{"689748":{"#nid":"689748","#data":{"type":"news","title":"Georgia Tech Research Shows East Coast Gateway Best Choice For Atlanta, Memphis And Nashville","body":[{"value":"\u003Cp\u003EA new study conducted by researchers with the \u003Ca href=\u0022https:\/\/www.scl.gatech.edu\u0022\u003EGeorgia Tech Supply Chain and Logistics Institute\u003C\/a\u003E shows that the \u003Ca href=\u0022https:\/\/gaports.com\/facilities\/port-of-savannah\/\u0022\u003EPort of Savannah\u003C\/a\u003E is the most cost-effective and reliable gateway for cargo destined for Atlanta, Memphis, and Nashville. According to the research, shippers can save more than $1,000 per container by routing freight through Savannah instead of West Coast ports, when evaluating full end-to-end supply chain costs and transit reliability.\u003C\/p\u003E\u003Cp\u003EThe study emphasizes that gateway decisions should not be based solely on ocean rates or sailing time. While trans-Pacific routes to the West Coast are shorter at sea, researchers found that congestion, cargo rehandling, and inland transportation complexity often introduce delays and variability. In contrast, Savannah\u0027s efficient port operations, on-terminal rail service, and direct interstate access help offset longer ocean voyages with faster inland movement and greater predictability.\u003C\/p\u003E\u003Cp\u003EResearchers analyzed vessel and inland transportation data from ten Asian ports to the three Southeastern markets. Their findings showed that Savannah\u0027s reliable port processing and inland logistics significantly reduce congestion exposure and transit variability, making it a more dependable gateway for shippers seeking consistent delivery performance.\u003C\/p\u003E\u003Cp\u003EThe study was conducted by Georgia Tech faculty and PhD students at the Institute\u0027s \u003Ca href=\u0022https:\/\/picenter.gatech.edu\u0022\u003EPhysical Internet Center\u003C\/a\u003E and reinforces previous Atlanta-focused research demonstrating similar benefits of East Coast routing. The findings support the growing role of the Port of Savannah as a strategic gateway for U.S. supply chains serving inland Southeast markets.\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003ERead the original press release from the Georgia Ports Authority here:\u003C\/em\u003E\u003Cbr\u003E\u003Ca href=\u0022https:\/\/gaports.com\/press-releases\/georgia-tech-research-shows-east-coast-gateway-best-choice-for-atlanta-memphis-and-nashville\/\u0022\u003EGeorgia Tech research shows East Coast gateway best choice for Atlanta, Memphis and Nashville\u003C\/a\u003E\u003Cbr\u003E\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Tech researchers have found that routing cargo through the Port of Savannah offers significant cost savings and more reliable transit for shipments bound for Atlanta, Memphis, and Nashville, outperforming traditional West Coast gateways in total landed cost and consistency.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Independent study shows Savannah saves shippers $1,000 per container compared to West Coast ports."}],"uid":"27233","created_gmt":"2026-04-14 18:02:30","changed_gmt":"2026-04-14 18:11:05","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Savannah, GA","dateline":{"date":"2026-04-09T00:00:00-04:00","iso_date":"2026-04-09T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"679945":{"id":"679945","type":"image","title":"Georgia Tech Research Shows East Coast Gateway Best Choice For Atlanta, Memphis And Nashville","body":null,"created":"1776188877","gmt_created":"2026-04-14 17:47:57","changed":"1776189100","gmt_changed":"2026-04-14 17:51:40","alt":"Railroad yard serving the Georgia Ports Authority with more than 6 railroad lanes with one engine towing a long line of intermodal containers.","file":{"fid":"264170","name":"260409-GPA-GA-Tech-Study-.jpg","image_path":"\/sites\/default\/files\/2026\/04\/14\/260409-GPA-GA-Tech-Study-.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/04\/14\/260409-GPA-GA-Tech-Study-.jpg","mime":"image\/jpeg","size":541590,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/04\/14\/260409-GPA-GA-Tech-Study-.jpg?itok=RnLPxWpp"}}},"media_ids":["679945"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/news\/scl-study-shows-savannah-beats-west-coast-cost-reliability-atlanta-cargo","title":"SCL Study Shows Savannah Beats West Coast on Cost, Reliability for Atlanta Cargo"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[{"id":"142","name":"City Planning, Transportation, and Urban Growth"},{"id":"194609","name":"Industry"}],"keywords":[{"id":"194848","name":"shipping costs"}],"core_research_areas":[{"id":"39461","name":"Manufacturing, Trade, and Logistics"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Einfo@scl.gatech.edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"689606":{"#nid":"689606","#data":{"type":"news","title":"SCL Managing Director Chris Gaffney Featured in Atlanta News First on Rising Fuel and Supply Chain Costs","body":[{"value":"\u003Cp\u003EChris Gaffney, Managing Director of the Georgia Tech Supply Chain and Logistics Institute (SCL), was featured in a recent Atlanta News First segment examining how a potential conflict involving Iran could impact fuel prices and broader transportation costs.\u003C\/p\u003E\u003Cp\u003EDrawing on his expertise in supply chain economics and transportation systems, Gaffney discussed how disruptions in global energy markets can ripple through logistics networks, ultimately affecting consumers and businesses across Georgia and the Southeast.\u003C\/p\u003E\u003Cp\u003ERead the full Atlanta News First article and watch the related video: \u003Ca href=\u0022https:\/\/www.atlantanewsfirst.com\/2026\/04\/08\/experts-warn-war-with-iran-could-raise-costs-georgia-fuel-prices-leading-way\/\u0022\u003EExperts Warn War With Iran Could Raise Costs, Georgia Fuel Prices Leading the Way\u003C\/a\u003E\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ESCL Managing Director Chris Gaffney provides expert insight on how geopolitical tensions could affect fuel prices and supply chains in Georgia and beyond.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"SCL Managing Director Chris Gaffney provides expert insight on how geopolitical tensions could affect fuel prices and supply chains in Georgia and beyond."}],"uid":"27233","created_gmt":"2026-04-10 12:54:26","changed_gmt":"2026-04-10 13:14:32","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2026-04-10T00:00:00-04:00","iso_date":"2026-04-10T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"679910":{"id":"679910","type":"image","title":"Chris Gaffney Featured in Atlanta News First on Rising Fuel and Supply Chain Costs","body":null,"created":"1775826586","gmt_created":"2026-04-10 13:09:46","changed":"1775826724","gmt_changed":"2026-04-10 13:12:04","alt":"Chris Gaffney on right being interviewed by Abby Kousouris on left from Atlanta News First in an outside setting on the Georgia Tech campus.","file":{"fid":"264131","name":"ChrisANF_20260407.jpg","image_path":"\/sites\/default\/files\/2026\/04\/10\/ChrisANF_20260407.