If AI is the new electricity, here are three principles to help your business avoid becoming the steam-powered factory of the 21st Century

‘AI is the new electricity’. So says Andrew Ng, the Stanford professor and former head of Google AI, who has spent his career at the forefront of the artificial intelligence and deep learning revolutions.

After a flurry of media attention over the past 18 months, it seems this message is breaking through, with 85% of business leaders recently responding that AI is likely to transform their industry.

This increased attention is important, though it’s yet to translate into clear action. Only 5% of respondents in the same survey said that they’re actually utilizing AI as a meaningful part of their current operations.

This lag should worry these businesses. If AI is the new electricity, history illustrates the stark danger of inaction.

At ViewX we’ve observed two contributing causes for this: first, senior executives still think in future tense, not realizing the extent to which the AI revolution is already upon them. And second, there is almost no practical guidance for business leaders on the simple steps they should be taking now to set themselves up for success.

There are two points that every business leader needs to keep in mind now, or else risk ending up a steam powered factory of the 21st century.

Point One: It’s the year 1900 for AI

To appreciate the urgency of AI adoption it’s important to electrification in its full context; the ubiquity of electricity today makes it easy to forget what a seismic event it had on the economy 100 years ago.

The introduction of electricity to the economy produced famous leaps in the productive capacity of businesses in virtually every industry. It produced an explosion in business capabilities, with average productivity growth rates rising to roughly five times greater than what we’re used to today.

While it produced enormous winners, it also produced huge classes of losers from those businesses who failed to act. An under-appreciated fact about electrification was that it drove the highest rate of business failure for established entities for any period in the 20th century, outside the Great Depression. That’s because it created competitive advantages for those who adopted it that effectively wiped out their steam-powered competition.

And this process happened quickly. In 1900 less than 5% of all industrial power in the US came from electricity. Steam power still reigned supreme with its reliable but limited single steam engine. Fast forward just 10 years though, and electricity’s contribution will have jumped to over 50%. Ten years after that and the electrification of the economy was complete. In just 20 years the era of steam power was over.

The relevance today of this today is that AI is the same age now as electricity was in 1900.

For electricity, the inflection point came from the construction of centralized high-voltage power stations in 1889, producing a reliable supply of electricity to business. The equivalent inflection for AI happened in the late 2000s with the discovery that GPU chips — originally designed for video games — were uniquely suited to the complex processing necessary to accurately mimic human brain performance.

This is what’s known as AI’s deep learning breakthrough; a development that suddenly opened up the massive digital data sets, that had been produced by the rapid spread of the internet and the inexorable digitization of the economy, necessary to feed the deep learning processes and transform their effectiveness. This combined growth of computing power and data supply transformed the capacity of AI to perform, and learn from, increasingly sophisticated tasks. This is why you’ve likely noticed an uptick in news stories over the past several years where AI has started to outperform humans in an increasingly wide range of tasks.

Hence the risk for businesses. If we’re in 1900 for AI, we’re about to hit a seismic period of disruption that creates huge classes of businesses winners and losers. And this change happens fast.

Point Two: Here are three simple principles to help every business incorporate AI

The lessons of electrification provide a useful starting point for how businesses can and should respond now. We’ve combined these insights with our experiences in bringing AI to the enterprise to distill three practical principles that distinguish the thinking of the most forward-thinking executives today, and which every senior executive can adopt to incorporate the benefits of AI capabilities to their business. They are:

1. Think big. Don’t settle for merely swapping out your steam-powered engine

2. Your data pipeline is your assembly line

3. Hire talent to design your wiring, not build your own grid

Adopting these principles is the meaningful first step most executives are missing, towards giving your business the best chance of thriving in this AI age, and avoiding being the steam-powered factory of the 21st century.

1. Think big. Don’t settle for merely swapping out your steam-powered engine

An early steam turbine. The early attachment to them is not totally clear now

By far the biggest failure of business owners in the 1900s was the failure to think big about the transformative potential of electricity. We see the same trap befalling uncertain executives today who tend to think of AI primarily in terms of basic automation and cost reduction opportunities. Just as with electricity, the big winners of the AI age will be those that direct their AI efforts at growing revenue and market share, not just shaving incremental cost.

For steam-powered businesses of 1900, the most common early adoption of electricity was simply to replace your steam-powered engine with an electrical one, leaving everything else about your factory intact. Not only were the results financially underwhelming — most usually failed to pay back the initial investment costs — but worse, the disappointing initial results often led early experimenters to dismiss electricity as a mere technological gimmick which had little practical business benefit and opt instead to stick with tried-and-tested steam.

As we know now, the benefit of electricity was not in its ability to produce power marginally cheaper than steam, but to completely re-define where and when power could be delivered to your workforce.

This was the insight of innovators like Henry Ford, who recognized the transformative potential of electricity to completely re-configure his factory floor in pursuit of improved productive output. Rather than seeking to do the same thing only slightly cheaper, Ford completely reimagined the production process, redesigning his factory from top to bottom so that his workers — no longer dependent on centralized power — were able to employ their tools whenever and however was best. The results of this re-thinking are now legendary, with Ford’s electrified factory seeing a 70% improvement in the productive output of his workforce, a capability that drove a five-times increase in his market share over the next six years, from 9% in 1908 to 48% in 1914.

