Why AI Adoption Alone Isn't 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. CIO of Avnet Max Chan proposed the A³ framework (Architect, Augment, Amplify), which helps move from technology adoption to changing decisions and processes within a company. Using predictive equipment maintenance as an example, the stages of designing change, embedding AI into decision-making, and scaling the pilot are explored.
Even if an AI model is successfully connected to data, integrations work, and users are trained, the business outcome may be absent — recommendations remain in a separate interface, managers act as before, and the pilot does not scale. Avnet CIO Max Chan proposed the A³ framework in 2026, which includes the stages Architect, Augment, and Amplify. In the Architect stage, you should start not with technology but with business change: define which decision should become different, who owns it, and how to measure the result. In the Augment stage (the 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 (the ARC model: Adapt, Rewire, Cultivate) turns a pilot into a regular practice: changes the operating model, aligns authorities and incentives (for example, a common reliability KPI for production and technical services), and develops employee competencies. Without these steps, AI remains an experiment, even though the business is already beginning to depend on it.
Source: Habr — хаб ИИ —
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