- The article “The Gen AI Playbook for Organizations” in Harvard Business Review (November–December 2025 issue) by Bharat N. Anand and Andy Wu asserts: businesses cannot wait for “perfect AI”—they need an immediate GenAI adoption strategy, focusing on strategic differentiation rather than speed of deployment.
- The authors propose a 2×2 strategic framework to identify where and how to use GenAI, based on two criteria: the cost of errors and the type of knowledge required (tacit vs. explicit).
- “No regrets zone” (low error cost, explicit knowledge): AI performs entirely – for example, customer responses, refund processing, CV screening.
- “Creative catalyst” (low error cost, tacit knowledge): AI supports ideation – writing slogans, design, presentations.
- “Quality control” (high error cost, explicit knowledge): AI produces – humans control – for example, drafting contracts, writing code, financial analysis.
- “Human-first” (high error cost, tacit knowledge): human leads – AI assists – for example, strategy, executive recruitment, medical diagnosis.
- The authors warn: asking “How smart is the AI” is the wrong direction; the right question is “Where should AI be used to create a competitive advantage.”
- The true value of GenAI lies in its ability to generate relative efficiency, not absolute accuracy. Even with small errors, AI helps save time, scale operations, and reduce operating costs.
- Businesses should universalize AI access for all employees, breaking down the “bottleneck” from IT or slow approval processes—otherwise, they will be overtaken by more agile competitors.
- Three sources of sustainable AI advantage:
- Quick and selective deployment in suitable tasks.
- Proprietary data – consolidating, exploiting, and “AI-ifying” internal data assets.
- Culture and people – using AI as a value-augmenting tool, not a replacement.
- Anand and Wu recommend that organizations review their organizational structure and redesign processes to suit an “AI-native organization.” Personnel will shift from “operating tools” to “collaborating with AI.”
- Common mistakes: waiting for AI to reach 100% accuracy, failing to measure the value of time saved, or not translating productivity gains into actual profits in the P&L (Profit and Loss statement).
📌 The article “The Gen AI Playbook for Organizations” in Harvard Business Review (November–December 2025 issue) asserts: businesses cannot wait for “perfect AI”—they need an immediate generative AI adoption strategy, focusing on strategic differentiation rather than speed of deployment. Organizations should review their organizational structure and redesign processes to suit an “AI-native organization.” Personnel will shift from “operating tools” to “collaborating with AI.” Long-term advantage will come from unique AI usage, proprietary data, and a culture of human-machine collaboration.
