Artificial Intelligence: Going Mainstream Faster Than You Think

Digital leaders are betting big that Artificial Intelligence (AI) will have a profound impact on the future of digital business.

So, what’s the easiest way for traditional companies to take advantage of AI capabilities? Focus on AI-powered cognitive services—computer vision, machine learning, natural language processing, speech recognition, and robotics.

Organizations that take this approach will score quick wins, generate value faster, and achieve long-term success four times more than organizations that don’t, according to Gartner.

AI Going Mainstream

Yes, implementation cost and complexity may hamper adoption in non-tech companies. But that hasn’t stopped many organizations from either thinking about AI or experimenting with it.

All you have to do is look around to realize that digital leaders—across a variety of industries—are moving beyond experimentation to integrate AI into their business operations.

Meanwhile, some of the biggest brands on the planet are placing huge bets on artificial intelligence, betting on everything from face-scanning smartphones and consumer gadgets to computerized health care and self-driving cars.

Cases in point:

• General Electric has leveraged AI, machine learning and Big Data, to transform itself into a “digital powerhouse,” with $7 billion in software sales in 2016, and expectations to double digital revenue to $15 billion by 2020.
• German automaker Audi has introduced a smart sedan that uses AI to drive itself autonomously— while in traffic jams.
• In medicine, researchers at McGill University unveiled a computer-driven algorithm that can predict Alzheimer’s progression with an accuracy of over 80%, proving that AI can detect disease patterns in brain scans long before humans.

It’s also worth noting that AI has quickly gone mainstream in popular consumer devices such as Apple’s Siri, Amazon’s Alexa, and Google’s Home Assistant. And this trend is happening faster than many could have imagined just a few years ago.

The million dollar question is: Will consumers expect the same level of digital interaction with banks, retailers, airlines, utilities, healthcare providers, and other organizations?

Great Expectations

While the emergence of AI has fueled great expectations, critics warn AI will kill jobs and spark a machine-learning apocalypse that will send humanity to its doom.

The good news?

Research shows the opposite is true, that technology has created more jobs than it’s displaced over the last 140 years.

More important, technology tends to displace dangerous, routine, jobs with higher-value, knowledge work.

Bottom line? The promise of AI, evidently, outweighs the risk.

Here’s the math:

• Worldwide revenues for cognitive and artificial intelligence (AI) systems will reach $12.5 billion in 2017, a huge 59.3% surge over 2016, according to industry analysts at IDC.
• On top of that, global spending on cognitive and AI solutions will hit a compound annual growth rate of over 54% through 2020, with revenues expected to top $46 billion.
• In the healthcare industry alone, the market for AI is projected to reach $6.6 billion by 2021, a 40% growth rate, according to a 2016 study by Frost & Sullivan.
• AI has the potential to improve patient outcomes by 30 to 40%—and reduce treatment cost by as much as 50%, according to the Frost & Sullivan report.
• It turns out that 38% of enterprises are already using AI, according to a recent Narrative Science survey. And that number is expected to top 60% by 2018.

Double Down or Wait?

So, should you double down now? Or, wait for the AI hype cycle to peak?

“It takes time to build the infrastructure to support emerging technologies like AI,” says Rita McGrath, a globally recognized expert on innovation and growth strategies.

“In 2018, I think we’re going to see emergence and disappointment in Artificial Intelligence and Machine Learning,” says McGrath, “…What AI and Machine learning can do better than people, is detect rich patterns that underlie massive amounts of data. These technologies are going to change a lot of things, but it’s going to take a lot longer than people expect….”

At the MIT Sloan Initiative on the Digital Economy, Principal Research Scientist George Westerman says that many traditional companies are investing in emerging technologies like AI, but that very few are doing it well.

“The ones that are doing it digital well,” said Westerman, “… are doing two things better than their competitors. They’re not just investing in digital, they’re using technology to transform operations and the customer experience…”

Vijay Gurbaxani, Founding Director, The Center for Digital Transformation at the University of California, Irvine, agrees.

Dynamic Duo: AI and Big Data

“I think Artificial Intelligence and Machine Learning are among the biggest things on the radar…. But I would say that the bigger challenge is to think about how all of this comes together,” says Gurbaxani. “I think we get caught up in seeing the trees and not the forest. We need to see how the world is changing. Not worry about a specific technology.”

Digital businesses are already pairing AI and big data to learn customer browsing patterns, purchase history, and preferences. Then offer personalized recommendations as customers browse online, or chat with merchants via messaging apps.

In the call center, AI is boosting productivity with applications that can identify customer calling patterns in hours instead of weeks or months.

AI-powered “bots” are being used to handle routine tasks—with natural language processing—to interpret customer requests, and instantly search back-end systems for answers, without the help of live agents.

Ready to Gear up with AI?

AI technologies will be in almost every new software product by 2020, according to Gartner.

The big challenge, though, is cutting through the hype of numerous software vendors, which can make selecting an AI vendor difficult and confusing.

Okay, but what if you’re having a “big gulp” moment with disruption, and you want to gear up with AI right now? What’s the best approach?

Perhaps it’s worth considering what Matt Calkins, founder and CEO of Appian, said about Appian’s approach to AI, in a recent Forbes interview.

“To me…general-purpose AI has no context at all. It’s just ‘here’s the world, you figure it out. …So AI is, in my opinion, a high-context application, which is to say it needs a lot of context in order to be valuable…It’s really a training wheels type of technology at the moment.”

Calkins also said that Appian’s approach to AI is structured around the idea of serving as a data divination partner to the businesses that use it. He added that the goal is not to eliminate human judgment entirely, but to help guide and inform it.

“… AI is way too difficult right now. Appian makes it easy. You just put your dataset in, you click a button, it gets uploaded to Amazon, and then you can have Amazon as an object giving you advice. You can just include that on the screen. So the screen is like, ‘Here’s your decision,’ and down below it says, ‘Your AI recommends the following.’ That’s where AI belongs.”

Hmm, combining AI with the Appian Low-Code Platform.

It doesn’t get any easier than that.