Tech CEOs Predict AI's Production Phase in 2026: Power, Security, Enterprise Readiness Key

• Global tech leaders at Davos 2026 foresee AI moving from pilot projects to large-scale deployment by 2026, driven by advancements in agentic AI and early physical AI.
• Key challenges for AI adoption include infrastructure (power, compute, network bandwidth), trust (security, safety), and data gaps, according to Cisco's Jeetu Patel.
• Emerald AI's Varun Sivaram highlights power shortages as a major risk, with 2026 being critical for countries like the US and India to secure energy for data centers.
• o9 Solutions' Chakri Gottemukkala suggests neuro-symbolic AI, combining LLMs with enterprise knowledge, will enhance decision-making in complex business environments.
• Check Point Software's Jonathan Zanger emphasizes increased investment in AI security, as many current AI solutions lack built-in protection against cyber threats.

Why It Matters: AI's widespread adoption by 2026 hinges on overcoming critical hurdles in power, security, and enterprise integration.