Online learning: Why is it so hard to find expertise in IoT & AI?

Published: June 26, 2017 4:13 AM

Traditional learning avenues like schools and colleges haven’t kept pace. While many engineering colleges offer electives in IoT or AI as part of the curriculum, the course content is very basic.

Online learning, Internet of Things, Artificial Intelligence, technology, CEOs, entrepreneurs, young professionals, AI implementations, IT revolution, Google, Nvidia, Microsoft The reason for the lack of expertise is paucity of project work in India.

Nihal Kashinath

Internet of Things (IoT) and Artificial Intelligence (AI) have been two of the fastest growing fields of technology in recent history—in India and across the world. The potential they hold to transform business and economy has been capturing the attention of CEOs, entrepreneurs, young professionals and students alike. Over the last four years that we’ve been tracking this space, the use-cases and business-cases being explored have matured significantly, and in the last 18 months there has even been an uptick in the number of companies ready to make investments in exploratory efforts. Yet we don’t see many pilot projects going on in India.

There are many factors that have led to this situation. IoT and AI implementations are not always clearly understood in terms of goals and roadmaps—they need sizeable investment in infrastructure, technical resources and management bandwidth, they are high-visibility initiatives in most companies and hence require senior management to have a failure-tolerant mindset (Cisco estimates the failure rate to be around 75% for IoT projects, globally), require a long learning period, often need external consultants to guide them, etc. The brave companies that do the necessary planning and commit to the pilot project eventually come to face the biggest roadblock—the lack of talent in implementing these pilots.

IoT and AI are extremely multidisciplinary in nature and the technologies are evolving rapidly. It is hard to find individuals with the necessary combination of expertise, experience and domain understanding to build holistic teams. For example, implementing a pilot for predictive maintenance in a manufacturing plant requires expertise in (or at least familiarity with) multi-sensory systems, edge processing, radios for communication, networking protocols, power optimisation, cloud for device and data management, analytics specific to the equipment type and function, overall system architecture across hardware and software components, project management to bring it all of it together, etc. It’s definitely a challenge to recruit a team, given the scarcity of talent in the local ecosystem.

So, why is it so hard to find expertise? The lack of IoT and AI education plays a significant role in this. The more traditional learning avenues like schools and colleges haven’t kept pace. While many engineering colleges are today offering electives in IoT or AI as part of the curriculum, the course content is still very basic. We also don’t have equivalents of training institutes like NIITs and Aptechs that fuelled the IT revolution of the 1990s and 2000s. New-age online learning platforms like Coursera and Udemy have also not been able to get much traction among Indian developers, possibly because of learners’ limited access to hardware components or powerful processors that are often required for this, or even comprehensive courses designed to take learners from beginner to expert levels.

In a recent survey we conducted of 391 IoT and AI professionals, over 91% said they were interested in workshops on these topics. Small as that sample size may be, the unmet need here is obvious. This is not an easy gap to fill, but many industry leaders like Google, Nvidia and Microsoft are conducting events and workshops every month, often in collaboration with developer networks and communities.

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Education may be the first step, but a more serious contributor to the lack of expertise is the paucity of project work. Time and again, we have seen that substantial development of skills happens by getting hands-on with a new technology, figuring out the nuances, making mistakes and learning from them. Typically, this happens on the job. But given the lack of such opportunities in IoT and AI, it is important for learners to pick a project idea on their own, form teams of people with complementary skills (or at least interests), and work together on the implementation. Today, there are several local meetup groups and communities that can facilitate this. The important thing is to just get started.

At a systemic level, there are several other challenges like poor university-industry collaboration, lack of hardware development and manufacturing expertise, limited funding for deep tech start-ups, and more, which adversely affect opportunity creation in this space. While we are moving in the right direction on these, there’s a long way to go for many of them to get resolved. India has the potential to become the leader in IoT and AI development, but we need to address the talent shortage issue first, and fast.

The author is founder & CEO of Applied Singularity—a platform for IoT and AI professionals. He is an alumnus of the Indian School of Business and a TEDx speaker on the future of technology

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