This is the same kind of thinking that will win in AI today. Just as electricity untethered productive capacity from the limits of mechanical power, AI now allows us to extend this even further, pushing us past human limitations. It allows us to process and use information at a scale and level of complexity that — just like the ability of electricity to deliver flexible mechanical power — were previously unimaginable.

At ViewX we’ve seen a great example of this in the way our media industry customers are using our technology to transform their video capabilities. Using our AI models — which are able to automatically read and understand vast video libraries at 70x human speed and 6x human quality — have helped these companies turn video from a pain point into a critical differentiator, transforming the scope and quality of their content experiences and delivering performance improvements of up to 180% as a result of higher utilization, consumption and monetization of this video content.

The lesson to take from these applications is that if you’re thinking of AI only in terms of cost reduction, and not at top-line growth, you’re not thinking big enough; you’re basically fitting out a slightly cheaper steam-powered factory.

2. Your data pipeline is today’s assembly line

The Model T and the model for how you should think about your data

The second principle today’s businesses can take from electrification is that the critical importance of reconfiguring your processes to truly activate the benefits of the technology. In 1900s, this meant innovating your assembly line. With AI it means reimagining your data pipeline.

To understand this let’s jump back to 1900 and the steam-powered factory, which would have been an awe-inspiring sight: entire floors of workstations connected by a complex network of leather belts and pulleys, all connected to a monolithic single drive shaft powered by a giant single steam engine.

However, its main strength — a reliable central power source — was also its critical limitation, requiring that the entire design of factories be based on those machines that needed to be closest to the drive shaft to get enough mechanical power. Electricity changed all this, enabling processes to be designed with production efficiency in mind, rather than merely what was needed for power supply. This was the birth of the modern assembly line. AI does the same thing today, but for data.

At its core, AI transforms the ability of today’s business to make use of information, redefining the capacity to gather, interpret and utilize masses of available data, to find previously unidentifiable connections, and to deliver insights, predictions and recommendations that improve business decision-making and transform business performance. Much like the assembly line changes during the 1900s, the business executives who are distinguishing themselves with AI today are the ones actively re-designing their business processes to collect more, and higher quality, data at every instance.

Again, we’re seeing great opportunities at ViewX in workforce enablement applications, where our AI can be used to analyze the millions of communication data points generated by their employees in day-to-day interactions to identify the skills and knowledge gaps that can be filled by delivering highly relevant information and guidance right to their fingertips. To do this requires concerted effort to identify, collect and design data capturing processes to make the most of this AI-enabled information, but once you do, research indicates that the payback is improvements worth up to 15% higher annual revenue performance from this new information-enhanced workforce.

3. Hire talent to design your wiring, not build your own grid

Early on-site electricity generators. You don’t need the AI version of these

The third and final lesson for today’s business owners is that the winners of electrification were those that most efficiently applied electrical power, not those that tried to build their own.

The knee-jerk response of many businesses of the 1900s was to build on-site generators, mistakenly identifying production as the source of competitive advantage for electricity. It seems ridiculous now, but we see this same dynamic playing out today in too many unsure executives who assume that introducing AI capabilities requires the recruitment of internal AI functions to build their own technology. Not only does this rarely pay back, it even more damagingly encourages the belief that, if these kinds of investments are out of reach for your business, so too are the benefits of AI. Nothing could be further from the truth.

Rather, the target in-house AI capabilities for almost every company we come across is met simply by having dedicated senior executive responsibility for identifying the capabilities and processes to be targeted for AI-enhanced performance improvements. At its core, this role requires an understanding of the AI landscape, awareness of the technological capabilities, and the authority and support to identify and recommend the most impactful application of AI to your business performance.

At ViewX we’ve seen this role performed well by a variety of functions like CTOs, Chief Product Officers and Chief Data Officers, when they possess a strong technical understanding of AI and are given cross-functional mandates. Other companies leaning heavily into AI are creating Chief AI Officer or VP of AI roles to quickly ramp up AI activities. At the end of the day, title is less important than substance, and the right choice will depend on the specifics of your company’s unique context and existing executive structure.

Most importantly, the winners of the AI age will not be those that spend their time unthinkingly trying to replicate core technology, but instead be those that maintain the ability to plug into the latest technology evolution, and then are most decisive in applying their domain expertise to translate that technology into transformative business performance.

Practical steps for meaningful benefit from AI

All available evidence points to the fact that we’re in the year 1900 for AI, which if true, means that we’re about to see a period of wide-scale disruption as AI-enabled capabilities sweep through every industry.

At ViewX we specialize in delivering our proprietary AI in a way that transforms business capabilities. The three principles we’ve laid out provide a practical starting point designed to help your business actively configure itself to plug-in to AI’s productive potential and translate this technology into tangible business benefits. We’d love to hear from you if you have any questions or could use some advice as you think through your own applications.

As history teaches, the sooner and more effectively you act, the greater chance you give yourself to thrive on the benefits of this technology, and the more likely it is your business won’t end up as the steam-powered factory of the 21st century.