Will AI liberate the IoT's potential?

When deployed in tandem, artificial intelligence (AI) and the Internet of Things (IoT) can bring powerful new capabilities and competitive advantages—a net effect that is greater than the sum of its constituent parts.


This is the central finding of a new study conducted by SAS, Deloitte and Intel with research from IDC based on survey of 450 global business leaders. Entitled “AIoT: How Leaders Are Breaking Away,” the survey report indicates that this combination of technologies, dubbed the Artificial Intelligence of Things, represents a key competitive advantage that already has passed from pilot-scale tests to early rollouts.



As companies grow into a fuller implementation of IoT, they begin to realize that the tremendous volumes of data generated are difficult to tame. In this context, the combination of AI with IoT is a natural fit for gaining insights that can help advance not just operational goals but business strategy.


Consider some of the findings the research brought to light:

  • 99% of respondents said, in aggregate, the benefits of using AI together with their IoT solutions met or exceeded expectations.

  • 90% of respondents who reported heavy use of AI for IoT operations said it exceeded their expectations for value.

  • 35% of senior leaders cited increased revenue as the single most important area of improvement they expected to achieve from their IoT efforts.

Overall, projects that combine IoT with AI are having a greater-than-expected impact in operations, the enterprise and ultimately, the bottom line.


The expectations game

It came as a bit of a surprise to IDC’s Maureen Fleming, program vice president for intelligent process automation, that leaders value the addition of AI to IoT projects as highly as the do. She confessed to Smart Industry that in her travels and client encounters, she’s been “barraged” with negative feedback to the point where “it seems like everywhere I go people are talking about the high failure rate of digital transformation efforts.”


Naturally, she expected lower engagement among respondents. “But what we found true is the exact opposite.” One possible explanation for the surprising, healthy attitude toward this thing called AIoT is that it’s the IT and operations leaders who fret over the details more than the CEO’s office. According to the research, 56% of senior leaders believe their AIoT projects significantly exceeded expectations, a margin 18% greater than operations-related teams and 31% greater than data scientists and IT leaders. Interestingly, operational leaders were the greatest proponents of IoT alone (Figure 1).


Figure 1

“In my experience, senior executives tend to be a lot more optimistic than those at other levels in the organization—it’s kind of a requirement for the job,” says Shak Parran, partner at Deloitte Canada and analytics leader for its Omnia AI practice. Below the top floor, he says, the practical reality of putting these capabilities to work can make data scientists “a little more pessimistic. They know that their data has to be cleaned up, they have to teach machines to do the right things, their processes have to be optimized, and so on. They see the obstacles, because that’s what they’re responsible for navigating.”


The good news is that this attitudinal gap may close over time, if an observation by Melvin Greer, Intel’s chief data scientist, comes to fruition. “Over the past 24-36 months, we’re seen ample evidence of chief data officers moving into the CEO suite.”


A competitive AI-vantage

As implementation teams have matured, so has the likelihood of success with digital transformation initiatives. For successful projects, focus shifts from connecting devices and collecting new and different data to the next step of the journey, analytics. From analytics to the use of AI is another step forward in the ability to filter, correlate and uncover complex relationships. The researchers confirm that industrial firms are indeed moving from proofs of concept and pilot tests to production systems with analytical approaches that incorporate AI.


The key to driving long-term, sustainable value with AIoT lies in building experience with large-scale rollouts, with higher levels of automation, throughout the organization. And the only way to reach that scale with AIoT is to increase the level of automation, according to Oliver Schabenberger, COO and CTO at SAS. “So many CIOs I talk with say automation is a primary focus, to make IoT-related analytics insights consumable by business analysts and others, not just the data scientists.