The compliance world is at an inflection point. AI promises to transform how we work — but between the hype and hesitation, it's hard to know where to actually start.
That's why EQS brought together compliance officers, legal professionals, and industry leaders for EQS Connect, a half-day event dedicated to cutting through the noise. The central question: How should compliance teams think about integrating AI when the work demands both precision and judgment?
Drawing on insights from the Chicago event on October 22 — including a keynote by Steph, a panel discussion featuring Elizabeth, and the newly released EQS AI Benchmark Report — we're sharing what we’re learning about AI's real capabilities, its limitations, and, most importantly, how to approach it thoughtfully. Whether you're experimenting with your first AI tools or building a comprehensive strategy, here's what compliance leaders need to know right now.
What Benchmarking Revealed
Working with Germany’s largest compliance association, EQS tested six leading AI models on 120 real-world compliance tasks, developed by EQS and informed by input from a diverse customer focus group. The benchmark included both synthetic and real customer materials—such as policies, speak-up reports, and HR datasets—provided with permission to reflect authentic compliance scenarios.
First, the headline: Google Gemini 2.5 Pro took the top spot at 86.7%, narrowly edging out OpenAI's GPT-5 at 86.5%. But what really stood out was the massive performance leap in just nine months — average model performance improved by roughly 16 percentage points between 2024 and 2025.
- Where AI excels: Structured tasks like matching investigators to competency profiles (91.8% average accuracy) and rule-based decision-making (90.8% average).
- Where AI struggles: Data analysis showed a 60-point spread between best and worst performers. Open-ended content generation — executive briefings, investigation reports, comprehensive policies — averaged just 63.3%, requiring significant human review.
- One revealing example: Analyzing HR records for whistleblower retaliation. The best model correctly flagged demotions and suspicious terminations, while the worst model flagged voluntary retirements as retaliation, generating 27 false positives that would have wasted investigative resources.
The Best Approach: Human-Led, Tech-Empowered
During the Chicago Connect panel, one theme kept emerging: speed without strategy is accelerated mediocrity.
Key advice: Maintain human oversight while adjusting automation levels. In her keynote, Steph used the analogy of an airplane pilot flying through fog: instruments and technology provide accuracy and efficiency, but it is human intuition and judgment that ultimately guide safe decision-making.
The same applies to the use of AI. As Elizabeth noted during the panel, true compliance agility isn't about how fast you can produce content. It's about how quickly you can influence behavior and strengthen culture.
That distinction matters enormously.
AI can help us detect patterns, but humans determine purpose. AI can monitor risk, but humans decide when to act. And when we combine those two — algorithmic insight with human integrity — we get the best of both worlds: speed and sense. The best solutions are designed around strategic AI integration that adapts based on task complexity and risk level.
Practical Steps Forward
Based on the benchmark findings and our experience, here's how to start:
- Start small with high-impact use cases. Identify one or two high-volume processes — translation workflows, preliminary case categorization, initial policy gap analyses — where AI delivers quick wins.
- Choose models strategically for your specific tasks. No single AI excels at everything. Test for your use cases rather than assuming one solution fits all.
- Be specific with prompts. Remember, AI is only as good as the prompts it receives. EQS’s benchmarking revealed that prompt design has a significant influence on outcomes, particularly in nuanced compliance work.
- Maintain human oversight at all times — especially where authenticity and judgment matter most. AI can make mistakes and should assist, not replace, human expertise in making ethical decisions and understanding cultural nuances.
Looking Ahead
The benchmark makes it clear that AI is ready for meaningful compliance work, provided it is accompanied by appropriate guardrails and human oversight. As we discussed on the panel, AI isn't replacing us — it's elevating what we can do.
But it’s also important to remember what AI can’t do.
As Steph said in her keynote, AI cannot truly feel, care, or comprehend the implications of choices. It can only simulate empathy and identify issues without understanding the human experience behind them. Compliance involves interpreting reality through discernment and wisdom, qualities that make human judgment indispensable in navigating moral complexities and organizational ethics.
The organizations that thrive will be those who find the balance early: between speed and quality, between automation and authenticity, between efficiency and effectiveness. Because the future of compliance isn't about choosing between technology and people. It's about empowering people with the right technology.
The full EQS AI Benchmark Report is available online.
