Alyssa Farrell, Senior Director of Platform and Horizontal Solutions at SAS, positions synthetic data generation as more than a technical workaround.“ Synthetic data is not a workaround, but a strategic weapon against data scarcity, privacy limitations and compliance bottlenecks,” Alyssa says.
She predicts competition will intensify around synthetic data capabilities in 2026, with organisations competing on their ability to generate realistic data at scale.“ In 2026, expect a data arms race, where companies compete not only on multimodal real-world data but on how convincingly they can create it.”
The emphasis on synthetic data reflects the dual pressures organisations face: regulatory requirements that limit access to real customer data and AI systems that require substantial training data to function effectively. Synthetic data offers a potential resolution by allowing organisations to train and test AI systems without exposing sensitive information.
Stu Bradley, Senior Vice President of Fraud and Security Intelligence at SAS, frames the overall transition as a market correction.“ 2026 will mark the start of AI’ s market reckoning – when hype collides with governance and only accountable innovation endures,” Stu says.“ The push for consistent ROI and transparent oversight will shutter vanity projects and reward the disciplined, refocusing investment on the fundamentals: data orchestration, sound modeling and explainable governance.”
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