Generative AI uses large language and generative models to create text, images, or other outputs, helping clinicians and staff summarize notes, draft messages, automate administrative work, and accelerate research. It’s most effective when grounded in trusted sources, evaluated for safety, […]
In banking, ethical generative AI use means preventing unfair treatment, protecting customer and supervisory data, avoiding IP misuse, reducing misinformation/deepfake harms, and ensuring clear accountability with audit trails. Approve GenAI only when it is governed, tested, monitored, and traceable to […]
Teams using generative AI should set rules that reduce harm and liability across fairness (bias), privacy/security, intellectual property, accuracy/misinformation, security/misuse, and accountability/transparency. Start by restricting sensitive inputs, verifying high-impact outputs, disclosing material AI involvement, and assigning a human owner for […]
Generative AI escalates cybersecurity risks by scaling social engineering and introducing application-layer vulnerabilities like prompt injection and data leakage in LLM apps. Mitigate these threats by defining data boundaries, enforcing least privilege for tools, and hardening output handling to prevent […]
Generative AI in customer support has moved from experimentation to production in customer support faster than almost any recent technology shift. Companies are no longer asking if AI should handle support interactions, but how it should be implemented—and at what […]
Generative AI can be safe for businesses when controls for privacy, security, and compliance are applied
AI in customer service has transformed the way businesses connect with their customers, offering new levels of efficiency, responsiveness, and satisfaction. With the right AI tools in customer support, companies can streamline workflows, provide 24/7 assistance, and create personalized experiences […]
Imagine doubling your affiliate marketing revenue without doubling your workload. Sounds too good to be true? Thanks to the rapid advancements in AI technology, this is not just a possibility but a reality for many marketers in 2025. AI tools […]
In our last blog, we talked about how you can customize machine learning models and even create your own. Now, we’re shifting focus to the challenges that come with building a custom generative AI model from scratch. While it might […]
There is a lot of magical thinking which states that Large Language Models are on the verge of achieving Artificial General Intelligence or AGI. And while increasing the training data, and compute has shown impressive performance gains in these systems, […]