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/04\/10\/ChrisANF_20260407.jpg","mime":"image\/jpeg","size":180265,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/04\/10\/ChrisANF_20260407.jpg?itok=bNd0MYh6"}}},"media_ids":["679910"],"related_links":[{"url":"https:\/\/www.atlantanewsfirst.com\/2026\/04\/08\/experts-warn-war-with-iran-could-raise-costs-georgia-fuel-prices-leading-way\/","title":"Read the related article at Atlanta News First"}],"groups":[{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[{"id":"144","name":"Energy"},{"id":"194610","name":"National Interests\/National Security"}],"keywords":[],"core_research_areas":[{"id":"39461","name":"Manufacturing, Trade, and Logistics"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Einfo@scl.gatech.edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"689495":{"#nid":"689495","#data":{"type":"news","title":"ISyE Graduate Program Maintains Top Ranking for 36th Consecutive Year","body":[{"value":"\u003Cdiv\u003E\u003Cp\u003EFor the 36th year in a row, Georgia Tech\u2019s \u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/\u0022\u003EH. Milton Stewart School of Industrial and Systems Engineering\u003C\/a\u003E (ISyE) has earned the No. 1 spot in the 2026 Best Engineering Schools ranking released by \u003Cem\u003EU.S. News \u0026amp; World Report.\u003C\/em\u003E \u0026nbsp;\u0026nbsp;\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u201cThis continued recognition reflects the exceptional work of our faculty and staff, students, and alumni, who are pushing the boundaries of industrial and systems engineering every day,\u201d said \u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/users\/pinar-keskinocak\u0022\u003EP\u0131nar Keskinocak\u003C\/a\u003E, H. Milton and Carolyn J. Stewart School Chair and Professor.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u201cBeing ranked No. 1 for 36 consecutive years highlights the strength of our community and our commitment to innovation, impact, and leadership in the field.\u201d\u0026nbsp;\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003EGeorgia Tech\u2019s College of Engineering (COE) also maintained its strong national standing, placing fourth overall for the third consecutive year. In addition, all 11 of the Institute\u2019s graduate engineering programs have ranked within the top 9 in their respective disciplines for the 12th straight year in the 2026 \u003Cem\u003EU.S. News \u0026amp; World Report \u003C\/em\u003Erankings.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003EExplore the full list of COE program rankings \u003Ca href=\u0022https:\/\/coe.gatech.edu\/news\/2026\/04\/engineering-grad-programs-remain-no-4-2026-rankings\u0022 rel=\u0022noreferrer noopener\u0022 target=\u0022_blank\u0022\u003Ehere\u003C\/a\u003E.\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\u003C\/div\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Tech\u2019s \u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/\u0022\u003EH. Milton Stewart School of Industrial and Systems Engineering\u003C\/a\u003E (ISyE) continues to set the standard for excellence, with its graduate program earning the No. 1 ranking for the 36th consecutive year by \u003Cem\u003EU.S. News \u0026amp; World Report. \u003C\/em\u003EThis sustained leadership reflects ISyE\u2019s unwavering commitment to innovation, rigorous academic training, and impactful research that addresses some of the world\u2019s most complex challenges.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"ISyE\u2019s graduate program continues to lead the nation, earning the No. 1 ranking for the 36th consecutive year and reinforcing its position at the forefront of industrial and systems engineering."}],"uid":"36736","created_gmt":"2026-04-07 16:37:01","changed_gmt":"2026-04-08 16:28:46","author":"ebrown386","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2026-04-07T00:00:00-04:00","iso_date":"2026-04-07T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"679875":{"id":"679875","type":"image","title":"2026 USNWR.png","body":null,"created":"1775579829","gmt_created":"2026-04-07 16:37:09","changed":"1775579829","gmt_changed":"2026-04-07 16:37:09","alt":"2026 USNWR","file":{"fid":"264095","name":"Rankings_2026--1080-x-1080-px---3-.png","image_path":"\/sites\/default\/files\/2026\/04\/07\/Rankings_2026--1080-x-1080-px---3-.png","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/04\/07\/Rankings_2026--1080-x-1080-px---3-.png","mime":"image\/png","size":160890,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/04\/07\/Rankings_2026--1080-x-1080-px---3-.png?itok=wMPXLVpf"}}},"media_ids":["679875"],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[{"id":"145","name":"Engineering"}],"keywords":[],"core_research_areas":[{"id":"39541","name":"Systems"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"689229":{"#nid":"689229","#data":{"type":"news","title":"ISyE Student Awarded IBM Fellowship for Research Excellence","body":[{"value":"\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/users\/hoang-nguyen\u0022\u003EHoang Nguyen\u003C\/a\u003E, a graduate student in the Algorithms, Combinatorics, and Optimization Ph.D. program at the\u0026nbsp;\u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/\u0022\u003EH. Milton Stewart School of Industrial and Systems Engineering\u003C\/a\u003E, has been awarded an IBM fellowship in recognition of his research contributions and academic achievements. The IBM fellowship program is a prestigious, invitation-only award that identifies exceptional Ph.D. students conducting pioneering research in their disciplines.\u003C\/p\u003E\u003Cp\u003ENguyen began his academic journey as an undergraduate at Minerva University, where he studied in a different country nearly every semester. This experience abroad shaped his approach to problem-solving. After graduating, Nguyen remained passionate about mathematics but became interested in applying theory to real-world challenges.\u003C\/p\u003E\u003Cp\u003E\u201cI still wanted to do math, but I wanted to apply my mathematical research to some tangible applications,\u201d Nguyen said. \u201cI wanted to see the meaning behind my research.\u201d\u003C\/p\u003E\u003Cp\u003EThat desire, along with ISyE\u2019s long-standing top national ranking in industrial engineering, led Nguyen to pursue his doctoral studies at Georgia Tech. His primary research focuses on applied probability, with an emphasis on bridging theoretical models and practical systems.\u003C\/p\u003E\u003Cp\u003ENguyen received the IBM Fellowship in recognition of his ongoing research. One of his current research projects examines how far a process is from the steady state and seeks to better understand the finite-time behavior of the system and to make accurate real-time decisions. This work has meaningful applications in many real-world service systems models, such as the load balancing algorithms found in data centers and ride-hailing systems.\u003C\/p\u003E\u003Cp\u003EIn additional his work in applied probability, Nguyen is exploring ways to improve artificial intelligence reasoning. His research investigates how large language models can verify their own outputs using mathematical heuristics and training data. By identifying and correcting discrepancies before displaying results to the user, the system could become more accurate and reliable.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003ENguyen contributes much to the mentorship of his advisor, Professor\u0026nbsp;\u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/users\/siva-theja-maguluri\u0022\u003ESiva Theja Magulur\u003C\/a\u003E.