Get hands-on: The full lineup of interactive roundtables at TechCrunch Disrupt 2026

Interactive roundtables at TechCrunch Disrupt 2026 offer direct access to practical advice on AI and enterprise software.

TechCrunch Disrupt 2026, scheduled for October 13-15 in San Francisco, will feature over 10,000 attendees including founders, investors, and tech leaders. The event will include a series of interactive roundtables covering topics such as fundraising, AI, enterprise software, physical AI, and scaling companies. These sessions will be led by industry experts, founders, and investors, offering practical perspectives and opportunities for connection. A key highlight is the focus on "physical AI," exploring its data challenges, applications in real-world scenarios like robotics, construction, and energy, and the practicalities of building reliable physical AI products. Discussions will also delve into the future of enterprise software in the age of AI, the path to IPO readiness with AI-enabled finance, the role of specialized data in AI development, and the modernization of legacy industries through AI. Other topics include effective introductions in an AI-driven world, the commerce AI playbook, quantum computing's commercial relevance, and the rapid adoption of generative AI in healthcare.

The focus on "physical AI" at TechCrunch Disrupt 2026 signals a significant market shift beyond purely digital applications. Discussions around data challenges, real-world reliability, and unique development approaches for robotics, construction, and energy indicate a maturing AI landscape seeking tangible outputs. This evolution suggests a growing demand for AI solutions that interact with and operate within the physical world, potentially opening new avenues for hardware and software integration startups.

The emphasis on AI's role in enterprise software, from modernizing legacy systems to orchestrating fragmented workflows, points to a future where AI is deeply embedded in business operations, not just an add-on. The conversations around agentic AI in the enterprise highlight the challenge of moving from pilot projects to scaled, trusted production environments, suggesting that practical implementation and ROI will be key differentiators. This will affect how businesses evaluate and adopt AI technologies, prioritizing integration and verifiable value.