What your business needs from AI is realistic predictions that identify hidden opportunities to maximize business impact. AI can help predict which of your sales opportunities are more likely to close, which marketing campaigns will generate more leads, or which online promotions will prevent abandoned shopping carts. Accuracy certainly seems like what we want – we want the predictions from our AI to be right. So, where does accuracy go wrong?
Costs, Benefits and Constraints
In business, the benefit of a correct prediction is never equal to the cost of a wrong prediction. But when AI is built purely for accuracy it assumes that all costs and benefits are equal.
What if my benefit of winning a deal is 100 times the cost of unnecessarily pursuing a deal? I might be willing to pursue and lose 99 deals for just a single win. An AI that only finds 1 win in 100 tries would be very inaccurate but would boost my net revenue. Is your AI being trained to recognize the right risk-reward trade-offs?
All businesses operate with real resource constraints. To succeed, we need to optimize for productivity and efficiency. But AI optimized for accuracy alone ignores real-world constraints.
AI that is always right, but only provides 5 good recommendations is of little value to a sales rep needing to close 100 deals per month. Likewise, a model that provides 10,000 recommendations is no good either, because there is no way to pursue them all. Is your AI optimized for your operational constraints?
Aible AI delivers the highest net business impact because it balances your relative costs and benefits – the rewards of getting it right, the costs of getting it wrong, and the hidden costs of missing a great opportunity. Aible optimizes for your resource capacity and goals to deliver an AI that works for your unique business reality.