\u003C\/p\u003E\u003Cp\u003E\u201cI would like to thank my advisor, Professor Siva Theja, for supporting me through this journey,\u201d he said. \u201cHe\u0027s an extremely caring, insightful, and attentive professor. He\u0027s also very supportive of me pursuing the AI reasoning research at Google DeepMind, although this is not his main research. Over the years, I have learned a lot from him as his student.\u201d\u003C\/p\u003E\u003Cp\u003EThe IBM Fellowship is the latest in a series of achievements for Nguyen. In 2024 and 2025, respectively, he was part of a Google DeepMind team that earned silver and gold medals in the International Mathematical Olympiad. He also won second place at the ACM SIGMETRICS 2025 Student Research Contest for his work on the finite-time behavior of queuing systems.\u003C\/p\u003E\u003Cp\u003EAs he continues his doctoral studies, Nguyen remains focused on advancing his research and contributing to both theoretical and applied fields.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ENguyen\u0027s work focuses on understanding real-world system behavior, such as queuing and load balancing, while also advancing methods for improving AI reasoning, building more reliable and effective technologies with practical applications.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Hoang Nguyen, a Ph.D. student at the H. Milton Stewart School of Industrial and Systems Engineering, has earned an IBM Fellowship for his innovative research in applied probability and AI, advancing real-world systems and intelligent technologies."}],"uid":"36736","created_gmt":"2026-03-30 13:26:44","changed_gmt":"2026-03-31 16:05:20","author":"ebrown386","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2026-03-30T00:00:00-04:00","iso_date":"2026-03-30T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"679770":{"id":"679770","type":"image","title":"Hoang Nguyen.jpg","body":null,"created":"1774877220","gmt_created":"2026-03-30 13:27:00","changed":"1774877220","gmt_changed":"2026-03-30 13:27:00","alt":"Hoang Nguyen","file":{"fid":"263971","name":"Hoang-Nguyen.jpg","image_path":"\/sites\/default\/files\/2026\/03\/30\/Hoang-Nguyen.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/03\/30\/Hoang-Nguyen.jpg","mime":"image\/jpeg","size":45371,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/03\/30\/Hoang-Nguyen.jpg?itok=jlrk7h12"}}},"media_ids":["679770"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[{"id":"145","name":"Engineering"}],"keywords":[],"core_research_areas":[{"id":"39541","name":"Systems"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EParker Avery, Student Writing Assistant\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"689150":{"#nid":"689150","#data":{"type":"news","title":"The Future of Brand in an AI-Driven World: A Supply Chain Perspective","body":[{"value":"\u003Cp\u003E\u003Cem\u003EBy Chris Gaffney, Managing Director of the Georgia Tech Supply Chain and Logistics Institute, Supply Chain Advisor, and former executive at Frito\u2011Lay, AJC International, and Coca\u2011Cola\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003EWe recently wrapped our semi\u2011annual industry advisory board meeting, where a core element of the agenda is a set of \u0022hot topics\u0022 sourced in advance from our member companies, curated, and facilitated to reflect what is most top of mind in the field. This cycle, one of those topics focused on the impact of AI on supply chain technology investment.\u003C\/p\u003E\u003Cp\u003EWhat began as a discussion on technology quickly surfaced a broader issue:\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAI is not just changing supply chains\u2014it is raising the standard for execution, and in doing so, redefining what it takes to sustain a brand.\u003C\/strong\u003E\u003C\/p\u003E\u003Ch2\u003EWhen Capability Becomes Cheap\u003C\/h2\u003E\u003Cp\u003EWithin that discussion, a simple example sparked debate. Most of us would trust a platform like DocuSign without hesitation. It has earned that trust through reliability, security, and consistent performance.\u003C\/p\u003E\u003Cp\u003EBut what if a new entrant\u2014call it \u201cFredSign\u201d\u2014offered similar functionality, powered by AI, at lower cost and with comparable features? Would you use it?\u003C\/p\u003E\u003Cp\u003EThe room split. Some argued that established brands are durable because of the trust they have built over time. Others pushed back, suggesting that AI\u2011enabled challengers could close that gap faster than expected, making brand less relevant.\u003C\/p\u003E\u003Cp\u003EThe discussion quickly moved beyond software to a broader question:\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003EIn a world where AI lowers the cost of building capability, does trust shift from brand to performance\u2014or does brand become even more important?\u003C\/em\u003E\u003C\/p\u003E\u003Ch2\u003EBrand as a Promise\u003C\/h2\u003E\u003Cp\u003EFrom a supply chain perspective, this is no longer theoretical. It is already happening.\u003C\/p\u003E\u003Cp\u003EAt its core, a brand is a promise. For product companies, that promise is built on quality, consistency, and the experience of using the product over time. For supply chain technology and service providers, it is grounded in reliability, security, and confidence in execution.\u003C\/p\u003E\u003Cp\u003EHistorically, brand has been reinforced by performance\u2014but also protected by time, scale, and familiarity.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAI is changing that balance.\u003C\/strong\u003E\u003C\/p\u003E\u003Ch2\u003ELower Barriers, Higher Expectations\u003C\/h2\u003E\u003Cp\u003EOn one hand, AI lowers barriers to entry. New entrants can replicate functionality faster, improve user experiences, and target specific gaps in incumbent offerings.\u003C\/p\u003E\u003Cp\u003EIn supply chain technology, this is particularly relevant. Many organizations have made significant, long\u2011term investments in systems that have not always delivered as expected. That creates an opening for AI\u2011enabled providers to enter through narrow use cases, solve specific problems better, and establish a foothold. Over time, they build credibility.\u003C\/p\u003E\u003Cp\u003EBut there is a second dimension that is more immediate\u2014and more consequential.\u003C\/p\u003E\u003Ch2\u003EAI Raises the Execution Standard\u003C\/h2\u003E\u003Cp\u003EOne way to frame this is simple: data is a terrible thing to waste.\u003C\/p\u003E\u003Cp\u003EFor years, supply chains have generated vast amounts of data across planning systems, transportation networks, warehouses, and customer interactions. Much of that data has been underutilized\u2014captured, stored, but not fully leveraged to anticipate risk or improve outcomes.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EThat is changing.\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EThe capability now exists\u2014and is rapidly maturing\u2014to sense, interpret, and act on that data in ways that were not previously practical. Risks can be identified earlier. Disruptions can be predicted. Corrective actions can be taken before the customer ever feels the impact.\u003C\/p\u003E\u003Ch2\u003EFrom Disruption to Preventability\u003C\/h2\u003E\u003Cp\u003EOver the past week, in the span of just six days and four unrelated conversations with members of my network, I heard a series of examples that all pointed to this shift.