This Paper Trail Is Causing a $1 Trillion Drag on US Businesses by Sam Colt

Rene Lacerte, CEO and co-founder,

This article originally appeared in The Huffington Post.

All good things must come to an end — especially those that aren’t very good in the first place. Few decisions could have such a widely felt impact on our economy as getting rid of checks, which have been burdening businesses with excessive costs for decades. It’s time to bid them farewell.

Checks aren’t just outdated — they’re hurting the companies that use them. Every time businesses use checks to pay vendors or their employees, they incur huge untold fees. $65 per check may not sound like a burden, but given that 20 billion paper checks are used each year, the cost to U.S. businesses is more than the market caps of Apple, Facebook, and Hewlett-Packard combined. The value at stake here is greater than that of our largest publicly traded company.

The cost of executing a check goes beyond just payment fees, which averages $13 per check. On top of that you have reconcile costs ($18 per check), error handling ($5 per check), invoice fees ($11 per check), and approval ($18 per check). That adds up to a whopping $65 per check, according to RPMG.

How could checks be so expensive? Once the only ostensible way for businesses to pay their employees, technology has enabled cheaper, better options — right?

Driven by an exploding Fintech industry, the world of finance going digital — and fast. Global investment in financial technology ventures tripled to $12.21 billion in 2014 and is expected to continue climbing in the coming years. Fintech startups are emerging to complement all of the finance industry’s core services: lending, payments, credit, and investing. For example, consumers don’t have to go through stock brokers anymore to make their investments. That’s handled in an app now — and at a lower cost.

There’s little doubt that the proliferation of Fintech startups is improving the lives of consumers, but lost in this tidal wave of technology are businesses, which have an even greater need for the innovation financial software can bring. The stakes are simply higher.

In addition to improving the consumer finance experience, startups have to recognize the tremendous opportunity they have to improve the way companies process payments nationwide. The technology exists to solve this pressing issue. It’s just a matter of time until checks are viewed through a glass pane in a museum, like mechanical cash registers.

There’s no doubt that fintech startups have disrupted our lives — changing many of the ways we interact with the financial institutions we’ve become used to. While tech companies should continue to innovate the consumer experience, there’s an arguably even greater need for disruption in corporate finance. Businesses of all stripes shouldn’t be forced to incur egregious fees to accomplish simple tasks like paying employees.

Technology is often thought of as a window to a better future. But fintech can do so much more than that — it can save hundreds of billions today.

Obsessing Over AI Is the Wrong Way to Think About the Future by Sam Colt

By Anant Jhingran, CTO, Apigee

This article originally appeared in Wired.

For many of us, the concept of artificial intelligence conjures up visions of a machine-dominated world, where humans are servants to the devices they created. That’s a frightening image, inspired more by Hollywood and science fiction writers than technologists and the academic community. The truth is less sensational but far more meaningful.

We’re actually nowhere near the self-sustaining robots Isaac Asimov imagined in I, Robot. What we have instead is intelligence amplification (IA), a field with exponentially more potential to change the world in the immediate future.

The distinction between AI and IA is as simple as it is significant. AI makes machines autonomous and detached from humans; IA, in on the other hand, puts humans in control and leverages computing power to amplify our capabilities.

For a real-world example of IA, look no further than IBM’s Watson, an intelligence amplification machine that is often mistaken for AI. The feedback loop created by exposing intelligence to humans through APIs enables Watson machine to learn and improve the information it provides. The machine presents that information to humans and then learns from their decisions. Like much of IA, Watson becomes smarter by amplifying our own intelligence.

While humans have used tools to bolster their productivity for centuries, the proliferation of application programming interfaces (APIs)—the mortar connecting the bricks of our digital world— in recent years has enabled greater access to valuable information in real time. The combination of intelligent computers, intelligent software, and APIs has profound implications for our everyday lives.

Doctors, for example, stand to benefit tremendously from IA in their interactions with patients. Say you have a doctor at the Mayo Clinic making a diagnosis. The patient is relying on the doctor’s expertise—but the publication of new medical research far outpaces the doctor’s ability to consume and analyze it. That’s where IA comes in. Rather than depending on his or her finite body of knowledge, the doctor can utilize supercomputers capable of surveying vast amounts of information quickly to present decisions the doctor might not have thought of or known about.

Meanwhile, present-day robots can hardly stay upright.

This isn’t to say artificial intelligence doesn’t have a significant role to play in the evolution of intelligent computers and they way we interact with them. Researchers at MIT, the University of Toronto, and elsewhere have advanced AI’s value in performing “soft intelligence” tasks like facial identification and pattern recognition—activities that ultimately improve judgment across the entire system. However, when it comes to “hard intelligence” activities like driving a car, AI still has a lot of learning to do.

Visions of the future have distracted us from what’s possible today. While Google experiments with self-driving cars that can be derailed with a simple laser pointer, automakers around the globe have already begun introducing IA-enhanced cars that can improve safety by assisting drivers with duties like highway driving on long-distance road trips. Tesla, Volvo, and Audi have or will soon introduce “autopilot” functionality on their vehicles. Though it’s still unclear when autonomous vehicles will become affordable for most Americans — keeping them in a world of moonshots for now — IA-integrated cars are something we can advance, utilize, and benefit from today.

Of course, technology will always need moonshot ideas —they’re what makes humans great. But focusing too heavily on fully-formed artificial intelligence misses the great strides we’re making here and now with intelligence amplification that’s actually changing lives.

The future of machine collaboration we’ve fantasized about is already here, and it’s not what we’ve been taught to fear. Our machines really are here to serve us—all we have to do is embrace them.

Anant Jhingran is Chief Technology Officer of Apigee, developer of an intelligent API platform for digital business. He is the former VP and CTO of IBM’s Information Management Division and one of the early technologists behind IBM’s Watson computer.