IT trends: What you missed at MIT CIO 2017

Each year, the MIT Sloan CIO Symposium serves as a leading indicator of technologies and business issues that are top of mind for IT leaders. At this year's symposium, CIOs were focused on three C's: connectivity, collaboration, and cognitive computing. Speakers and attendees alike buzzed about how the lines between IT and the rest of the business have become not so much blurred as nearly nonexistent.

CIOs and other top IT execs (many of them MIT grads) largely agreed that "digital" is now in just about everyone's job description. Meanwhile, exhibitors and regular attendees discussed how their organizations have all become technology businesses—even if technology isn't their core business—because of trending technologies like artificial intelligence (AI) and the Internet of Things (IoT).

Accordingly, MIT CIO speakers distilled these three key talking points into three respective tips on modern business agility. The upshot is that enterprise IT can use these tidbits to better respond to both the needs of the business and the needs of its customers.

AI: Augment—don't replace—human intelligence

AI was one of the primary focuses of this year's symposium. And yet what marketers and salespeople refer to as "AI" today doesn't fit the more platonic idea of AI as a generalized intelligence that can self-actualize its own programming and function.

The reason why AI (or, more precisely, machine learning) is enjoying such massive interest of late is because of recent technological advancements in data collection, data storage, and computation—hence making theoretical ideas on AI from the 1960s possible today.

Ali Azarbayejani, chief technology officer of Cogito, a behavioral analytics software company, was emphatic that true, "generalized" AI is still far from reality. Instead, machine learning and other AI-like technologies are best leveraged as "augmentative intelligence." Cogito provides natural-language processing and machine learning technology to analyze customer service calls. Cogito uses this data to help call center employees and supervisors improve their performance.

This runs counter to the AI vision of robots handling customer service calls all by themselves. One problem with leaving customer service to the robots—aside from present technological challenges—is a loss of trust. In the AI-replacement model of customer service, Azarbayejani explained, a customer or user who has already been failed by the company's systems is asked to invest time and energy in again trusting the company's systems. Instead, AI is best leveraged at this point to augment and support human understanding—helping to make people their best selves—instead of trying to replace humans altogether.

IoT: Let big data do double duty for monetization

It has become relatively common knowledge that as the Internet of Things (IoT) has made data more ubiquitous and accessible, it has made businesses more efficient and helped them save money. For the modern CIO, though, the next step is to leverage IoT to make more money.

Jeff Kaplan, managing director of cloud consultancy THINKstrategies, frequently speaks on the global economic shift from products to services—and how this shift is both connected to and enabled by the IoT. At a networking lunch session at MIT CIO titled "Becoming a Connected Company," Kaplan emphasized that IoT today is more than just incorporating sensors into legacy devices to snag data about current business operations. IoT also enables entirely new business models. 

Kaplan used the example of Caterpillar to show how IoT, cloud computing, and real-time data analytics are boosting business agility by creating new revenue opportunities. Originally, said Kaplan, Caterpillar used IoT sensors on its tractors to inform vehicle maintenance programs. Eventually, the company realized that it could leverage the data it was collecting via its tractors to sell "agriculture information services." This simple discovery has revolutionized how Caterpillar and other agriculture companies do business.

"[With IoT], we can sell more information to people for added value," said Kaplan, who added that IoT can also provide "a way you digitize your employees, so they can feel engaged in that world."

DevOps: The two-pizza rule

Engaging employees—both within and outside of IT—for effective collaboration was the third big idea that carried the day at MIT CIO. IT leaders agreed that the best ideas can come from anywhere in the organization.

This opportunity presents a problem, however. On the one hand, modern agile development methodologies are stunted when only one person—or even a very few—are siloed away as they attempt to plug along on a project. This is especially the case when multiple, particularized branches of expertise are required on a project. On the other hand, agile methodologies can also suffer from the bureaucracy of "too many cooks." So how do CIOs foster and ensure the right amount of collaboration?

Christopher Crummey, executive director of X-Force at IBM, offered attendees a positively delicious answer: Make sure that two pizzas can feed all collaborators. The "two-pizza rule" is often attributed to Jeff Bezos, who argues that no meeting should ever be so large that two pizzas cannot feed the group. The problem with communication is that too much communication hinders collaboration; communication should be optimized in execution rather than maximized in volume. The rule has been backed up by research—suggesting that the optimal size of a collaborative team is four to five colleagues (and never more than 10).

Crummey suggests that eight to 10 collaborators is the optimal size for a productive team. Keeping teams a reasonable size (large enough to talk at a biggish table but small enough to not have their voices drowned out) is generally a winning collaboration solution in DevOps and other projects—any way you slice it.