The key to driving massive ROI from AI after some of the initial high-value use cases is largely about deploying it massively while also controlling costs. But how?
Learn about the three steps to reducing costs associated with AI in this five-minute read.
The potential for ROI from AI is huge, but maximizing that ROI requires wide deployment across the enterprise. The problem?
An organization's first AI use cases are likely low-hanging fruit that have more value than the 10th, 50th, or 100th use cases, so the marginal value of use cases is decreasing overall. At the same time, maintenance costs and the cost of executing each use case is increasing.
The real cost of implementing AI is often an ugly truth, but the good news is that there are three key, concrete ways to reduce the costs associated with AI (particularly large-scale AI deployment).
This 5-minute read covers all three, with actionable next steps for making them a reality at your organization.