AI in Action: Real-World Examples and Success Stories

By Max Votek

When you think about artificial intelligence (AI), the 1950s wouldn’t be the first thing that comes to mind.

After all, AI’s capabilities are more akin to the technological advancements of the 21st century.

But AI as we know it came into fruition during the boom years, also known as the 1950s, noted Co-Founder and Chief Technology Officer at KUNGFU.AI, Ron Green.

He was among the speakers at Innovation Day Miami, a Customertimes-hosted event held earlier this year that brought together a select group of guests to discover AI insights across various industries.

Guests and speakers shared their thoughts on AI and on where they see the technology heading. To set the stage, Green gave a summary of the technology going back many years.

“The history of AI was decades of research and advancement, punctuated by overpromising and underdelivering,” Green said.

Living In “The AI Renaissance”

Yet, amidst the ebb and flow of AI progress over the past seven decades, a resurgence emerged, bringing with it a new era of possibility.

We’re in that era today. Green likes to call it, “the AI renaissance.”

We have, for example, seen AI accurately predict breast cancer risk. Green said AI has been trained on 1.6 million mammograms from across the globe, and it can now predict breast cancer seven years ahead with 77 percent accuracy.

But even with the rise of AI, we still don’t see many cases of the technology being widely implemented across sectors, he noted.

Nevertheless, Green doesn’t recommend business leaders jump on the AI bandwagon for the sake of it.

“Don’t go do something around AI simply because you’re getting pressure from the board,” he said.

“Make sure the people [across your organization] who are using it also have by-in.”


Data: Gold Of The AI Era

Green also has a message for businesses that are sitting on top of a lot of data.

“If you have a proprietary data set in your business, you’re sitting on a goldmine,” he said.

“That can really differentiate you from your competitors.”

He gave an example of a company with two decades of data around pump jacks—devices used in the petroleum industry to extract crude oil from wells.

Based on all the data the company housed, it built an AI model that can now predict whether a pump will fail five days in advance with 87 percent accuracy.


Automation Isn’t About Killing Jobs

In another example, Green referred to a company in the transportation space that produces an exorbitant number of loans per month.

The company has hundreds of employees dedicated to processing the paperwork, sifting through the documents to catch fraudulent activity.

Now, the company has implemented AI, which is taking all that history of loan data, building a model out of it, and handling 80 percent of the decisions around the loans on a monthly basis.

And that’s good news for workers at the organization.

The hundreds of employees are still working there. AI hasn’t taken their jobs. Rather, it’s allowing the company to sift through the data deluge not only from the 9 to 5, but 24 hours a day, seven days a week.

And when AI has questions about the veracity of the documents, those questions go to the employees—who are a necessity to the success of the organization.

“[The employees] focus on the hard things, where they have to go on the phone to talk to people.”

The introduction of AI to this organization has done wonders for the company’s bottom line.

“This is incrementally adding hundreds of millions in revenue,” Green said.

Chief Operating Officer of KUNGFU.AI, Christian Barnard, echoed Green’s sentiment.

He also shared a glimpse into the window of AI opportunity for organizations today.

“We’ve been in business for six years. We’ve received four RFPs,” Barnard said.

“To me it’s an indicator of the maturity of the market. If clients don’t know to ask for, they can’t write an RFP.”

The business value is there for AI, but why aren’t companies racing to adopt AI?

Barnard said for many, the uncertainty and fear of failure are key concerns.

To address these concerns, business leaders need to manage AI-related risks and consider what the data availability is in their respective organizations.

Start by not focusing on the tech. Rather, focus on the organizational capabilities around how AI is going to be used and implemented in the company, Barnard added.

AI Implementation: Key Takeaways To Consider For Business Leaders

Innovation Day in Miami left business leaders with several key takeaways.

If you’re a business or tech leader considering implementing AI across your organization, avoid implementing AI due to external pressures.

Ensure you have organizational readiness and buy-in to align AI initiatives with business goals.

And if you’re a business with proprietary data sets, you have a competitive advantage in today’s market. You can differentiate yourself from competitors who lack such proprietary data.

Leveraging this data enhances decision-making accuracy. And that means your data is a strategic advantage.

Additionally, AI integration does not necessarily lead to job losses. AI can handle routine tasks, allowing employees to focus on more complex activities, improving job satisfaction and productivity. This approach retains jobs and enhances operational capacity.

Finally, the AI market is maturing, but many clients lack awareness of how to request AI solutions. Educating businesses on AI capabilities helps them better articulate their needs, leading to more successful AI implementations.

By considering these key takeaways, you can better navigate AI adoption and harness its potential to drive innovation and growth within your organization.

Max Votek

Max is one of the co-founders of Customertimes and also a trained pharmacist. He’s used his clinical knowledge to drive innovative tools that advance the life sciences industry. He’s committed to drive collaboration with pharmaceutical organizations around drug development, clinical trials, patient support, and field sales—all to continue the trajectory of innovation in the life sciences & healthcare sector.


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