\u003C\/p\u003E\u003Cul\u003E\u003Cli\u003EA global food company managing risk tied to a critical supplier whose quality issues could impact multiple major brands\u2014raising the question of whether AI could have surfaced a near sole\u2011source dependency earlier.\u003C\/li\u003E\u003Cli\u003EAn e\u2011commerce retailer using machine learning to reduce theft and damage in its fulfillment network, improving the customer experience.\u003C\/li\u003E\u003Cli\u003EAn organization proactively shifting its fulfillment partner mix based on AI\u2011driven insights into which nodes can and cannot handle surge capacity.\u003C\/li\u003E\u003Cli\u003EA high\u2011end clothing shipment arriving wet due to a fulfillment breakdown\u2014where the loss was not just the product, but a time\u2011sensitive moment that could not be recovered.\u003C\/li\u003E\u003Cli\u003EA consumer receiving an empty box after successfully purchasing a limited\u2011release product that could not be replaced.\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003EThese are not isolated anecdotes. The common thread is not disruption\u2014it is preventability.\u003C\/p\u003E\u003Cp\u003EAs AI enables earlier detection of risk, better prediction of disruptions, and faster response to exceptions, the tolerance for failure is declining. Companies are no longer judged simply on whether something went wrong. They are judged on whether it should have been avoided.\u003C\/p\u003E\u003Ch2\u003EBrand Is the Delivered Experience\u003C\/h2\u003E\u003Cp\u003EFrom a brand perspective, that is a fundamental shift.\u003C\/p\u003E\u003Cp\u003EA product brand may invest heavily in innovation and customer engagement. But if the product arrives damaged, late, or not at all, the customer does not distinguish between the brand owner and the supply chain behind it.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EThere is only one experience\u2014and therefore only one brand.\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EIn an AI\u2011enabled supply chain, failure is no longer just a risk\u2014it is increasingly a choice.\u003C\/strong\u003E\u003C\/p\u003E\u003Ch2\u003EThe Weakest Node Defines the Brand\u003C\/h2\u003E\u003Cp\u003EA brand is now only as strong as its weakest node.\u003C\/p\u003E\u003Cp\u003EThat node may be a supplier, a logistics provider, a fulfillment partner, or a technology platform. Many sit outside the direct control of the brand owner, yet their performance is inseparable from the customer\u2019s perception of the brand.\u003C\/p\u003E\u003Cp\u003EAI makes it possible to identify and address these weak points\u2014but it also makes it more apparent when companies fail to do so.\u003C\/p\u003E\u003Ch2\u003EImplications for the Supply Chain Ecosystem\u003C\/h2\u003E\u003Cp\u003EThis dynamic extends directly to platform and software providers. In an AI\u2011enabled environment, it is no longer sufficient for supply chain technology to be stable or functionally adequate. It must evolve\u2014continuously\u2014to sense risk earlier, enable better decisions, and improve execution outcomes. If it does not, its limitations will be exposed quickly, and alternatives will emerge.\u003C\/p\u003E\u003Cp\u003ETechnology providers are not insulated by their brand; they are judged by the outcomes they enable. Their brand will strengthen if their platforms improve execution\u2014and erode if they do not.\u003C\/p\u003E\u003Cp\u003EProduct companies must use AI to protect the customer experience end\u2011to\u2011end. Logistics providers must adopt AI to remain credible partners. Technology providers must evolve their platforms to meet a higher execution standard.\u003C\/p\u003E\u003Cp\u003EIf one part of the system advances while another does not, the gap will be visible\u2014and acted upon quickly.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EWinners and losers are being judged daily.\u003C\/strong\u003E\u003C\/p\u003E\u003Ch2\u003EWhat This Means for Leaders\u003C\/h2\u003E\u003Cp\u003ENone of this suggests that brand is no longer important. In high\u2011trust, high\u2011risk environments\u2014contracts, financial transactions, healthcare, and other sensitive use cases\u2014brand remains critical.\u003C\/p\u003E\u003Cp\u003EEven in this environment, trust must be continuously reinforced through performance. Leaders must clearly understand what underpins their brand. Brand is not an asset to be protected; it is the result of consistently delivering on a promise. Any performance gaps must be addressed before others move in. AI\u2011enabled challengers will not challenge strengths\u2014they will target weaknesses.\u003C\/p\u003E\u003Cp\u003EFinally, leaders must elevate their ecosystem. Brand performance is now inseparable from partner performance. That requires greater visibility, tighter integration, and higher expectations\u2014not only internally, but across suppliers, logistics providers, and technology partners.\u003C\/p\u003E\u003Ch2\u003EOne Question to Answer Now\u003C\/h2\u003E\u003Cp\u003EThis execution dimension is only one part of how AI is reshaping brand\u2014but it is already decisive.\u003C\/p\u003E\u003Cp\u003EA great product can still win. A strong brand can still endure. But in an AI\u2011driven world, where disruptions can be anticipated and failures mitigated, the margin for error is disappearing.\u003C\/p\u003E\u003Cp\u003EAnd in many cases\u2014especially where the purchase is infrequent or the moment is critical\u2014you only get one shot. At the conclusion of our discussion, one participant framed it simply:\u003C\/p\u003E\u003Cblockquote\u003E\u003Cp\u003EWhat is our secret sauce\u2014and what are we doing to build on it?\u003C\/p\u003E\u003C\/blockquote\u003E\u003Cp\u003EThat is the question every supply chain leader should be answering now.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBecause in an AI\u2011enabled world, your brand will be defined by what your system consistently delivers.\u003C\/strong\u003E\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EAI is transforming supply chains by lowering the cost of building capability and raising execution standards, which forces brands to rely more on consistent performance rather than just historical trust. In this new landscape, a brand\u2019s promise is inseparable from its supply chain\u0027s reliability, as AI-driven data makes operational failures increasingly preventable and less tolerable for customers.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Practical guidance to drive real progress in 2026."}],"uid":"27233","created_gmt":"2026-03-24 14:57:25","changed_gmt":"2026-03-24 19:00:46","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2026-03-24T00:00:00-04:00","iso_date":"2026-03-24T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"679724":{"id":"679724","type":"image","title":"The Future of Brand in an AI-Driven World: A Supply Chain Perspective","body":null,"created":"1774372889","gmt_created":"2026-03-24 17:21:29","changed":"1774372889","gmt_changed":"2026-03-24 17:21:29","alt":"A split-panel conceptual infographic asks a central question: \u0022IN A WORLD OF LOWERED CAPABILITY COSTS, WHERE DOES TRUST LIE: BRAND OR PERFORMANCE?\u0022 The left side, \u0022THE BRAND DIMENSION,\u0022 features a glowing shield on a pedestal with an \u0027X\u0027 logo and lists traits like \u0022TRUST\u0022 and \u0022HERITAGE.