Article
Seizing the real AI opportunity
Ignore the hype to make real progress
From the business pages to Black Mirror, artificial intelligence (AI) is a source of both great hope and rising fear. Some believe AI heralds a bright new era for humanity; others see machine intelligence creating a dystopia. Many feel the future they envision—for good or bad—is almost here.
The reality is more humble. To be sure, AI has made incredible advances in recent years, and there is some substance behind the hype: it can be applied to help increase productivity, improve customer interactions, and quickly solve problems too complex for human brains.
But AI is still in its infancy. We’re nowhere near creating an artificial general intelligence that’s equal or superior to human intelligence. It’s not yet clear when, or if, we’ll ever reach a point where it’s better than humans at every kind of thinking.
This big gap between hype and reality can create issues in organizations. Those on the leadership team can fall into the trap of believing AI is further along than it really is, while technology teams can become frustrated by leadership’s unrealistic expectations. Navigating these two diverse perspectives can hinder an organization’s progress, because when reality doesn’t live up to the hype, there’s a risk that disillusioned decision-makers may pull back on further AI investment.
That’s exactly the wrong thing to do because even in its current form, AI has the potential to transform the way organizations make decisions, unlock value, and achieve sustained, profitable growth. Tools and data are more accessible than ever, and they’re ready to be deployed to improve efficiencies and gain useful business insights. Proprietary and open-source software is also available, while cloud-based hardware means researchers and developers can readily access the computing power they need. Prominent vendors have made open-source data libraries available to help “train” machine learning systems.
It’s becoming easier than ever for businesses of all sizes to make significant progress on their AI vision. The first step is to ignore the hype and focus on what can be achieved today.