AI in demand
The intelligence might be artificial, but the trend is real. AI has emerged as one of the most promising and in-demand capabilities for achieving any number of goals—from enabling new and different offerings to improving speed, quality and efficiency of existing products and services. Go just a bit below the surface, though, and it quickly becomes apparent that AI represents a diverse set of tools and technologies. Most of these are niche products; many are increasingly “plug and play.” Yet these technologies are emerging and changing faster than budget cycles.
Meanwhile, as data-driven enterprises focus on building different types of AI, they face some common challenges. In some cases, AI projects are taking too long. That can be due to a number of recurring obstacles, including not having a consistent platform, a lack of talent or of clean, accurate data for training the AI. Others are conducting proofs of concepts that demonstrate good value, but they remain hesitant to deploy them into production due to a lack of formal governance. And while some may be unable to identify any strong use cases, others are overwhelmed in trying to manage a set of highly dynamic use cases.
Chalk it up to business models that demand significant technological agility and fuel uncertainty about what the enterprise may need in the not-so-distant future.
Tackling this complexity may feel akin to building an airplane while in flight. How do you decide where to invest when you arenít sure what you need, what solutions will meet those needs and what resources youíll need to deliver them? The answer lies in developing an enterprise AI platform.