AI is moving faster than regulation, faster than governance, and – perhaps most dangerously – faster than our ability to verify what’s real and what’s not. As the world races to unlock AI’s potential, a growing body of evidence shows that unchecked, even well-meaning AI tools can create serious consequences across sectors that can least afford them.
Obama’s Warning: Democracy and Deepfakes
In a recent public appearance, former U.S. President Barack Obama issued a clear warning about the erosion of truth in the age of generative AI. From manipulated video to automated disinformation, he notes that we are “entering an era where seeing is no longer believing.” The implications for trust, politics, and public safety are immense.
“The tools of AI are already being used to manipulate elections and public opinion.” – Barack Obama
LinkedIn Summary
The Legal Industry: Hallucinations Have Real Consequences
Stanford HAI’s recent research shows that when AI is tasked with answering legal queries, hallucinations occur in up to one in six answers – even among models trained specifically on legal content.
“Large language models can be confidently wrong, even when fine-tuned for legal use cases.”
Stanford: Legal Hallucinations
In high-stakes environments like law, finance, and healthcare, AI hallucinations aren’t just annoying – they’re dangerous. Imagine a chatbot generating false case law in a legal filing, or an AI model misclassifying patient data because of incomplete training.
McKinsey: Adoption Is Up – So Are the Risks
According to McKinsey’s State of AI report, over 70% of companies are now using generative AI in some form – but only a minority have frameworks in place for managing hallucinations, privacy risks, or reputational damage.
“Fewer than one-third of organisations are mitigating hallucination risk.”
McKinsey: The State of AI
That means businesses are moving quickly to integrate AI tools – while largely hoping nothing goes wrong.
JPMorgan: Taking Responsibility Into Their Own Hands
In a standout example of proactive governance, JPMorgan Chase recently issued an open letter to its global suppliers, making it clear that third-party use of AI must meet JPMorgan’s own internal trust and safety standards. They are embedding risk frameworks across their supply chain to ensure ethical AI is not just a talking point but a prerequisite for doing business.
“We expect our suppliers to ensure their AI systems do not generate hallucinations, misinformation, or other inappropriate content.”
JPMorgan: Open Letter to Suppliers
Where Do We Go From Here?
The future of AI is not just about what these systems can do – it’s about what they should do and how we hold them accountable.
Whether it’s a law firm relying on legal models, a retailer deploying AI-generated product descriptions, or a financial institution issuing investment advice, the risks of hallucinations, bias, and system manipulation are no longer hypothetical.
The leaders of tomorrow will be those who act today – by validating their data, demanding AI transparency from partners, and embedding ethical safeguards across their ecosystems.
Because in the AI era, trust isn’t just a feature – it’s infrastructure.
