IoT Allows Organizations To Embrace AI and Other Digital Technologies: Study
IoT is by far the most widely implemented digital technology that unlocks the potential for more.
43% of organizations have embraced IoT, which has visibly improved operations and has facilitated rapid adoption of companion digital technologies such as AI, analytics, chatbots, etc. Cognizant assesses that IoT is key to future-proof an organization’s position vis-à-vis competitors.
IoT adoption has a direct impact on business performance, according to IT professional services giant Cognizant. The company discovered through The Work Ahead in IoT: The Gap Widens Between IoT ‘Haves’ and ‘Have-nots’ report that IoT adopters noticed improved operational agility that led to faster and flexible decision making and product/service development.
IoT is also facilitating the adoption of other digital technologies such as artificial intelligence, data analytics tools, chatbots, etc. The reason is that the scope of IoT as a concept is advancing from being a platform to a technology system that is increasingly becoming associated and, more importantly, reliant upon other enabling technologies that can unlock its true potential.
Besides AI/ML, 5G and edge computing are some of the key enablers of IoT adoption, with data at the center. “An increasingly pressing byproduct of digital migration is that organizations are now awash in data — whether it is sourced from IoT or elsewhere — and by all indications, the tidal flow of data shows no sign of receding,” Cognizant explained.
Intelligent analysis of this raw data collated from millions of sources is essential to derive value. But before that, there’s still a long way to go when it comes to widespread adoption. Yet, compared to other digital technologies, IoT is way ahead of the curve in terms of being adopted for day-to-day business operations.
Cognizant’s data indicates that 43% of the respondents from the study already have IoT implementations in place. Of the remaining, only 19% have no plans, with 38% either having pilot projects or are exploring adoption.
Comparatively, the widespread AI implementations stand at half (8%) of IoT, with 30% using it in some projects. Analytics is also behind, with 5% using it to a great extent and 30% using it in some projects, as is automation (8% widespread and 21% in some projects).
Who Are IoT Leaders?
In the report, Cognizant categorized those using IoT as leaders (43%) and those considering or have no plans as laggards (57%).
Five manufacturing-intensive industries viz., consumer goods, life sciences, manufacturing, oil & gas, and utilities make up over half (53%) of IoT leaders. The rationale being the push for smart manufacturing and digital augmentation under Industry 4.0.
At the same time, manufacturing-intensive companies are slow to adopt other digital technologies compared to those from non-manufacturing-intensive industries.
IoT leaders, Cognizant found, are usually larger companies with annual revenue of $500 million and more.
See Also: Top 6 Factors To Consider When Designing the IoT Infrastructure
How Have IoT Leaders Benefitted?
One of the biggest benefits of IoT for leaders is evident from them being largely remaining unaffected from the COVID-19 pandemic. Less than 40% of IoT leaders said the pandemic had a negative impact on business. On the other hand, 51% of IoT laggards said the pandemic had a negative impact.
The organizational agility of more than a quarter (26%) of IoT leaders improved. However, this number isn’t as significant as compared to IoT laggards, a whole 22% of which also noticed an improvement in operations.
More importantly, the data generated by IoT devices requires certain analysis for it to materially impact decision-making. To make data more meaningful and actionable, IoT has indirectly spurred companion digital technologies.
So much so that IoT leaders have adopted digital technologies such as AI, analytics, software bots, chatbots, and blockchain at a rate twice as high as laggards. The breakdown is given in the chart below:
Source: Cognizant
Why AI/ML?
Well, to replace human involvement in routine and redundant processes with machines. Additionally, AI/ML is proving to be a game-changer to take accurate decisions for complex tasks.
Currently, 19% of the work, the most prominent being sifting, by IoT leaders involves intelligent machines. IoT laggards’ machine adoption stands at 15%. This is expected to grow to 26% for leaders and 21% for laggards by 2023.
Machine vs. Human Involvement in Tasks | Source: Cognizant
Dataset sifting, or the determination of an ideal variable to perform a particular assessment, remains the most popular AI/ML use case for IoT data. The reason, according to an unnamed CMO who participated in Cognizant’s study, is accuracy. They said, “AI or analytics or bots or IoT cannot reach 100% of their potential if the key prerequisites working at the back end are not accurate. The higher the proportion of accurate data, the better the chances are of the right predictive model.”
Sifting is followed by decision-making, process improvement, etc.
Why ML is used with IoT | Source: Cognizant
Cognizant assessed that this divide is on the rise. “IoT laggards may soon find themselves in a situation of too little, too late with machine-learning adoption.”
Wrapping Up
Cognizant believes that even as IoT leaders are leaping ahead in terms of gaining a competitive edge, they’re still a long way off from fully becoming operationally, financially, technologically and culturally digital.
IoT certainly is key, but it is becoming evident that it is a stepping stone for companies to become fully digital. But the more important factor is that companion digital technologies can prove not to be as effective without IoT.
Note: Cognizant’s report is based on 4,000 respondents from 23 countries, working as C-suite and senior executives in 14 industries in organizations with a revenue of $250 million or more.
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