To move from the PoC to the deployment stage, organizations must identify their strategy, as we covered earlier, as well as the use cases with high impact. Prioritizing these use cases based on their impact, cost, data readiness, and resistance to adoption is essential. Becoming familiar with the limitations and capabilities will also be important for decision-makers. and you must leave room for the possibility of failure. Once this is done, various PoCs and pilots can be launched, based on the problems an organization genuinely wants to solve.
Additionally, transparency with your internal stakeholders is key. Communicate lebanon whatsapp number data how these changes and the cultural shift will impact them, augment their capabilities, ensure productivity, and make them more effective. A change management program right from the start is necessary.
The Way Ahead
Going forward, the main differentiator will be how enterprises deploy foundational models responsibly. Given the cost to train and maintain foundational models, enterprises will have to decide how they want to deploy them for use cases. At the PoC level, a lot can be overlooked, but at the enterprise level, solving business problems will require a degree of certainty and decision-making around cost, time effort, data privacy, intellectual property, etc. If a foundational model lacks business context, it can result in outputs that make it challenging to identify accuracy. Accuracy is a critical factor – biases and hallucinations are real concerns because most foundational models are trained on extensive datasets. If there’s an inherent bias in that data, it will manifest in the outcomes.