsoft’s Work Trend Index and McKinsey’s ongoing workforce analysis. [4] [5] But treating any single data point as the final word would be naive.
What we can say with confidence: the blanket “AI will take all our jobs” narrative is not supported by the current evidence. The reality is more complex, more hopeful, and more actionable than the headlines suggest.
Is AI actually creating more jobs than it eliminates?
According to Snowflake’s March 2026 research surveying 2,050 global leaders, yes. 77% of organisations report increased hiring due to AI, compared to 46% seeing role reductions. Among those experiencing both, 69% say the net effect has been positive. Multiple other studies support this directional finding.
What kinds of jobs is AI creating?
New roles include AI implementation specialists, prompt engineers, data quality managers, AI trainers and evaluators, and hybrid roles that combine domain expertise with AI skills. Most new positions require human judgment and contextual understanding rather than purely technical coding skills.
Do I need to learn to code to stay relevant?
No. The data shows that the most in-demand skill is the ability to use AI tools effectively within your existing domain, not coding. An HR professional who can use AI to improve recruiting, or a marketer who can use AI for campaign analysis, is demonstrating exactly the hybrid capability employers want.
How much ROI are companies getting from AI investment?
The Snowflake research reports an average return of $1.49 for every $1 invested in AI. That is a positive but modest return. Organisations with multiple AI use cases report stronger returns than those still in early adoption stages.
What should I do right now to future-proof my career against AI?
Pick one AI tool relevant to your work and use it daily for real tasks. Document your results quantitatively. Learn effective prompting techniques. Build examples of human-plus-AI collaboration. Stay informed about developments monthly. The gap between experienced and inexperienced AI users is widening, so consistent practice matters more than theoretical knowledge.
This guide breaks down Snowflake’s March 2026 research on AI’s workforce impact. It’s written for professionals who want to understand what the data actually says (not what the headlines suggest) and how to position their careers accordingly. No technical background required.
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Sana is an AI educator and learning designer specialising in making complex ideas stick for non-technical professionals. She has trained 2,000+ learners across corporate teams, bootcamps, and keynote stages. Future Factors offers AI Bootcamps, Corporate Workshops, and Speaking & Consulting for businesses ready to adopt AI without the overwhelm.
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