Why AI Implementation Is Not Enough: The A³ Framework for Real Business Change
Avnet
A technically successful AI project may fail to deliver business results if management and organizational changes are not considered. Avnet CIO Max Chan proposed the A³ framework (Architect, Augment, Amplify), which helps move from technology implementation to changing decisions and processes within the company. Using predictive equipment maintenance as an example, the stages of designing change, embedding AI into decision-making, and scaling the pilot are analyzed.
Even if an AI model is successfully connected to data, integrations work, and users are trained, the business result may be missing — recommendations remain in a separate interface, leaders act as before, the pilot does not scale. CIO of Avnet Max Chan in 2026 proposed the A³ framework, which includes the Architect, Augment, and Amplify stages. At the Architect stage, you need to start not with technology, but with business change: identify which decision should become different, who owns it, and how to measure the result. At the Augment stage (AIR cycle: Align, Institutionalize, Refine), the role of AI in the solution is determined — for example, a recommendation mode with escalation, embedding into authorities, responsibilities, and regulations, as well as continuous improvement of the entire system. Amplify (ARC model: Adapt, Rewire, Cultivate) turns the pilot into regular practice: changes the operating model, aligns authorities and incentives (e.g., a common reliability KPI for production and technical service), and develops employee competencies. Without these steps, AI remains an experiment, even though the business is already starting to depend on it.
Source: Habr — хаб ИИ —
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