On November 13, industrial AI company IFS announced strategic partnerships with leading technology firms, including Anthropic, Boston Dynamics, Siemens, and 1X. This news marks an incredible advancement in the industrial AI space. Its emphasis on increasing operational efficiencies and integrating cutting-edge technologies into every aspect of operations is noteworthy. Just days later, on November 17, HCLTech opened another physical AI innovation lab, this time with global chip leader Nvidia. This step foregrounds the swiftly accelerating changes taking shape within the technological landscape of AI.
This lab in Santa Clara, California, is a crucial facility for businesses. It enables them to explore, incubate and scale applications of industry-focused physical AI and cognitive robotics. Powerful simulation tools, robotics, and edge-compute technologies are changing the game. This convergence brings the industrial AI revolution closer to the operations floor than ever before. As Guntur points out, these improvements make a big difference in lowering the rate of AI hallucinatory responses. This innovation shows potential for large scale deployment and application in industrial operations.
The Rise of Industrial AI
Industrial AI is finally at a point where the quality is proven to be acceptable for broad, large-scale implementation. Industrial AI has a much higher bar for accuracy since many of its use cases are mission-critical. White-collar enterprise AI of yore was forgiving of mistakes. This increased focus on precision is very important. Given that industrial automation already impacts nearly 70% of international workers, it illustrates how integral AI will be in our future workforce.
According to a report from Markets and Markets, the global AI market for industrial automation is expected to increase exponentially. It is projected to grow from $20.02 billion in 2024 to over $90.28 billion by 2033. That includes a CAGR of 18.6%. More than 60 percent of supply chain and warehousing executives surveyed say they’re already at advanced or fully automated maturity levels. This is a clear indicator that momentum for enterprise industrial AI adoption is accelerating at an exponential rate.
The recent partnerships announced by IFS are a strong indication of a forward looking mindset in this fast changing industry. By partnering with pioneering, deep tech companies such as Anthropic and Boston Dynamics, IFS is leading the way on innovation. That makes them well-poised to lead the industrial applications. Organizations, in turn, are compelled to innovate to remain competitive. This new push will almost certainly create a wave of new collaborations across the burgeoning industrial AI ecosystem.
Advancements in Edge Inference
One of the most striking industrial AI developments helping to drive adoption is the rapid drop in price for edge inference technologies. Over the last two years, the cost-per-inference at the edge has plummeted. It has gone down by an astounding four times to twenty times! This affordability makes it practical for a wider range of businesses to adopt edge AI tools within their workflow.
Edge inference allows us to process data at the source of the data generation. This on-device approach makes response times faster and reduces latency-related challenges typically associated with in-the-cloud processing. This ability becomes especially useful in manufacturing environments where quick, data-driven decisions are critical. Now that these edge technologies are more available and achievable than ever, organizations can tap into the potential to drive productivity and operational efficiency.
Combining physical AI with industrial shop floor environments presents enormous potential. As a result, it’s one of the most powerful tools available today for addressing our industries’ hardest, most complicated challenges. Together, HCLTech and Nvidia are working to harness the thrilling opportunities that lie ahead. Their innovation lab is focused on pushing the frontiers of cognitive robotics, forging an “infinite workforce.” That idea paints a picture of human workers and AI systems evolving together in teamwork to boost productivity well into the future.
Future Implications for Industrial Automation
IFS has consistently built deep collaborative partnerships, and HCLTech recently opened an IFS-focused innovation lab. These plays demonstrate a new current of making bigger bets on AI made specifically for industry. As enterprises embark on more sophisticated automation strategies, it will be increasingly critical for them to focus on the most advanced technologies that can help achieve their operational objectives.
The data released by MIT’s Center for Transportation and Logistics provides even more confirmation of this trend. The research reveals that an increasing majority of supply chain practitioners have reached advanced maturity levels. Some have gone as far as creating fully automated systems. Taken together, this data highlights just how widely automated solutions are starting to be accepted and implemented across sectors.
Sector-wide, industries are moving quickly to adapt to a digital transformation. This transition will be made possible through close collaboration between technology providers and end-users to build a resilient industrial automation landscape of the future. Pressure on these institutions to remain relevant and competitive in an ever-evolving climate requires innovative solutions and strategic collaborations.