How ready is AI for real business decisions?
Enterprise AI readiness – Databricks has delivered a reality check that the enterprise AI world has been waiting for. With the launch of Databricks OfficeQA, a new open-source benchmark, Databricks shifts the conversation from theoretical AI brilliance to real-world business reliability, where mistakes aren’t merely academic but are also expensive. This marks a critical moment for enterprise AI readiness across industries.
Unlike popular benchmarks such as ARC-AGI-2 or Humanity’s Last Exam, which emphasize abstract reasoning, OfficeQA focuses on AI benchmarks for enterprises by testing what truly matters in real organizations: whether AI agents can reason accurately over large, messy, and evolving business documents.
This level of intelligence is essential for enterprise AI decision making in finance, compliance, operations, and analytics domains where “almost right” can mean regulatory risk, financial loss, or strategic missteps and directly impact AI reliability for business.
What Makes OfficeQA Different?
OfficeQA is built around grounded reasoning, which enables AI to answer questions using real, heterogeneous document collections rather than simplified prompts. To make this challenge authentic, Databricks used nearly 89,000 pages of U.S. Treasury Bulletins, spanning over 80 years of revisions, tables, and historical financial data.
The benchmark includes 246 rigorously verified questions, divided into “easy” and “hard” categories based on frontier model performance.
The Results: A Wake-Up Call for Enterprise AI
Even the most advanced AI agents struggled.
- GPT-5.1 Agent achieved 43.1% accuracy overall
- Claude Opus 4.5 Agent reached 37.4% accuracy
- On the OfficeQA-Hard subset, scores dropped below 25%
- Without access to documents, accuracy fell to ~2%
These numbers are striking and intentional. OfficeQA exposes a critical truth: strong performance on academic benchmarks does not translate to enterprise readiness.
Where AI Still Falls Short
Error analysis reveals persistent gaps that enterprises can no longer ignore:
- Difficulty parsing complex financial tables
- Poor handling of revised and versioned data
- Weak visual reasoning, especially with charts and graphs
- Misinterpretation of historical trends and key figures
In business environments, these aren’t edge cases, they’re everyday realities. And when AI gets them wrong, the consequences are real.
OfficeQA: Not a Scoreboard, but a Diagnostic Tool
Databricks positions OfficeQA not as a leaderboard but as a diagnostic instrument, a way to identify where AI systems break down and how they can be improved. Its focus on realistic documents and automatically verifiable answers makes it uniquely valuable for enterprises building production-grade AI.
To accelerate adoption and innovation, Databricks is launching the Grounded Reasoning Cup 2026, inviting researchers and industry leaders to expand OfficeQA beyond Treasury data and apply it to broader enterprise scenarios.
Why This Matters for Enterprises
OfficeQA reinforces a powerful message:
Enterprise AI success depends on data grounding, governance, and architecture, not just model size.
For organizations serious about deploying AI at scale, this benchmark highlights the need for platforms that combine:
- High-quality data pipelines
- Robust document intelligence
- Governance-ready AI architectures
- Continuous evaluation in real business contexts
OfficeQA is open-source, freely available, and already reshaping how the industry measures AI success. With this launch, Databricks isn’t just testing AI, it’s redefining what “AI-ready for business” truly means.
Media Contact: Chithra Sivaramakrishnan | +1(646) 362-3877 | chithra.sivaramakrishnan@prolifics.com
