{"id":195538,"date":"2026-03-13T10:33:00","date_gmt":"2026-03-13T14:33:00","guid":{"rendered":"https:\/\/testing.news-you-need.com\/index.php\/2026\/03\/13\/arc-industry-forum-explored-artificial-intelligence-cybersecurity-and-more\/"},"modified":"2026-03-13T10:40:11","modified_gmt":"2026-03-13T14:40:11","slug":"arc-industry-forum-explored-artificial-intelligence-cybersecurity-and-more","status":"publish","type":"post","link":"https:\/\/testing.news-you-need.com\/index.php\/2026\/03\/13\/arc-industry-forum-explored-artificial-intelligence-cybersecurity-and-more\/","title":{"rendered":"ARC Industry Forum explored artificial intelligence, cybersecurity and more"},"content":{"rendered":"

ARC Industry Forum explored artificial intelligence, cybersecurity and more<\/a><\/p>\n

https:\/\/www.controlglobal.com\/industry-news\/news\/55363752\/arc-industry-forum-explored-artificial-intelligence-cybersecurity-and-more<\/a><\/p>\n

Publish Date: 2026-03-13 10:33:00<\/a><\/p>\n

Source Domain: www.controlglobal.com<\/a><\/p>\n

Author: <\/a><\/p>\n

Using an unordered list, summarize the following article with between 4 and 8 key points. Just like everywhere else lately, artificial intelligence (AI) was front and center at ARC Advisory Group\u2019s 30th annual Industry Leadership Forum on Feb. 9-12 at Renaissance Orlando Sea World. It consisted of more than 500 attendees from more than 280 companies attended presentations by more than 100 speakers in four tracks.
\nAs usual, the forum kicked off with the 14th annual edition of its traditional cybersecurity sessions organized by Sid Snitkin, ARC\u2019s VP and GM of enterprise services. Some cybersecurity strategies reported on by Snitkin, sponsor Fortinet, and the other speakers included enabling firewalls to perform deeper cyber-threat detections, as well as more granular network segmentation of equipment and other assets, which is called micro-segmentation. They also referenced virtual patching, which consists of addressing vulnerabilities in legacy devices without taking them out of operation, and using further segmentation to shroud them from exposure to possible cyber-attacks.
\nThe cybersecurity presenters also reemphasized that it\u2019s still crucial to gain management\u2019s buy-in and support, maintain cooperation between increasingly converged OT and IT staffs, and conduct ongoing training for personnel. They also reported that digital twins and other simulations can enable cybersecurity initiatives, and added that AI tools like Chat GPT have the potential to help, too, though most of those efforts are still in early, experimental stages.
\nCybersecurity panel
\nIn the first panel discussion, Lorena Nunes, OT cybersecurity specialist at petrochemical manufacturer Braskem, reported that machine learning (ML) functions have helped its intrusion detection system (IDS), and that it\u2019s mainly experimented with using ML for auditing and rule changes. \u201cIt\u2019s also using large language models (LLM) to find gaps in cybersecurity functions, and examines overall business directives to determine how and where AI might be useful,\u201d said Nunes. \u201cAI also may be able to speed up testing tasks, and allow users to respond faster.\u201d
\nDennis Hackney, OT cyber principal at Chevron, added that LLMs typically run at Level 4 and 5 of the Purdue Enterprise Reference Model for industrial control system (ICS) cybersecurity, so his company is using them for business plans and reports. \u201cWe also requires that all devices performing AI functions be registered,\u201d said Hackney. \u201cSo far, these include some vision inspection components, though AI may be able to help with cybersecurity by enabling compliance mapping.\u201d
\nIn a second cybersecurity discussion, Marty Martin, process control director at Air Liquide, reported the best starting point for secure remote access and cybersecurity assessments is writing down all the requirements that a process, facility or organization needs, listing the actions and tools that a proposed solution should provide, and using the results to evaluate proposals.
\nBrad Nash, IIT perimeter security at ExxonMobil, added his company already had many hardware and software-based operating systems, but growing demand for remote access is increasing its network connections. To know what\u2019s on its network or trying to access it, Nash reported that ExxonMobil\u2019s security operations center (SoC) documents all links with the outside world, and requires participants to explain why they want to connect, where they\u2019re from and other details.
\nJacob Partain, senior cybersecurity and process control engineer at BASF, reported his company uses a compliance-based strategy for cybersecurity risk assessment. In accordance with the IEC\/ISA 62443 cybersecurity standard, it examines its operations network infrastructure for vulnerabilities, firewall performance and any backdoors or other issues, and adds appropriate risk-based procedures and devices.\u00a0
\nAI expected to lighten data overloads
\nIn the forum\u2019s opening keynote on Feb. 10, Ashin Parikh, strategy and transformation SVP for global supply chain and operations at PepsiCo, reported its farm-to-table operations generate about 1 billion interactions daily, which require it to organize and manage about 15 petabytes of data. Parikh added that AI is assisting his company with this monumental task, making its operations more predictive, and helping it understand and react more quickly to market conditions. The four pillars where PepsiCo is applying AI tools include:<\/p>\n

Functional scope for operations that are compliant, safe, scalable, reusable, responsible and integrated by design.
\nMulti-agent framework to help the company progress toward a hybrid, human-and-AI workforce.
\nDigital twin 2.0 program that integrates a human- and society-based simulation engine.
\nGenerative AI (gen AI) infused robotics.<\/p>\n

\u201cAI will help transform our distribution centers and warehouse facilities by enabling them to process more data more quickly,\u201d said Parikh. \u201cIn fact, we\u2019re already collaborating with Nvidia and Siemens on an effort replicate some of these operations. They expect these digital twins to:<\/p>\n

Using intelligent vision cameras and other devices to find bottlenecks, save time, increase throughput by 19.4%, and avoid $4.5 million to $5 million in expansion costs\u2014for a total 25% reduction in capital costs at its warehouse in Grand Prairie, Texas.
\nIncrease utilization by 54% optimizing dock operations at its mixing center in Lancaster, Pa.
\nEnable the transition from six-door operations to full automation for 55 semitrailers per day at its Arizona-based loading facility, which is also expected to enhance safety, labor efficiency and scalability.
\nImprove design and construction of its warehouse and yard in Denver, and validate materials flows from its manufacturing and storage facilities.<\/p>\n

In the second keynote, Chase Christensen, VP and CIO for business units and enterprise solutions at Jabil, reported that considering and applying AI must start with the value it can bring to processes and organization\u2014and not just its technology. This is why Jabil established an AI steering committee to reduce obstacles, determine how to invest in generative AI (gen AI) and agentic AI, identify and resolve problems, bring along and augment its users, establish strong data governance, and harvest insights.
\n\u201cWe use AI to deliver real-time data value across our operations. This includes developing an intelligent procurement assistant tool for securing and delivering raw materials for our electronic circuit boards, mechanical and packaging products,\u201d said Christensen. \u201cThis assistant complements existing systems using LLMs because it gives users more options for working with their long-term data. For example, it used to be difficult to incorporate physics-based parameters into our mechanical intelligence solution, but AI lets it add schemas and algorithms that integrate this complex information more easily. Because our procurement assistant tool is embedded in existing systems, it puts control back in users\u2019 hands because they\u2019re supposed to be at the point where decisions are made. AI isn\u2019t about finding a place to deploy its technology\u2014it\u2019s about finding problems that AI can help solve.\u201d
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