\u0022 The right side, \u0022THE PERFORMANCE DIMENSION,\u0022 displays a holographic data interface with metrics like \u0022EXECUTION,\u0022 \u0022RELIABILITY,\u0022 and \u0022PREDICTABILITY.","file":{"fid":"263916","name":"20260324_FutureOfBrandInAnAI-DrivenWorld.jpg","image_path":"\/sites\/default\/files\/2026\/03\/24\/20260324_FutureOfBrandInAnAI-DrivenWorld.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/03\/24\/20260324_FutureOfBrandInAnAI-DrivenWorld.jpg","mime":"image\/jpeg","size":444486,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/03\/24\/20260324_FutureOfBrandInAnAI-DrivenWorld.jpg?itok=DBEaOCed"}},"674087":{"id":"674087","type":"image","title":"Chris Gaffney","body":"\u003Cp\u003EChris Gaffney\u003C\/p\u003E","created":"1717067903","gmt_created":"2024-05-30 11:18:23","changed":"1771883375","gmt_changed":"2026-02-23 21:49:35","alt":"Chris Gaffney, Managing Director, Georgia Tech Supply Chain and Logistics Institute","file":{"fid":"257557","name":"chris-gaffney_scl.jpg","image_path":"\/sites\/default\/files\/2024\/05\/30\/chris-gaffney_scl.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2024\/05\/30\/chris-gaffney_scl.jpg","mime":"image\/jpeg","size":129544,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2024\/05\/30\/chris-gaffney_scl.jpg?itok=_M0fOBTF"}}},"media_ids":["679724","674087"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/news-events\/newsletters","title":"View past SCL newsletters and join our mailing list"},{"url":"https:\/\/www.scl.gatech.edu\/","title":"Georgia Tech Supply Chain and Logistics Institute"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[{"id":"194606","name":"Artificial Intelligence"},{"id":"42911","name":"Education"},{"id":"145","name":"Engineering"}],"keywords":[{"id":"2556","name":"artificial intelligence"},{"id":"194489","name":"scl-spot"},{"id":"167074","name":"Supply Chain"},{"id":"187190","name":"-go-gtmi"}],"core_research_areas":[{"id":"39461","name":"Manufacturing, Trade, and Logistics"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":["info@scl.gatech.edu"],"slides":[],"orientation":[],"userdata":""}},"685211":{"#nid":"685211","#data":{"type":"news","title":"If I Were Starting My Supply Chain Career Today, Here\u2019s How I\u2019d Learn GenAI","body":[{"value":"\u003Cp\u003E\u003Cem\u003EBy Chris Gaffney, Managing Director, Georgia Tech Supply Chain and Logistics Institute | Supply Chain Advisor | Former Executive at Frito-Lay, AJC International, and Coca-Cola\u003C\/em\u003E\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EIntroduction\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThis year has felt like a lifetime in the Generative AI (GenAI) world. Tools, capabilities, and best practices are shifting monthly, sometimes weekly. For supply chain professionals, the message is clear: ongoing development is not optional. Like lean, analytics, or S\u0026amp;OP in prior decades, GenAI proficiency is quickly becoming a differentiator. The question is not if you\u2019ll integrate GenAI into your workflow, but how quickly and effectively.\u0026nbsp;\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EThe Evolution of GenAI in 2025\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EWhen we look back to January, it\u2019s striking how much progress has been made in less than a year. Early in 2025, the conversation centered on \u003Cstrong\u003Eagentic AI\u003C\/strong\u003E and \u003Cstrong\u003Elarger models\u003C\/strong\u003E. GPT-5 and Claude 4 improved reasoning and context windows, while OpenAI introduced ChatGPT Agent in preview, able to carry out bounded multi-step tasks like retrieving files, browsing the web, and drafting structured outputs. In supply chain, this translated into early experiments with automating shipment steps or running contract reviews in a single query \u2014 tasks that were pilot-level at best in January.\u003C\/p\u003E\u003Cp\u003EBy mid-year, \u003Cstrong\u003Emultimodal capabilities\u003C\/strong\u003E and \u003Cstrong\u003Eenterprise copilots\u003C\/strong\u003E began shifting from concept to daily use. Users could combine text, image, and voice inputs to detect defects or summarize complex documents, and copilots became embedded inside SAP, Oracle, Microsoft, and Google platforms. For the first time, GenAI wasn\u2019t just a tool \u0022off to the side\u0022 but something integrated directly into the systems supply chain professionals rely on.\u003C\/p\u003E\u003Cp\u003EIn the second half of the year, new capabilities started layering on: memory, specialized small models, and synthetic data with digital twins. Memory allowed copilots to recall context from prior chats or S\u0026amp;OP cycles, reducing rework. Domain-tuned models made GenAI lighter, cheaper, and faster for logistics, procurement, and planning tasks. And digital twin integration allowed organizations to stress-test networks under disruption scenarios, from weather to labor shortages.\u003C\/p\u003E\u003Cp\u003EEnterprises also moved closer to operations with \u003Cstrong\u003EAI at the edge\u003C\/strong\u003E, using IoT data for predictive maintenance or real-time routing. At the same time, \u003Cstrong\u003Eguardrails and compliance\u003C\/strong\u003E became a central topic, with more organizations creating clear \u0022green\/yellow\/red\u0022 tiers for safe use. And in Q4,\u003Cstrong\u003E collaboration AI\u003C\/strong\u003E and \u003Cstrong\u003Ehybrid architectures\u003C\/strong\u003E came to the forefront \u2014 copilots that can negotiate contracts in multiple languages, and architectures that blend closed and open-source models to balance sovereignty, cost, and security.\u003C\/p\u003E\u003Cp\u003EFor \u003Cstrong\u003Emainstream individual users\u003C\/strong\u003E, the picture is simpler but still powerful. Anyone with ChatGPT Plus or Copilot today can take advantage of:\u003C\/p\u003E\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EMemory and custom instructions\u003C\/strong\u003E to save preferences and formats across sessions.\u003C\/li\u003E\u003Cli\u003E\u003Cstrong\u003EProject-only memory\u003C\/strong\u003E (rolling out) to organize work by context.\u003C\/li\u003E\u003Cli\u003E\u003Cstrong\u003EAgent previews\u003C\/strong\u003E like Operator to see how automation might work on bounded tasks.\u003C\/li\u003E\u003Cli\u003E\u003Cstrong\u003EConnectors and file uploads\u003C\/strong\u003E to bring internal data into conversations.\u0026nbsp;\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003EFor \u003Cstrong\u003Eleaders\u003C\/strong\u003E, the focus is on policy, safe pilots, and scaling. They are:\u003C\/p\u003E\u003Cul\u003E\u003Cli\u003ESponsoring agent experiments in low-risk domains (like supplier alerts).\u003C\/li\u003E\u003Cli\u003EEmbedding copilots in enterprise systems for daily planning and reporting.\u003C\/li\u003E\u003Cli\u003EFormalizing AI use policies so employees know what\u2019s encouraged, conditional, and off-limits.\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003EThe net result: what started in January as experimentation has, by October, become a layered landscape. Individual users now have practical tools to reclaim time, while leaders are piloting more ambitious integrations and building the governance to make adoption sustainable.