"LLMs demonstrate difficulty detecting psychomotor retardation or agitation from text alone – a limitation that parallels challenges human clinicians face when restricted to written communication without visual or auditory cues."
Dr. Adi Ganesan, Stony Brook University
September 2025 | What's new this month
AI in practice: LLMs, psychology research, and mental health
We’re excited to have Adi Ganesan, a PhD researcher at Stony Brook University, Penn University, and Vanderbilt, on the show. We’ll talk about how large language models LLMs) are being tested and used in psychology, citing examples from mental health research. Fun fact: Adi was Sid's research partner during his Ph.D. program.
AI Governance & Assurance | Ethics & Responsibility
Global AI Regulations and Their Impact on Industry Leaders There is significant regulatory uncertainty in global AI oversight, primarily because of the fragmented legal landscape across countries, which hinders effective governance of transnational AI systems. The absence of robust AI governance and risk management frameworks exposes organizations to operational, ethical, and financial risks. Compliance failure is costly: fines under the EU AI Act can reach up to € 40 million or 7% of global revenue for severe violations. On a recent episode of the ‘AI in Business’ podcast, Emerj Editorial Director Matthew DeMello sat down with Michael Berger, Head of Insure AI at Munich Re, to discuss how companies should actively manage growing AI risks by setting governance frameworks, defining risk tolerance, and reducing aggregation risk through model diversification and task-specific fine-tuning.
Globally, artificial intelligence is advancing at a remarkable pace, with market forecasts projecting a compound annual growth rate exceeding 30% through 2030. Alongside this acceleration, questions of regulation and ethics are rising to the forefront across jurisdictions. As AI systems become more sophisticated and deeply embedded in daily life and critical infrastructure, their impacts on business and society correspondingly increase. Without robust governance, these powerful technologies can introduce significant risks to individuals, communities, and even national systems.
The insurance industry’s use of artificial intelligence faces increased scrutiny from insurance regulators. Red teaming can be leveraged to address some of the risks associated with an insurer’s use of AI. The U.S. Department of Commerce’s National Institute of Standards and Technology defines a “red team” as:
"A group of people authorized and organized to emulate a potential adversary’s attack or exploitation capabilities against an enterprise’s security posture. The red team’s objective is to improve enterprise cybersecurity by demonstrating the impacts of successful attacks and by demonstrating what works for the defenders (i.e., the blue team) in an operational environment. Also known as cyber red team." Red teaming is a concept in cybersecurity. The insurance industry’s enterprise risk, legal and compliance areas are becoming more familiar with the use of red teaming in connection with AI corporate governance efforts.
Impact & Society
Acknowledging the transformative impact of AI on insurance operations Can generative AI (GenAI) deliver real value in general insurance today? That was the question under discussion during a ‘power lunch’ discussion at the 2025 Insurtech Insights Europe conference where Guidewire’s Laura Drabik spoke to Tom Wilde, CEO of Indico Data and Terry Buechner, global insurance core systems lead at AWS about the practical application of AI in insurance.
Contextualising where AI is adding value and where it’s in danger of becoming overhyped, Wilde noted that last year about 25 million people globally identified as software engineers. When GenAI arrived, it essentially enabled anybody able to type at a computer to become a programmer. That’s the scale of the disruption, he said, and it’s what is so profound about the advancement of AI.
How Underwriting and Claims Are Reshaped by AI in Insurance — and How They Stay the Same The use of artificial intelligence in insurance continues to grow. Here’s how the industry is using AI to optimize and augment its processes while keeping people at the center of the equation. AI is a powerful tool with the potential to streamline and speed up many functions, but it can also misinterpret information or mislead users if left unchecked. Today, AI is reshaping the way insurers do business –mostly for the better – but it comes with its own set of risks that the industry is carefully considering as it adopts and implements new tools.
