Artificial intelligence is everywhere these days, but many of the most successful businesses aren’t reaping their full benefits. Many companies are excited by AI’s potential, but few put real resources behind implementing it.
Last week I had the opportunity to speak on a panel hosted by Frost & Sullivan at their Mind of the Enterprise conference in Boston. One of our panelists was Lance Olson, Founder and CEO of Vecna Technologies (NASDAQ: VECNA), who talked about how they’ve managed to more than double sales over the last four years through technology investments. During that discussion, he pointed out that although his company has spent significant amounts on research with universities around robotics, AI and machine learning, most businesses can’t or won’t do the same.
This is too bad, because artificial intelligence is on the cusp of transforming business—especially manufacturing and supply chains. Just look at Tesla’s (NASDAQ: TSLA) work on autonomous vehicles, or Amazon’s (NASDAQ: AMZN) Echo device that uses AI to automate everyday tasks.
AI Is Already Here
While AI may be a buzzword today, but it isn’t just for techies anymore. Businesses are already using AI in ways that have an immediate impact on their bottom line, whether they know it or not. From predictive analytics to self-driving cars, AI is already here, but many companies are still left behind by failing to invest adequately in this area.
I think there are four main reasons businesses haven’t dedicated additional resources to AI:
They don’t recognize the long-term benefits of such investments. It’s harder than it looks. They think it’s too expensive and complicated to implement. They don’t understand how it can apply to their business model.
Let’s take a look at each of these in turn:
1) Long-Term Benefits of AI Investments Are Not Always Apparent To Leaders
Most companies invest in technologies that they believe will improve sales or lower costs, but very few study the longer-term impact on brand reputation and overall company value. No doubt leaders understand that implementing cutting-edge technology may lead to short-term problems if not done correctly, but too many fail to see its potential—and pitfalls—over time.
This is why Vecna, which develops robotics software for the healthcare industry, has focused on investing in emerging technologies that are too risky or immature for others to touch. Their work with robotics, AI and machine learning is still relatively early-stage, but it has already yielded valuable insights into how devices can be remotely operated by medical professionals.”
2) Implementing Artificial Intelligence Is Harder Than It Looks
While most businesses probably recognize the potential benefits of artificial intelligence, they also know it’s easier said than done. Many have tried to implement some sort of big data analytics technology in the past only to give up when they encountered technical snafus along the way. One report suggested that less than 10 percent of businesses are able to successfully implement their big data projects.
Likewise, many companies have invested in robotics before without realizing the technology is still immature and has a long way to go before it can help them fully realize it’s potential. I know a few large business-to-business companies that thought they’d be able to automate certain tasks with Kiva Systems (now Amazon Robotics), only to find out several years later that the technology was nowhere near ready for prime time.
3) AI Is Expensive and Complicated To Implement
It’s no secret that implementing emerging technologies like blockchain, cloud computing and even mobile devices can be expensive and difficult for some businesses. In fact, one study suggested that less than half of all IT departments feel prepared enough to take on such major new initiatives.
This is especially true of AI, which requires dedicated resources and significant up-front investments. I’ve heard from consultants who advice companies on how to implement intelligent robotics that the second most common reason for failure (after technical issues) is a lack of available staff who knows enough about AI to properly carry out a project. That’s why it’s essential for organizations to invest in both human and technical resources if they want to successfully adopt artificial intelligence over the next few years.
4) Most Businesses Don’t Understand How to Apply Artificial Intelligence to Their Operations
It’s easy to understand the entire buzz around emerging technologies like blockchain, but many companies don’t even know where or how they can apply such concepts within their own business models.
Likewise, many organizations have invested in big data analytics only to find out that it’s harder than they thought to actually derive business insights from their data resources. The same goes for applying AI, which has the potential to transform nearly every aspect of a company over the next few years. Sure, some businesses are ahead of the curve when it comes to intelligent automation because they’re already using robotics or deep learning algorithms, but most are still trying to figure out how these concepts can apply to their operations.
Conclusion:
In spite of all the excitement surrounding artificial intelligence, most companies are still struggling with how to implement these technologies within their own operations. While many firms may realize that blockchain, IoT and other emerging concepts have the potential to transform their businesses over the next few years, they aren’t sure where or how to start. This explains why so many organizations remain on the sidelines despite a lot of noise in the market about these advancements.
