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Can AI really support high-level corporate strategy and deep research — or does it only generate surface-level answers? In this episode of Working with Agents, we asked five different AI systems the exact same strategic question about China Speed — a topic that requires economic insight, operational understanding, and credible sourcing. We tested: • Copilot (GPT-5) • DeepSeek R1 with web search • Manus (autonomous agent) • Kimi K2 Researcher • AnyGen The goal was simple: 👉 Can AI compile large amounts of information and turn it into convincing, board-level strategy? What we discovered is revealing: • Some AIs produce correct but superficial answers • Others gather sources but fail to synthesize • Only one delivers credible strategy, case studies, and executive-ready insights This video shows why tool choice matters more than model power, and how professionals should evaluate AI for research, consulting, and strategic decision-making. If you use AI for leadership, consulting, or corporate analysis, this episode will fundamentally change how you choose your tools. ⸻ ⏱️ Timestamps 00:00 – Why we tested AI for strategic research 00:28 – The question we asked all 5 AIs 00:52 – Copilot (GPT-5): correct but superficial 01:33 – Why this won’t convince a board 02:16 – DeepSeek R1 with web search 03:32 – References help — but depth is missing 04:00 – Manus agent: transparency and sourcing 05:13 – How agents gather and compile articles 06:49 – When AI becomes convincing for strategy 08:02 – Kimi K2 Researcher mode explained 09:12 – Research paper vs corporate strategy 10:36 – AnyGen: the strongest strategic output 11:59 – Case studies, structure, and credibility 12:47 – Final comparison across all 5 AIs 13:43 – Key takeaway: how to use AI for real strategy AI strategic research, AI agents comparison, corporate AI strategy, deep research AI, AI for executives, AI consulting tools, AI board presentation, China speed strategy, enterprise AI analysis, generative AI research, reasoning models vs agents, AI decision making