Dive into the 2025 State of AI Report: The Builder's Playbook podcast, your essential guide for building and operationalizing AI products to gain a competitive advantage. This deep dive unpacks the "how-to" of conceiving, delivering, and scaling AI-powered offerings end-to-end.

Join us as we explore core dimensions of the builder's playbook, including Product Roadmap & Architecture, Go-to-Market Strategy, People & Talent, Cost Management & ROI, and Internal Productivity & Operations. We draw on proprietary survey results and insights from AI leaders across the ICONIQ community to offer a blueprint for anyone tasked with turning generative intelligence from a promising concept into a dependable, revenue-driving asset.

Key topics we'll cover:

• AI Product Development: Understand why AI-native companies are moving faster through the product lifecycle, with approximately 47% of their primary AI products already reaching critical scale and proven market fit. Discover that agentic workflows and application layers are the most common types of AI products being built across both AI-native and AI-enabled companies, with notably around 80% of AI-native companies currently building agentic workflows.
• Model Usage & Infrastructure: Learn how companies prioritize model accuracy above all other factors when choosing foundational models for customer-facing use cases. We'll discuss the increasing trend of companies adopting a multi-model approach to AI products and the dominance of fully cloud-based solutions and reliance on external AI API providers for training and inference infrastructure.
• Challenges & Optimization: We'll address the top challenges noted by companies when deploying models, such as hallucinations, explainability & trust, and proving ROI. Find out how organizations are optimizing AI infrastructure costs by exploring open-source models and focusing on inference efficiency.
• Talent & Costs: Explore insights into the increasing presence of dedicated AI leadership as companies grow, the finding that AI/ML engineers take the longest time to hire on average, and how companies are allocating approximately 10-20% of their R&D budget to AI development. We'll highlight that API usage fees are cited as the most challenging infrastructure cost to control, and inference costs and data storage & processing costs surge post-launch, especially for high-growth companies.
• Internal Productivity: Understand how annual internal AI productivity budgets are set to nearly double in 2025 across all revenue tiers, with cost being the most important consideration when choosing models for internal AI use cases. Discover the significant impact of coding assistance, which is by far the leading use case in terms of tangible impact on productivity, and how most companies are tracking productivity improvements and cost savings from internal AI use.

This podcast is ideal for architects, engineers, and product leaders aiming to harness AI expertise, foster cross-functional collaboration, and sustain long-term innovation. Tune in for expert insights into AI strategy, development, scaling, and cost management derived from a comprehensive April 2025 survey of 300 executives at software companies building AI products.