Gartner Says 60%+ of AI Data Will Be Synthetic - Here's What That Means

Few statistics have shaped the conversation around artificial intelligence as much as this one: Gartner has predicted that 60% of the data used to develop AI and analytics projects would be synthetically generated by 2024, up from just 1% in 2021. That's not incremental change. That's a near-total reversal of how enterprises source the data that powers their models, and it happened in the span of a few years.

So what does this shift toward synthetic data AI actually mean for your business? Let's unpack it.

The problem: AI is outgrowing the data that feeds it

Synthetic data is artificially generated information that mimics the statistical patterns, relationships, and structure of real-world data, without containing any actual records. Its explosive rise isn't hype; it's a response to three problems that every data-driven enterprise is now facing at once.

AI is starving for data. Modern machine learning models need vast, diverse, high-quality datasets to perform well. Real data is often incomplete, imbalanced, or simply unavailable for the specific scenarios teams need to train against, rare diseases, edge-case fraud patterns, new product categories.

Privacy regulation has made real data a liability. GDPR, HIPAA, and CCPA make using actual customer data in development and testing environments genuinely risky. One misstep can mean a breach, a regulatory fine, or both.

Real data is slow and expensive. Requesting access to a production dataset, cleaning it, and anonymizing it can take weeks, and it still leaves sensitive information exposed. That delay kills project velocity and drives up cost.

The result is a bottleneck: teams that can't get safe, realistic data on demand simply can't build and test AI fast enough to compete. This is precisely why Gartner sees synthetic data overtaking real data, it solves all three problems at once. But there's a catch: synthetic data generation only works if it faithfully reflects real-world complexity. Poorly built datasets introduce bias, miss edge cases, and break the relationships that make data meaningful. Generating it well, at enterprise scale, is the real challenge, and it's why modern synthetic data generation tools have become essential infrastructure.

The solution: how Onix's Kingfisher closes the gap

This is exactly the problem Onix's Kingfisher was built to solve. As an enterprise-grade synthetic data generator, Kingfisher produces statistically accurate, bias-free, fully compliant datasets, mapping each capability directly to the problems above.

It ends the data shortage. Kingfisher generates data by understanding your business logic, not by copying records. You can create synthetic data straight from your DDL/DML and application code, or replicate the patterns of your production data to build realistic datasets, and scale from a few rows to petabytes without additional cost. As an intelligent AI data generator, it gives your models the training data they need when real data is limited or unavailable.

It removes the compliance risk. Because Kingfisher creates data that mimics the statistical properties of the real thing without exposing a single real record, it's safe to use under GDPR, HIPAA, and CCPA. Teams can test, analyze, and train freely, dramatically reducing breach risk while keeping the data authentic.

It eliminates the delay. Kingfisher is deployed inside your own environment, giving you full security and control, with a zero-code platform and REST API integration for on-demand generation. As a powerful test data generator tool, it delivers realistic, schema-compliant data whenever you need it,  no waiting on approvals, no touching sensitive production systems. That means faster QA, regression, and migration testing, and quicker AI/ML model development.

The outcome is what the Gartner shift promises but few tools deliver: abundant, privacy-safe, high-fidelity data that turns a bottleneck into a competitive advantage. As a trusted synthetic data company, Onix already supports top banks and telecom providers, including a global bank that achieved 85% savings with Kingfisher.

Get ready for a synthetic-first future

Gartner's longer-term outlook suggests synthetic data will eventually overshadow real data in AI development altogether. The organizations that build the capability now will be the ones ready to scale AI responsibly when synthetic data becomes the default.

The question is no longer whether synthetic data belongs in your strategy, it's how quickly you can put it to work.

Ready to solve your data bottleneck? Book a Kingfisher demo and see how Onix can power your AI with safe, compliant, on-demand data.