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003E1. Action Planning is Critical\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThe pace of change makes a one-and-done training activity insufficient. Think of GenAI skills like fitness: it requires steady reps over time. Professionals who set quarterly development goals \u2014 experimenting with new tools, building prompt libraries, testing workflows \u2014 will not only stay current but pull ahead.\u003C\/p\u003E\u003Cdiv\u003E\u003Cp\u003E\u003Cimg src=\u0022https:\/\/www.scl.gatech.edu\/sites\/default\/files\/news\/2025-09\/figure1-QtrlyGenAI_dvlpt_cycle.jpg\u0022 alt=\u0022Quarterly GenAI Development Cycle table\u0022\u003E\u003C\/p\u003E\u003C\/div\u003E\u003Cp\u003E\ud83d\udca1 Try This Quarter:\u003C\/p\u003E\u003Cul\u003E\u003Cli\u003EBuild a custom prompt library for routine tasks (e.g., supplier follow-ups, KPI summaries).\u003C\/li\u003E\u003Cli\u003ETest one open-source tool such as LangChain or Haystack.\u003C\/li\u003E\u003Cli\u003EUse AI to summarize two recent meetings and validate output with your notes.\u0026nbsp;\u003C\/li\u003E\u003C\/ul\u003E\u003Ch3\u003E\u003Cstrong\u003E2. Prompt Maturity is the New Literacy\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EI\u2019ve personally learned the most about prompting by asking ChatGPT to critique my style against a 12-step framework. The feedback gave me a process improvement plan I still use today. Prompt maturity isn\u2019t abstract \u2014 it\u2019s a measurable, improvable skill.\u003C\/p\u003E\u003Cp\u003E\u003Cimg src=\u0022https:\/\/www.scl.gatech.edu\/sites\/default\/files\/news\/2025-09\/figure2-steps1-12.jpg\u0022 alt=\u0022Steps 7-12: Advanced Implementation\u0022\u003E\u003C\/p\u003E\u003Cp\u003E\ud83d\udca1 Applied step: Rewrite one work prompt per week by climbing the ladder.\u0026nbsp;\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003E3. Unlocking Personal Productivity\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EOne of the fastest returns from GenAI comes from personal productivity. In our short courses this year, I\u2019ve seen learners gain comfort and lower stress as they practice more with the tools. Many reclaimed time by using GenAI for emails, presentations, meeting notes, and data prep.\u003C\/p\u003E\u003Cp\u003EWhile the list of GenAI time-saving strategies is broad, some uses are already mainstream and validated by thousands of professionals. The table below organizes these strategies into categories, provides guidance on how to accomplish them, and highlights common watch-outs to ensure they deliver value without risk.\u003C\/p\u003E\u003Cp\u003E\u003Cimg src=\u0022https:\/\/www.scl.gatech.edu\/sites\/default\/files\/news\/2025-09\/figure3-TimeSavingStrategies.jpg\u0022 alt=\u0022Time Saving Strategies\u0022\u003E\u003C\/p\u003E\u003Cp\u003E\ud83d\udca1 Try this week: Track one workflow where AI saved time and estimate the hours reclaimed.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003E4. Critical Thinking: Ironically More Important than Ever\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EWe wrote about critical thinking and added it to our curriculum after studies raised concerns about overreliance on AI. The smarter the tools become, the more important it is to validate their outputs.\u003C\/p\u003E\u003Cp\u003E\u003Cimg src=\u0022https:\/\/www.scl.gatech.edu\/sites\/default\/files\/news\/2025-09\/figure4-CriticalThinkingFrameworksForSCPros.jpg\u0022 alt=\u0022Critical Thinking Frameworks for Supply Chain Students and Professionals\u0022\u003E\u003C\/p\u003E\u003Cp\u003E\ud83d\udca1 Applied step: Take one AI output this week and run it through the checklist \u2014 you\u2019ll see both strengths and blind spots.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003E5. Advocating for Strategy and Guardrails\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EWe\u2019ve seen firsthand how AI policies can evolve. One major retailer shifted in less than a year from a rigid \u201conly data scientists experiment\u201d model to encouraging all employees to try safe versions of multiple LLMs. This shift shows why professionals should advocate for strategy and guardrails that evolve with the technology.\u003C\/p\u003E\u003Cp\u003E\u003Cimg src=\u0022https:\/\/www.scl.gatech.edu\/sites\/default\/files\/news\/2025-09\/figure5-FrameworkUseTiersDataSensitivity.jpg\u0022 alt=\u0022Framework: Use Tiers \u0026amp; Data Sensitivity\u0022\u003E\u003C\/p\u003E\u003Cp\u003E\ud83d\udca1 Ask your manager: Which of our daily tasks fall into green, yellow, and red today?\u0026nbsp;\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003E6. Agents: Early but Essential\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EMany industry partners are actively testing agents. Our software partners are hitting singles and doubles now, with bigger \u201chome run\u201d opportunities still developing. Agents aren\u2019t fully reliable yet, but they are advancing quickly and will increasingly appear in ERP, TMS, and WMS platforms.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EIn practice, most organizations today sit between \u003Cstrong\u003ELevel 1 (Exploratory)\u003C\/strong\u003E and \u003Cstrong\u003ELevel 2 (Task-Specific Agents)\u003C\/strong\u003E, with early pilots pushing into \u003Cstrong\u003ELevel 3 (Augmented Workflows)\u003C\/strong\u003E. Tech-forward enterprises \u2014 particularly in retail, e-commerce, and global manufacturing \u2014 are building domain-specific agents for forecasting, procurement support, and transportation planning, often embedded inside ERP or planning platforms. These companies are experimenting with multi-agent coordination but keep humans firmly in the loop. By contrast, mainstream companies are still largely in the exploratory stage: individuals using general copilots for drafting documents or ad hoc analysis, without enterprise integration, security controls, or governance. The gap is widening \u2014 forward-leaning firms are developing playbooks for orchestrated workflows, while many organizations are just beginning to set policies and figure out where AI fits safely into their operations.\u003C\/p\u003E\u003Cp\u003E\u003Cimg src=\u0022https:\/\/www.scl.gatech.edu\/sites\/default\/files\/news\/2025-09\/figure6-AgentMaturityPathSupplyChain.jpg\u0022 alt=\u0022Agent Maturity Path in Supply Chain\u0022\u003E\u003C\/p\u003E\u003Cp\u003ELooking ahead, \u003Cstrong\u003ELevel 4 (Collaborative Automation)\u003C\/strong\u003E is where the near-term breakthroughs will happen. In the next 3\u20135 years, we can expect multi-agent orchestration to become a practical tool for managing recurring disruptions \u2014 think transportation rerouting during weather events or automated supplier alerts when delivery milestones are missed. Early adoption will occur in large, tech-forward enterprises with strong governance and secure infrastructure. Level 5 (Autonomous Resilience) remains aspirational: while the vision of end-to-end supply chain automation is compelling, regulatory hurdles, trust, and explainability challenges mean human oversight will remain essential. The more realistic trajectory is that enterprises will selectively automate narrow disruption scenarios while maintaining tight human control, with broader autonomy coming only as governance, standards, and trust mechanisms mature.\u003C\/p\u003E\u003Cp\u003E\ud83d\udca1 Applied step: Identify one repetitive process in your work that could be a candidate for an agent.