Trends, insights, and practical guidance on how trusted data and AI shape decision-making.
AI pilots can impress in isolation but unravel at enterprise scale. Discover how trusted data and Real-World Context give AI agents the clarity to reason accurately, act confidently, and turn ambitious AI investments into measurable business outcomes.
The risk that matters most in a supply chain often sits several layers away, in ownership structures and third parties that a standard onboarding check never reaches. With trusted business intelligence and connected context, organizations can see the wider network and act on it with confidence.
When a fraudster logs in with stolen credentials and an intercepted one-time code, every authentication check passes and the bank sees a genuine session. Spotting the takeover depends on context that keeps arriving after the login.
Identity thieves rarely work in rings. They work in strings, reusing one stolen identity across banks, insurers, benefits agencies, and carrier registries, while each institution sees only one plausible event and nobody sees the whole pattern.
Even with accurate data, decisions fail under scrutiny when leaders don't deploy explainable AI. Context is the critical layer that enables trusted, transparent AI-driven decisions.
Discover why incorporating Real-World Context is crucial for bank's AI systems to effectively use data to enhance decision-making.
Your data is almost certainly biased. What matters is how your AI acts on it. Learn how knowledge graphs help make AI decisions defensible.
Gartner® identifies the absence of a dedicated context layer as a major contributor to the value gap between AI investments and outcomes. Find out what they are and why real-world context is necessary to drive reliable and trusted decisions from AI agents.
Eighteen months of new rules across banking, insurance, government, and trade all point the same way. Liability for authorized fraud is shifting to institutions, and prevention is now the standard they will be measured against.
