The general feeling from our respondents is that right now the landscape is changing too quickly, and what was exciting yesterday is not interesting today. There’s a lot of activity going on around security, supply chain, inventory management, customer experience and document summarization/generation (whether these activities are home-grown or not). These are some of the ideas our respondents came back with: • Education – Personalized Learning • Accuracy and Contract Review – 3 Renewals, insurance, other legal • Multi-LLM Frameworks documentation • Order Processing • Agent Platforms – Connecting LLMs • Pharmaceuticals – Drug discovery with actions • Security Operations – Particularly • Agriculture – Coreweave GPUs/CPUs automating end-to-end security tasks • Automation – Development, DevOps, based on gen AI recommendations Security, etc. (e.g. ML for anomaly detection that feeds into gen AI for remediation to • Content Creation – Marketing, sales create an autonomous response) (proposals), legal (boilerplates), security (SOPs). Can be text or visual • Software Development – Including the synthesis of operation signals. AI can • Copilots – Eng, analysts, and more recommend root causes to improve (dataset analysis) • their efficiency • Customer Experience – Chatbot to • Summarization – Lay summaries of chatbot direct interaction, clinical research, manufacturing conversation, and resolution of issues documentation, and more • Customer Predictive Modeling – • Supply Chain – Computer vision, last Forecasting, inventory management mile resilience • Diagnosis – Augmented diagnostic • Test Automation capabilities in healthcare • Videoconferencing , VP Data Science and Analytics, Northwestern Mutual “My favorite perspective on AI comes from historian and storyteller Yuval Noah Harari: ‘AI has hacked the operating system of human civilization.’ Language, rights, religion, and so much more are all cultural artifacts we created by telling stories and writing laws. So what happens when AI becomes better at this than humans?”