Episode 11: Top 10 AI Questions for 2026: Liability, Deepfakes, & The Agentic Enterprise

Описание: The Hidden Risk of AI Autonomy 🤖⚖️ We are working in the Agentic Enterprise — where autonomous AI systems are not just tools, but active participants in decision-making, creativity, and leadership.
Today, Convergence hosts answer the burning question: “When AI Messes Up… Who Takes the Blame?”
The future of digital trust is being defined as we navigate AI AGENTS. As enterprise AI practitioners, Lauren Hawker Zafer and Faisal Hoque unpack the most pressing real-world questions shaping the AI transformation: from digital trust and corporate liability to the ethics of deepfakes, sustainability, and the future of human collaboration.

Can enterprises truly trust AI to act responsibly? Who is accountable when intelligent agents go wrong? And what does leadership look like when machines begin to shape judgment itself?

This episode explores how businesses, policymakers, and talent can navigate the rise of AI agents — balancing efficiency with empathy, and automation with accountability.

Listen to discover:
• The rise of the Agentic Enterprise and responsibility in the age of autonomous systems.
• How deepfakes redefine authenticity, trust, and influence.
• The hidden environmental cost of AI — and how enterprises can act responsibly.
• Why human insight and authenticity remain the ultimate competitive advantage.
• The evolving relationship between leaders, agents, and digital ethics.

YouTube Chapters: Episode 11 (2026) “The Top 10 AI Questions”

00:00 — Intro: Entering the Age of the Agent Enterprise
01:25 — 2026 and the Shift from Tool to Partner
02:45 — Top 10 AI Questions: What We’ll Explore
03:25 — Question 1: Who’s Liable When an AI Agent Makes a Mistake?
06:15 — Enterprise Responsibility and Context Blindness
08:45 — Why Full AI Autonomy Is Still a Risky Bet
10:15 — Shared Liability: Human, Vendor, and System Errors
11:45 — Legal and Ethical Ecosystems Around AI Agents
12:15 — Question 2: How Much Energy and Water Does AI Consume?
13:45 — Environmental Impact and Data Center Footprints
15:15 — Sustainable AI: Smaller Models, Sharper Focus
16:10 — Carbon Footprints, AI Energy Taxes, and Future Regulation
16:35 — Question 3: If AI Is a Commodity, Where’s the Competitive Edge?
17:45 — Authenticity, Storytelling, and Brand Differentiation
19:15 — Information vs. Wisdom: The Value of Human Expertise
21:05 — Question 4: Can I Pay for AI Visibility (GEO & SEO in 2026)?
22:45 — Sponsored Responses and Bias in Generative Models
24:15 — Fairness, Transparency, and “Pay to Play” AI
25:15 — Question 5: Solving the Apprentice Gap in the AI Workforce
26:30 — The Importance of Entry-Level Roles in an AI-Driven Economy
27:45 — Middle Management as the Organizational Glue
28:35 — Human-AI Apprenticeship: Collaboration Over Replacement
30:00 — Closing Thoughts: Agents, Leadership, and the Year Ahead


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Other Top 10 Questions People are Asking About AI going into 2026:

Is my work actually 'Meaningful' if AI does 80% of it?
What specific datasets was this model trained on?
How do I optimize my website for 'AI Search' (GEO) instead of SEO?
How do I build 'Change Fitness' in my organization?
How do we manage 'Know Your Agent' (KYA) protocols?

***Just as banks have "Know Your Customer" (KYC) rules, the finance world is asking how to assign "non-human identities" to agents. They want to know how an AI can have its own credit score, digital wallet, and cryptographically signed credentials to shop on behalf of a human.
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