Scott Hebner introduces the New Next Frontiers of AI podcast which discusses the future of AI in business and provides top predictions for 2025. Tim Sanders, VP of Research Insights at G2, joins the discussion to provide insights on the predictions. Prediction 1: LLMs will run out of gas for enterprise ROI. LLMs have limitations in decision-making and adaptability. Correlation-based outcomes may lead to inaccuracies and hallucinations. Complementary specialized models will be needed for agentic AI. Prediction 2: AI reasoning will be democratized. Reasoning involves chain of thought, semantic reasoning, causal AI, and swarm intelligence. Vendors are creating user-friendly environments for businesses to apply reasoning techniques. Prediction 3: AI explainability will be crucial for innovation. Slowing deployments due to lack of trust in AI calls for explainability. Rote and effective explainability will be important for building trust and overcoming trust gaps in AI. Understanding the chain of thought in AI systems will enhance trust and decision-making. In the upcoming year, there will be advancements in explainability in AI. If explanations are not possible, there may be a slowdown in AI deployments, especially in agents and generative AI. Generative AI may follow a fate similar to the browser wars of the early internet age, where it becomes part of the infrastructure rather than the center of innovation. Andrew Ng emphasized the importance of the application layer over the foundation layer in technology. Software developers will increasingly need to become data scientists to stay relevant. The gap between supply and demand for AI talent will drive the need for talent augmentation. Trust, talent, and rapid advancements in explainability and decision intelligence will be crucial in the AI industry in 2025. The industry is moving quickly, so individuals should prioritize learning about AI to stay ahead.