\u0026nbsp;\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003E7. Human in the Loop: Non-Negotiable\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003ECompetition has improved model quality this year \u2014 but hallucinations and memory issues remain. That\u2019s why \u201chuman in the loop\u201d is not just a principle; it\u2019s operational reality. AI is still an assistant, not a replacement.\u003C\/p\u003E\u003Cp\u003E\ud83d\udca1 Applied step: Write down one checkpoint you always apply before sharing AI outputs.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EConclusion\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThese observations \u2014 from teaching courses, updating curriculum, and watching partners experiment \u2014 motivated this article. GenAI is evolving at extraordinary speed, and our profession must evolve with it. Build your plan, refine your prompts, reclaim time, apply critical thinking, advocate for strategy, explore agents, and always keep the human in the loop. Those who do will thrive in 2026 and beyond.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis year has felt like a lifetime in the Generative AI (GenAI) world. Tools, capabilities, and best practices are shifting monthly, sometimes weekly. For supply chain professionals, the message is clear: ongoing development is not optional. Like lean, analytics, or S\u0026amp;OP in prior decades, GenAI proficiency is quickly becoming a differentiator. The question is not if you\u2019ll integrate GenAI into your workflow, but how quickly and effectively.\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Generative AI is rapidly evolving, and for supply chain professionals, adopting it quickly and effectively is becoming essential to stay competitive."}],"uid":"27233","created_gmt":"2025-09-24 13:17:49","changed_gmt":"2026-02-27 15:20:05","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2025-09-25T00:00:00-04:00","iso_date":"2025-09-25T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"679472":{"id":"679472","type":"image","title":"If I Were Starting My Supply Chain Career Today, Here\u2019s How I\u2019d Learn GenAI","body":null,"created":"1772205493","gmt_created":"2026-02-27 15:18:13","changed":"1772205579","gmt_changed":"2026-02-27 15:19:39","alt":"Futuristic illustration showing lightbulb with elements of modern supply chain inside.","file":{"fid":"263639","name":"StartingSupply-ChainCareer-Today.jpg","image_path":"\/sites\/default\/files\/2026\/02\/27\/StartingSupply-ChainCareer-Today.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/02\/27\/StartingSupply-ChainCareer-Today.jpg","mime":"image\/jpeg","size":105606,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/02\/27\/StartingSupply-ChainCareer-Today.jpg?itok=e5D2ReOJ"}},"674087":{"id":"674087","type":"image","title":"Chris Gaffney","body":"\u003Cp\u003EChris Gaffney\u003C\/p\u003E","created":"1717067903","gmt_created":"2024-05-30 11:18:23","changed":"1771883375","gmt_changed":"2026-02-23 21:49:35","alt":"Chris Gaffney, Managing Director, Georgia Tech Supply Chain and Logistics Institute","file":{"fid":"257557","name":"chris-gaffney_scl.jpg","image_path":"\/sites\/default\/files\/2024\/05\/30\/chris-gaffney_scl.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2024\/05\/30\/chris-gaffney_scl.jpg","mime":"image\/jpeg","size":129544,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2024\/05\/30\/chris-gaffney_scl.jpg?itok=_M0fOBTF"}}},"media_ids":["679472","674087"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/gaiascp","title":"Generative AI Application for Supply Chain Professionals course"},{"url":"https:\/\/www.scl.gatech.edu\/news-events\/newsletters","title":"View past SCL newsletters and join our mailing list"},{"url":"https:\/\/www.scl.gatech.edu\/","title":"Georgia Tech Supply Chain and Logistics Institute"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[{"id":"194606","name":"Artificial Intelligence"},{"id":"42911","name":"Education"},{"id":"145","name":"Engineering"}],"keywords":[{"id":"2556","name":"artificial intelligence"},{"id":"194489","name":"scl-spot"},{"id":"167074","name":"Supply Chain"},{"id":"186857","name":"go-gtmi"}],"core_research_areas":[{"id":"39461","name":"Manufacturing, Trade, and Logistics"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":["info@scl.gatech.edu"],"slides":[],"orientation":[],"userdata":""}},"688363":{"#nid":"688363","#data":{"type":"news","title":"Putting Points on the Board with AI in Supply Chain","body":[{"value":"\u003Cp\u003E\u003Cem\u003EBy Chris Gaffney, Managing Director of the Georgia Tech Supply Chain and Logistics Institute, Supply Chain Advisor, and former executive at Frito\u2011Lay, AJC International, and Coca\u2011Cola, and Michael Barnett, Founder and Principal of Synaptic SC, former global leader of Supply Chain AI at BCG, and former executive at Aera Technology and Koch Industries.\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003EEntering 2026, one thing is clear: staying on the sidelines is no longer a viable option. We both agree that 2025 was the last year when being \u201cbehind\u201d on AI adoption could be rationalized. In 2026, leaders cannot stay in the foxhole. They need to move forward, doing so in a way that reduces the risk of failure.\u003C\/p\u003E\u003Cp\u003EThe past two years have been full of promise for AI in supply chain: we have seen impressive pilots, compelling research findings, and no shortage of claims about what agents and large language models can do. At the same time, many supply chain leaders are frustrated; there has been significant activity and investment in centralized capabilities without meaningful results in the supply chain. Too many efforts stall. Too many pilots never scale. Many organizations feel they have kissed a lot of frogs and are still waiting for something that works reliably.\u003C\/p\u003E\u003Cp\u003EThe question for 2026 is no longer whether to engage with AI, but how to do so in a way that consistently delivers results. This is the year to put points on the board through disciplined, repeatable progress rather than moonshots.\u003C\/p\u003E\u003Ch2\u003ETwo Principles Separate Progress from Experimentation\u003C\/h2\u003E\u003Cp\u003EAcross our work and conversations with supply chain leaders, organizations that are driving tangible results tend to follow two principles, sometimes explicitly, sometimes intuitively:\u003C\/p\u003E\u003Ch3\u003E1. Leverage GenAI Where It Adds Differential Value\u003C\/h3\u003E\u003Cp\u003ELarge language models are exceptionally strong at working with language. They summarize, explain, code, and translate intent into logic. This makes them powerful tools for accelerating development, analysis, and communication.\u003C\/p\u003E\u003Cp\u003EMuch of supply chain execution, however, depends on precision. Planning rates, forecasts, production schedules, routing logic, and inventory policies rely on structured data, mathematical relationships, and deterministic logic. In these environments, hallucinations or probabilistic answers are not just inconvenient. They can be operationally disruptive.\u003C\/p\u003E\u003Cp\u003EMany early failures stem from applying LLMs where deterministic logic is required, rather than using them to support the creation, maintenance, and monitoring of that logic. In practice, GenAI is most effective upstream, helping teams build analytics faster, surface issues earlier, and lower the friction of development and maintenance.