Responsible AI (RAI) is not just desirable, but essential
This report shines a spotlight on the imperative for responsible AI best practices, while revealing huge gaps in enterprises’ ability to deliver safe and reliable agentic AI.
RAI at the center
No organization can ignore RAI. Good practice leads to a 39% drop in incident costs, 18% lower damage severity, and cheaper AI deployments. But just 2% of companies are getting it right according to our RAISE BAR Index.
AI risks are real and can be severe
Negative consequences of poor RAI are universal. Nearly all the companies we surveyed - 95% - have experienced AI-related incidents in the past two years.
These range from regulatory noncompliance to privacy violations and security breaches. These incidents can cause significant legal, reputational, and financial damage.
40% of decision makers said this damage was “severe” or “extremely severe”, and 10% of this cohort said these damages were an existential threat to their business.
RAI drives growth
On the upside, best-practice methods can reduce the damage.
Moreover, RAI is considered by 78% of senior leaders to be a growth lever, and most welcome more, not less, regulation.
Bigger RAI teams achieve higher throughput of AI initiatives, and therefore more successful deployments overall – though with diminishing returns.
Safe agents are the future of enterprise AI
Most decision makers agree that agentic systems will increase risk and compliance challenges. As agents are embedded deep into business process, making them safe, reliable, and transparent is not optional.
Enterprises should take four steps to get ahead in the agentic AI era:
- Learn from the leaders
- Institute product-led, platform-driven, operating models
- Embed RAI guardrails into platforms
- Create an RAI office to support governance
