Artificial intelligence (AI) is everywhere, touted as the next big thing. But while some AI innovations are revolutionizing industries, others are little more than misguided attempts at modernization. The real challenge lies in distinguishing opportunities with lasting market value from fleeting trends; investors risk missing out on AI applications that, though less flashy, are driving important changes in key sectors. Manoj Boopathi Raj, a Senior Software Engineer at Google and IEEE Senior Member, offers insights into where AI’s most powerful undercurrents are reshaping sectors—and some developments investors should be watching more closely.
AI in Telecom: Bolstering Performance & Resiliency
Despite projections that generative AI in telecom could reach $4.8 billion by 2033, the real transformation is happening in the quieter, unseen layers of mobile infrastructure and management.
Network performance optimization. When it works well, you hardly notice it. When it fails, companies scramble to meet their SLAs while customers are left confused and frustrated. By implementing machine learning at each stage of traffic management, service providers are finding ways to intelligently manage network resources, predicting and mitigating issues like congestion and latency before they affect users.
Boopathi Raj, speaking from his extensive experience launching America’s first eSIM mobile network, explains, “For telcos, increasing efficiency across a network in response to demand was once a problem best solved through labor-intensive manual work or the costly installation of fiber optics. Now, AI enables real-time adjustments based on hundreds of dynamic configurations. This is a much more proactive way to improve quality of service—not to mention the savings from cutting down on manual intervention.” Investors should consider telecom companies that are investing in AI-managed network operations, as these firms are likely to become mainstays in an increasingly mobile-oriented world.
Over $400 billion is lost to service failures annually, which is why the predictive maintenance of network infrastructure should be a forward-thinking service provider’s priority. By analyzing patterns in equipment performance and environmental factors, AI-driven health metrics can show when and where failures are likely to occur, allowing for preemptive maintenance. “Telecom failures are incredibly costly, the effects can cascade, and the downtime can be devastating for businesses,” says Boopathi Raj. “The money burned in recovery efforts could instead be spent on predictive maintenance. It improves the entire lifecycle of telecom assets in the long run.” Companies excelling in this area will offer investors steady returns as the global demand for reliable network and telecom services continues to climb.
AI in Automotive: Easing into the Automatic Revolution
While the initial excitement around autonomous vehicles has cooled, AI continues to be a catalyst for change in the automotive industry, focused instead on the incremental improvements laying the foundation for the future.
AI-enhanced driver assistance systems (ADAS) are showing wider adoption, providing features like adaptive cruise control (ACC), automated lane keeping systems (ALKS), and assisted parking. These systems rely on a combination of AI-powered sensor data fusion and advanced machine learning models to interpret data from the vehicle’s surroundings and assist drivers in making safer decisions.
With his industry-defining work on Android Automotive and familiarity with ADAS in leading OEMs, Boopathi Raj emphasizes the potential of these systems: “ADAS is a massive leap forward in vehicle safety and convenience—it’s not an exaggeration to say that some of these systems are digital airbags,” he says. “Unlike full autonomy, these systems reinforce safe driving in incremental ways, making them a great introduction to automative AI.” For investors, companies developing ADAS technologies are likely to see substantial growth as these systems become standardized features in new vehicles.
AI is also driving innovation in energy efficiency and battery management for electric vehicles (EVs). With states like California enforcing zero-emission vehicle sales, optimizing EV battery performance and energy consumption becomes increasingly important until the charging infrastructure catches up. Deep learning algorithms can take an individual’s driving patterns, local environmental conditions, and battery health, and create an optimized energy usage plan, extending the range and lifespan of EV batteries. “Short of an energy storage breakthrough, AI’s role in managing energy efficiency is crucial for the ongoing viability of Evs.
AI in Online Safety: Setting the Bar for Content Moderation
Legislation such as the Kids Online Safety Act (KOSA) is pushing even the top platforms to adopt robust safety measures for their digital communities. As creators become key drivers of media provider traffic, these regulations could have far-reaching effects on the bottom lines of other industries.
AI is at the forefront of content moderation, used to identify and remove harmful content. Boopathi Raj has firsthand experience in this area, having contributed to the development of YouTube’s spam classifier—a machine learning model designed to detect video content that breaks community guidelines. “Short-form videos dominate across all platforms, but moderating videos isn’t as straightforward as text,” explains Boopathi Raj. “The models must be sophisticated enough to understand context—whether a piece of content genuinely harms the platform’s integrity, or if it falls under satire or humor.”
The challenge is achieving high precision and consistency without excessive false positives, which could inadvertently censor legitimate—and profitable—content. With ad revenue amounting to more than $7 billion each quarter for YouTube alone, there’s little room for error or compromise.
More recently, AI is being put to the test in real-time content filtering. Platforms are relying on computer vision to monitor live-streams and concurrent video uploads, hoping to detect and flag inappropriate content before it goes live. While the results have been mixed, it’s proving to be necessary in a world dominated by influencers and the push towards authenticity and high-engagement media. “The underlying technology may differ, but the goal is very much the same: We want to mitigate PR crises and maintain platform integrity. Only AI can keep up.” Investors should make the distinction between companies specializing in pre-recorded versus live media, as effectively employing this technology will be crucial in sustaining trusted content platforms.
The Insider Perspective
As AI reshapes telecom, automotive, and online safety, investors may need to reconsider their portfolios. Insights from experts like Manoj Boopathi Raj suggest that the true value of AI emerges in the structural work happening behind the scenes. It’s time for investors to look beyond headlines and explore where AI is fostering long-term, industry-defining change.
