This article explores the growing importance of predictive AI and the emergence of hybrid systems combining it with generative AI (genAI). It highlights the potential of this partnership to unlock the full promise of genAI autonomy while ensuring its reliability and business value. The article also discusses the need for 'ML valuation' to assess the real-world impact of predictive AI.
while predictive AI makes fewer headlines these days, its vital role in achieving operational gains only continues to expand. Moreover, many thought leaders and1) The emergence of hybrid predictive AI / genAI systems Predictive AI and genAI need one another. Many capabilities can only materialize by combining the two in innovative ways.
For one, predictive AI has the potential to do what might otherwise be impossible: Realize genAI's bold, ambitious promise of autonomy—or at least a great deal of that often overzealous promise. By predicting which cases require a human in the loop, genAI systems could gain the trust needed for them to be unleashed. For example, consider a marketing campaign using genAI to personalize content for each customer. The content might be 95% reliable, meaning that 5% of customers would receive false or otherwise problematic content. This could make the project as a whole unviable, resulting in it simply never deploying. But if predictive AI flags for human review the, say, 15% of cases most likely to be problematic, this might decrease the rate of problematic content reaching customers to an acceptable 1%, while achieving 85% genAI autonomy. That is, for 85% of cases, genAI could do its thing with no human in the loop. In light of this, enterprises will soon begin turning to this approach as a necessary means to achieve a substantial piece of genAI's promise.2) The emergence of “ML valuation”—to ensure predictive AI captures business value: The estimated business value they would deliver in deployment must be calculated. But to date, they usually are not valuated. Imagine you're developing a rocket. If you don’t stress test it—in its intended usage (via simulations, wind tunnels, etc.)—then its launch will be a shot in the dark, if not entirely scrubbed by sensible decision-maker
Predictive AI Genai Hybrid AI Machine Learning Valuation Business Impact
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