How can you quickly and effectively deploy the power of artificial intelligence to benefit your business? According to MIT Review Technology, this goal can be out of reach for many companies as “deploying AI is slower and more expensive than it might seem.” For a technology that has the potential to create massive efficiencies, actually using it to get results can require large investments up front. The article says “Despite what you might hear about A.I. sweeping the world, people in a wide range of industries say the technology is tricky to deploy. It can be costly. And the initial payoff is often modest.”
AI holds the promise of transforming businesses by relieving its human counterparts of mind-numbing, repetitive tasks and, primarily, by providing predictions about what might happen next in a business. This kind of proactive management through predictive analytics is possible when effectively employing machine learning, an enabling technology of AI, to sift subtle but meaningful patterns out of otherwise noisy data.
However, this model is far from the science fiction robots you see in pop culture. In fact, for AI to be effective in business, humans must be a big part of the equation. People must be employed to verify and tune the recommendations made by AI, which “requires not just money but also patience, meticulousness, and other quintessentially human skills that too often are in short supply.” There is a nationwide shortage of individuals with the skills to deeply understand this technology and wield it effectively. So, despite the huge benefits that AI can bring to a business, its value is out of reach for most.
Not only is a skilled workforce hard to find, but the author outlines other obstacles to implementing this technology, such as integrating different record-keeping systems so data can be pooled and recommendations can be delivered to the front lines. An example outlined in the piece is from UC Health, a network of hospitals and medical clinics in Colorado, Wyoming, and Nebraska. The network’s attempts to roll out a conversational software, Livi (think Siri or Alexa for healthcare), in order for staff to spend more time helping patients - took more than a year and a half to deploy. This was due, in part, to the fact that the system had to be linked to other existing software. Even with this lengthy deployment time, Livi still only represents “the tip of the iceberg” of what AI could actually do in the healthcare setting. The article then dives into more detail about the challenges and opportunities of implementing AI.
One solution that can move this process along more quickly in today’s marketplace - with its shortage of skilled workers and need for cross functional experts for implementation - is to go with a consultancy model. This solves not only the need for experts to effectively deploy the technology, but also allows for a quicker turnaround because all the resources needed are coming together at once. For example, at Pacific Data Science, we have data scientists, project managers, and full-stack software engineers bringing an integrated team approach to client data strategy and engineering needs. Our deep experience can be applied to a variety of industries to allow them to tap into the power of AI.
After all: “A.I. will play a role in most of the industries we see today, some more predominantly. To completely ignore it is not an option.”
For the complete MIT Review Technology article visit: https://medium.com/mit-technology-review/this-is-why-a-i-has-yet-to-reshape-most-businesses-2f029d83b8d5