Summary of Key Points
The article argues that platform-based organizations are an inevitable choice for corporate evolution (not just an optional innovation, but a trend from which businesses will be excluded if they do not adopt it). However, in the past, various barriers such as bosses' desire for power, departmental silos, insufficient talent capabilities, interpersonal distractions, and complex incentive systems made such transformations difficult to implement. Today, AI technology can overcome these four major obstacles—forcing organizational restructuring, enabling rapid capability replenishment, penetrating through human complexities, and facilitating precise incentive management—thus becoming a key force in driving organizational change. It even allows bosses to let go of their concerns about maintaining power.
Detailed Explanation
1. AI as a “Forced Restructurer”: Breaking Down Departmental Silos to Make Resources More Flexible for Customer Needs
In the past, companies wanted to divide into smaller teams to serve customers more effectively, but departmental boundaries hindered this process: employees were assigned to specific departments and focused on completing their departmental tasks, with projects being secondary. Department heads, concerned about maintaining their power, were reluctant to allocate resources to cross-departmental initiatives. Calls for collaboration and execution were ineffective due to the natural tendency to prioritize one's own domain.
With AI, this changes: large models serve as a foundation, turning resources and capabilities into “universal interfaces” (APIs) that front-line teams (such as those serving customers) can directly utilize without needing approval from department heads. Departmental KPIs are no longer about internal processes but about empowering the front line; otherwise, resources (like AI processing power) or funding may be cut, or even replaced by external providers. This eliminates the need for bosses to persuade departments to work together.
2. AI as a “Capacity Replenishment Station”: Quickly Addressing Talent Gaps Without the Need for Extensive Training
Platform-based organizations require employees with market knowledge and specialized skills, but traditional hierarchical structures often waste talent: even well-educated graduates become ineffective after a year or two and are prone to switching jobs. Bosses frequently struggle to form effective teams due to high training costs.
AI can instantly provide the necessary capabilities: for example, HRBP (Human Resource Business Partners) can use AI assistants to break down performance metrics, suggest benchmarks, and predict outcomes. Similar tools exist in R&D and finance departments. This reduces the need for a large workforce, allowing companies to retain only elite employees, which simplifies management (since elites are more self-disciplined and cooperative).
3. AI as a “Filter for Human Interferences”: Making Change Irreversible and Freeing Bosses from Old-Fashioned Resistance
When bosses tried to drive change, they often faced resistance from senior staff who argued that platform-based models were unsuitable or that the company culture had changed. AI makes such changes irreversible: departments are connected through intelligent systems, and any attempt to revert to traditional methods would face opposition from other departments (for instance, if the R&D department wanted to go back to manual processes, the front-line teams would oppose it because everyone relies on real-time data provided by AI). Bosses no longer need to mediate interpersonal conflicts.
4. AI as a “Precise Calculator”: Solving Incentive Issues and Eliminating Disputes over Compensation
Incentives are crucial for organizational change, but in the past, bosses would make vague promises without a clear plan (e.g., how employees should participate in profit-sharing or how much commission to allocate). HR was limited by fixed salary structures, unable to design effective incentive schemes. AI uses “tokens” (internal rewards) to automate this process: employees earn tokens by using AI services, and the distribution of these tokens is automatically enforced according to predefined rules in smart contracts. For example, if a business unit makes a profit, tokens are distributed to members as agreed, eliminating the need for arbitrary decisions or arguments.
Conclusion
AI is not just an added benefit but a solution that breaks the “deadlocks” preventing organizational change in the past—addressing both tangible issues like departmental silos and talent shortages, as well as softer barriers such as bosses’ power struggles and interpersonal complexities. If companies want to survive in the future, they may indeed need to rely on AI to drive their evolution.