If your company is like most, a majority of its IT spending is trapped in the ongoing maintenance, integration and security of legacy (read: old) systems and applications, leaving precious little time and money for truly innovative technology services. A chief information officer’s main challenge is to escape that trap, focusing much more on deploying cutting-edge technologies that will create a competitive advantage, much less on preserving the status quo.
We asked eight leading CIOs which emerging technologies and strategic initiatives are top of mind for them—even if those technologies aren’t quite on their roadmaps yet. Their responses included a mix of general purpose and industry-specific technologies.
Artificial intelligence and the related machine learning topped most of their lists. Those technologies—the building blocks of self-driving cars, retail recommendation engines, smartphone assistants and other ‘smart’ applications—are still creeping up the adoption curve. But most of the CIOs we interviewed think applications that can analyze, reason and propose actions will play a central role in how their organizations serve customers and run their operations.
One early AI-powered asset mentioned by a few of the CIOs is chatbots—digital assistants that answer customers’ and employees’ questions and help them make better decisions. “We believe the future of digital is ‘conversational commerce,’ and chatbots will provide the bridge between consumers and businesses, combining intimacy and automation in a more personalized and simplified customer experience,” says Jaime Vogel, CIO of Australian Finance Group, a Perth-based provider of home-mortgage, insurance and other financial services.
Ryan Klose, CIO of National Pharmacies, a chain of pharmacies in southern Australia, is energized by the potential for chatbots to change the conversations the company has with its member-customers. Klose sees chatbots opening the door to in-home robots that remind customers to, say, take their meds or test their blood-glucose levels and log the results. Advances in natural-language technology, and the ability to connect chatbots to data in enterprise customer service, sales, supply chain and other applications, make those engagements ever-more viable, he says.
National Pharmacies is pilot testing chatbots to serve both employees and customers. “It isn’t what we’re doing today so much that excites us about chatbots,” Klose says. “It is where they’re going to take us.”
More broadly, AI and advanced machine learning will provide “the foundation for the convergence of data, knowledge and intellect,” AFG’s Vogel says. “Machine learning is already assisting AFG in a number of ways, like determining the propensity for a customer to refinance. However, this is just the tip of the iceberg.”
Gaston Perez, chief technology officer of Dr. Consulta, a network of low-cost health management centers launched in São Paulo, Brazil, in August 2011, acknowledges the expanding hype around artificial intelligence. “But for us, AI is a standard,” Perez says. “It allows us to always deliver a high level of service.”
Using machine-learning algorithms to correlate clinical data and patient conditions will help Dr. Consulta’s doctors make more precise diagnoses and ultimately serve patients more efficiently, he says. And by sifting through vast amounts of data in medical journals and research reports, AI will also help the network’s doctors and other practitioners keep current on recent discoveries and treatment options. “It’s impossible for doctors to keep pace with all of the new medical knowledge out there,” Perez says. “By the time a doctor leaves medical school, much of her medical knowledge is already outdated.”
Margaret Miller, whose 30-year career in IT includes leadership roles in the private and public sectors, most recently as CIO of New York State, is particularly excited about AI-based rules engines—software systems that execute customer service, production, inventory, legal and other business rules that are essentially ‘if-then’ processes. For example, if a regular customer hasn’t bought anything from a company for more than three months, a business rule might trigger a friendly email to that customer with a discount offer.
“These products have matured very quickly to the stage where they can provide the core processing underpinning many applications,” Miller says. “These engines are essentially the first large-scale implementation of artificial intelligence, packaged in such a way to support rapid, reliable development of complex applications.”
Jason Wenrick, CIO of Sonoma State University in California, is interested in the potential of AI to serve as a kind of computerized student adviser, factoring in a student’s interests, grades in different subjects and schedules in order to suggest courses to take and majors/careers to pursue, as well as how to schedule classes to fulfill graduation requirements most efficiently.
“Those are the rules that allow people to start finding and tracking patterns and then you can start programming in and automating a lot of this stuff,” Wenrick says. “But that’s a ways off. I still think you’re going to need that human touch, the personal interactions with the student where counselors start gauging their interests, why they are doing certain things. Those are never really going to be replaced.”
Christian Anschuetz, chief digital officer at UL (formerly Underwriters Laboratories), is exploring potential applications for machine learning and “advanced, intelligent automation” via bots.
“These two technologies are opening up new areas of commerce for us and enabling us to create entirely new business models,” says Anschuetz, alluding to the company’s move to offer customers professional advisory services in advance of product development, in addition to its traditional product testing and certification services. “Exciting times.”
Promise of Big Data
A close kin of AI and machine learning is advanced data analytics, as enterprises are now collecting and buying more data than ever before, providing the fuel for smart machines and applications to make more informed, insightful, accurate and timely decisions and predictions.
Sonoma State’s Wenrick notes that AI-assisted data analytics are already helping universities identify at-risk students, so that counselors and administrators can intervene before they drop or fail out. For example, such analytics have flagged that students who eat breakfast daily are far more likely to succeed in their classes than those who don’t.
Former New York State CIO Miller notes that the volume of structured and unstructured data collected from applications, social media and the Internet of Things far surpasses the ability of most enterprises’ internal functions to process it.
“This is a perfect use of cloud-based services, whereby off-premises capabilities can be used to process the data, ideally supported by specialist analysts who can help make sense of the data,” she says. “These capabilities are specialized and rare and so far better ‘rented’ than developed in-house.”
Many organizations are also grappling with how to bring together data from multiple sources, both onsite and in cloud vendors’ data centers. Some cloud services have their own data models that are inconsistent with other such products, as well as with legacy on-premises applications, Miller says. Master data management tools aren’t brand new, but they will be ever-more essential by allowing enterprises to reconcile the data held in an increasingly complex web of software services, she says.
No technology frontier is as expansive as the Internet of Things, the science of collecting data from sensors embedded in a variety of networked machines, work environments, wearables and other devices and then analyzing that data to reveal new insights and market opportunities. Estimates put the number of ‘things’ that will be connected to the internet at about 50 billion by 2020, feeding a worldwide IoT products and services market projected to reach $7.1 trillion. IoT applications and connectivity will transform almost every industry, from industrial manufacturing to agriculture to transportation to pharmaceuticals.
One early adopter is agribusiness and food company Land O’Lakes, which for years has been using various aspects of IoT, mainly for precision farming—when, where and how much to plant, water, fertilize and harvest to produce the highest yields.
Like most of the other CIOs we interviewed, Land O’Lakes CIO Mike Macrie is also experimenting with other emerging technologies: AI for robotics and automation; virtual reality and augmented reality to teach modern farming techniques to farmers in Africa; and blockchain, the digital ledger security technology, for tracking and tracing food supplies.
“All of these emerging technologies are poised to radically change how farms operate and will reduce the overall environmental footprint of global agriculture,” Macrie says. “We’re excited about leveraging these technologies to increase yields enough to feed the world in the most sustainable way possible.”
Agility to Innovate
Jeff Wollen, CIO of Wiggle, an online retailer of athletic gear and attire for triathletes, is in a different position from the other CIOs we interviewed. Because Wiggle is a ‘cloud native,’ it isn’t saddled as much with the cost and complexity of legacy systems. As such, emerging technologies are front and center for Wiggle, not something to consider sometime down the road.
“Being smaller means you’re much more nimble,” Wollen says. “You can jump straight to the world-class products and systems and cloud-based solutions that you never could have had access to before. Companies like Oracle have spent billions of dollars in maturing and evolving the retail product set and its capabilities. So now, as a startup or a relatively small company, we can avail ourselves of that richness that allows us to compete with the big boys.”