Industry 4.0 Expert Leader
Vicki Huff Eckert, Global Leader, Technology
Most innovation strategies today encompass emerging technologies, including artificial intelligence (AI). As the business advantage of the future, according to 72% of business decision makers recently surveyed by PwC, artificial intelligence and its value are critical concepts for business leaders to grasp. AI is technology that can understand, learn, and then act based on gained or gathered information, holding the potential to transform markets far and wide. Businesses are betting big: 54% of executives in our 2017 Global Digital IQ Survey tell us their companies are making substantial investments in AI today; in three years, that number increases to 63%. The rise of AI comes at a point when many companies already are feeling pressure to reinvent. They see industries around them transforming and more nimble competitors jetting ahead. In this environment, some are making investments in emerging technology are motivated not by pragmatic strategy, but by fear. This reactive mindset often leads to haphazard deployments, a poor user experience, and wasted funds. These projects won’t pay off and in the end will only serve to slow down adoption. One of the fascinating findings from a recent report on artificial intelligence is that 54% of business executives say the AI solutions they have implemented have benefited productivity. That means that nearly one in two executives who have utilized AI to date either achieved a benefit other than productivity—and there are many—or were disappointed in the results. I’d wager that a few of these projects were implemented without clearly aligning operations, strategy, and corporate goals.
With so much excitement and media buzz about AI, it can sometimes feel like trying to jump aboard a runaway train. It’s important to take this hype seriously, but taking a thoughtful approach to AI is just as important. It’s powerful technology, but AI will pay off only if you are poised to take advantage of it.
For any innovation, the key to success is mapping the possibilities of the technology to your real-world corporate strategy. The model must make sense with the business you’re in and the realities you face today. These days I see so many innovation projects fail—expectations are too high, timelines are too tight, investments are misdirected or not enough. To beat the odds, start by considering what will have the greatest impact on your core business and proceed in a thoughtful, systematic manner from there.
My colleague Anand Rao has published the Strategist’s Guide to Artificial Intelligence, which is an excellent outline of the current AI landscape from a business perspective. He highlights some important considerations for any company evaluating AI systems.
He notes that although most 2017 Global Digital IQ Survey respondents say they are making substantial investments in AI today, only 20 percent say their organizations have the skills necessary to succeed with this technology. This statistic is concerning, because user adoption is the greatest indicator of long-term success for any emerging technology. Not everyone who touches AI needs a PhD in data science, but your strategy must address human capital. Taking AI from the lab to the lines of business will require a workforce that has the necessary skills and knowledge to leverage the technology. You’ll likely accomplish this goal through a combination of investments and training. Look at the strategies for building a data science and analytics talent pipeline in our new report on the 2017 data science and analytics job market that we prepared with the Business-Higher Education Forum.
Anand also outlines the three ways that AI works today: assisted intelligence, augmented intelligence, and autonomous intelligence. These approaches sit on a continuum and complement each other, but they require different types of investment, different staffing considerations, and different business models. Assisted intelligence, for example, amplifies the value of existing activity and can be used widely today to alleviate repetitive, menial tasks such as scheduling—something 79% of respondents in our survey were eager to hand over. The strategic selection of the tasks to be automated is critical. Assisted intelligence is a great strategy for cost centers but should be carefully implemented when applied to human-based variable revenue models to avoid inadvertently shorting revenue.
As Anand notes, the field of AI is evolving quickly, and capabilities are expected to increase while costs decline. As AI matures and new practical applications emerge, it will be increasingly important to consider how AI plays a role in your digital transformation strategy. But it’s equally important to ensure you are taking a thoughtful, considered approach to this innovation and transforming what is transformable.