Original): Manbir T
Originally published in the direction of artificial intelligence.
How to scale the decision making by Enterprise AI by measurable P&L influence and proof ready for management
If you had many “promising” AI version, but nothing moves with a needle, you are not alone. The Muthatory pilot is common in AI Enterprise because the teams are building models before defining the decision. This makes the success of Squisha-What Metrior, whose owner, who from the P & L lever? Add gaps in readiness for data, distributed prototypes and management fears, and you will receive months of movement without any result.
The article discusses challenges related to the implementation of effective AI decision -making in enterprises, emphasizing the importance of defining decisions before developing models to avoid traps such as “Pilot Purgate”. It presents a framework for adapting AI initiatives with business priorities, emphasizing key factors such as the impact of decisions, management and development of decision support systems. The steps include the identification of priority decisions, design of indicators and establishing architectural foundations in order to ensure the measurable impact of profit and losses.
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