Let’s be real: no single language rules the world anymore. It’s all about the right tool for the job.
You’ve seen the lists:
- “Top Programming Languages of 2024.”
- “Python vs. Rust: The Ultimate Showdown.”
- “Why Java Refuses to Die.”
But you rarely see SAS on these lists. And I get it. It’s not open-source. It’s got legacy associations. And sure, a lot of our users run workloads through SAS Studio or SAS Enterprise Guide instead of writing raw code.
But here’s what gets missed: SAS quietly powers the AI behind some of the world’s most mission-critical systems. It’s running behind the scenes at banks, monitoring for fraud, in pharmaceutical companies, running clinical trials and at public agencies shaping life-and-death policy.
It’s not flashy. It’s foundational.
Built for governance, auditability and scale, especially in industries where “oops” is not an acceptable error message.
And while others are still debating which language is ‘most loved,’ SAS just ranked No. 5 in employer demand, based on job postings, in IEEE Spectrum’s 2024 rankings, ahead of Rust, Go, and a bunch of buzzier tools.
So maybe the question isn’t why SAS isn’t trending, maybe it’s why we keep ignoring what works?
Related blog post: Is SAS a programming language?
Understanding SAS’ place in the AI ecosystem
Programming languages have settled into natural tiers based on how they’re used in the real world, not just what’s trendy.
- Tier 1 – Ubiquitous and essential: Python, Java, JavaScript/TypeScript, SQL
These are the default languages for general-purpose development, web apps and data science. - Tier 2 – Domain workhorses: C, C++, C#, Go, Rust, R, SAS
These are trusted tools for specialized, high-performance, or heavily regulated environments, where precision and scale matter more than popularity. - Tier 3 – Specialized or emerging: Swift, Kotlin, MATLAB, Ruby
Languages with more niche applications or rising potential, often confined to specific platforms or communities.
SAS lands firmly in Tier 2: the workhorse tier.
It’s a language designed for reliability, governance and performance, especially in sectors where trust and compliance matter as much as speed or scale. And despite its legacy reputation, SAS is actively evolving beyond modern development expectations.
Not your dad’s SAS
Enter SAS® Viya® Workbench, an environment designed for developers, not just data scientists with full support for Python, R and SAS, all in one place. Whether you’re building in Jupyter notebooks, deploying through Git, or scaling via Kubernetes, Workbench meets you where you are. It’s language-agnostic, cloud-ready, and fully integrated with SAS Viya.
And when it comes to innovation? You’re not boxed into one toolset. You get access to the full suite of SAS advancements: from agentic intelligence to synthetic data that’s privacy-safe and production-ready.
While SAS Viya Workbench modernizes how you build with SAS, what really sets it apart is how seamlessly it integrates with the tools and workflows you already use.
SAS works with what you know
SAS doesn’t exist in a vacuum. With Viya, you can:
- Seamlessly integrate with Python, R, Kubernetes and cloud-native architectures.
- Write code once, deploy anywhere across on-premises and multi-cloud environments.
- Support both code-first and low-code workflows without compromising on audit, lineage, or scale.
SAS may not show up in Reddit flame wars or Hacker News debates. But if you’re building AI that needs to scale, last and pass audit?
SAS isn’t just relevant. It’s essential. Let’s stop sleeping on that.
Want to see what SAS can really do?
Get a free 14-day trial of SAS Viya and test it for yourself