\u003C\/p\u003E\u003Ch3\u003E2. Design with People in the Loop\u003C\/h3\u003E\u003Cp\u003EThis is not only a philosophical stance. It reflects technical reality. While \u003Ca href=\u0022https:\/\/research.gatech.edu\/age-autonomous-supply-chains-here\u0022\u003Erecent research\u003C\/a\u003E shows that collections of agents can outperform humans in controlled settings, production supply chains are not laboratories. They are complex, interconnected processes and organizations that operate in a dynamic, ever-changing environment. In contrast to AI that augments workers, fully autonomous systems introduce risks\u2014technical, organizational, and reputational\u2014that erode the incremental value relative to the increased costs to develop and maintain them.\u003C\/p\u003E\u003Cp\u003EHuman-in-the-loop is not a concession. It is a design principle.\u003C\/p\u003E\u003Ch2\u003EFrom Ideation to Error-Proofed Execution\u003C\/h2\u003E\u003Cp\u003EMost supply chain organizations are not short on AI use cases. What they lack are clear, high\u2011probability paths to value creation.\u003C\/p\u003E\u003Cp\u003EA familiar pattern plays out: organizations rush into pilots without a clear view of where AI adds value. Results are mixed and hard to interpret. When early efforts disappoint, leaders become more cautious, not because they doubt AI\u2019s potential, but because they are wary of repeating visible failures.\u003C\/p\u003E\u003Cp\u003EOne executive described this dynamic as being \u0022tired of kissing frogs.\u0022 After aggressively leaning into new technologies early, the organization became skeptical, insisting on external proof and peer validation before investing further.\u003C\/p\u003E\u003Cp\u003EThe more productive question is no longer \u0022What is the most advanced thing we can try?\u0022 but instead: \u0022What can we do today that has a high probability of working, scaling, and building our capabilities?\u0022\u003C\/p\u003E\u003Ch2\u003EHow to Put Points on the Board in 2026\u003C\/h2\u003E\u003Cp\u003EAcross our experimentation and advisory work, two areas consistently emerge where GenAI is already delivering value.\u003C\/p\u003E\u003Ch3\u003EEnterprise Productivity: The Safest On-Ramp\u003C\/h3\u003E\u003Cp\u003EThe most reliable progress comes from improving everyday productivity.\u003C\/p\u003E\u003Cp\u003EMost organizations take a restrictive approach, limiting AI access to a small group or tightly controlled pilots led by centralized technical teams, only to realize they were slowing learning and adoption across the enterprise. In one large retailer, leadership initially centralized AI use due to security and governance concerns. Over time, they shifted to enterprise licensing that centralized risk management while allowing broader employee access within guardrails.\u003C\/p\u003E\u003Cp\u003EThe result was not chaos or \u0022shadow IT.\u0022 It was productivity: meeting summaries, analysis support, presentation development, and faster access to internal knowledge.\u003C\/p\u003E\u003Cp\u003EThese gains may sound modest, but they matter. Giving people five to ten hours per week back changes how employees experience AI. It becomes a tool that helps them do their jobs better, not a signal that their jobs are being automated away.\u003C\/p\u003E\u003Cp\u003EFor leaders, this means actively enabling access to approved tools, supporting skill development, and encouraging experimentation within clear boundaries. This is one of the most straightforward ways to quickly and visibly put points on the board.\u003C\/p\u003E\u003Ch3\u003EDecision Intelligence: Rewiring the Operating Model\u003C\/h3\u003E\u003Cp\u003EAdvanced analytics, optimization, and planning systems predate GenAI. What is new is not the math, but rather the speed, accessibility, and maintainability of building and sustaining advanced analytics solutions.\u003C\/p\u003E\u003Cp\u003EGenAI acts as an accelerator. It reduces the friction of writing code, standing up, monitoring logic, and explaining results. It brings advanced capabilities closer to the business, rather than confining them to a small central team.\u003C\/p\u003E\u003Cp\u003EA concrete example comes from production planning. Planned production rates are often set during commissioning or early ramp up and then reused for long periods. Over time, changes in labor mix, maintenance practices, or product complexity cause actual throughput to drift. Plans continue to run, but they quietly degrade.\u003C\/p\u003E\u003Cp\u003EIn effective implementations, GenAI does not update the planning system autonomously. Instead, it operates adjacent to it. It helps teams build monitoring logic that compares planned versus actual performance, surfaces statistically meaningful drift, and generates candidate adjustments with supporting context. Planners review and approve changes before they are re-ingested into the APS.\u003C\/p\u003E\u003Cp\u003EThe system of record remains intact. Human accountability is preserved. What improves is the speed, frequency, and quality of assumption hygiene, enabling earlier detection of problems before they cascade into service, cost, or inventory issues.\u003C\/p\u003E\u003Ch2\u003EAvoid Kissing Frogs: Technology and Organizational Choices\u003C\/h2\u003E\u003Cp\u003EMany organizations \u201ckiss frogs\u201d not because the new technology is flawed, but because they are not ready to adopt it.\u003C\/p\u003E\u003Cp\u003ETo avoid this fate, successful efforts often include the following elements:\u003C\/p\u003E\u003Col\u003E\u003Cli\u003E\u003Cstrong\u003ELeverage existing, approved AI platforms rather than onboarding new technologies\u003C\/strong\u003E\u003Cul\u003E\u003Cli\u003EAccelerates time to value\u003C\/li\u003E\u003Cli\u003EHelps define the true limitations of your current technology stack to guide future platform selection\u003C\/li\u003E\u003C\/ul\u003E\u003C\/li\u003E\u003Cli\u003E\u003Cstrong\u003EMaximize the value of current systems (e.g., APS, production scheduling software) instead of chasing new applications\u003C\/strong\u003E\u003Cul\u003E\u003Cli\u003EExisting, complex supply chain software often under-delivers on its promised value\u003C\/li\u003E\u003Cli\u003EAI agents and workflows are highly effective at improving master data quality and ensuring planning parameters are accurate\u003C\/li\u003E\u003C\/ul\u003E\u003C\/li\u003E\u003Cli\u003E\u003Cstrong\u003EFoster ideation and solution development with internal teams, while using third parties to accelerate capability building\u2014not to replace it\u003C\/strong\u003E\u003C\/li\u003E\u003Cli\u003E\u003Cstrong\u003EMake progress visible by sharing early wins, curating employee-driven experiments, and scaling what works\u003C\/strong\u003E\u003C\/li\u003E\u003C\/ol\u003E\u003Cp\u003EChange management is not an option; it must be designed into every aspect of an AI program from the start. When organizations invest heavily in advanced capabilities at the top while doing little to equip everyday employees, the message received is often, \u0022This is happening to you, not for you.\u0022 That perception creates resistance, fear, and organizational drag.\u003C\/p\u003E\u003Cp\u003EEffective leaders communicate a clear vision for how new capabilities will augment, not replace, their teams, so that scarce human intellect is applied where it adds the most value.\u003C\/p\u003E\u003Ch2\u003EKey Actions to Win in 2026\u003C\/h2\u003E\u003Cp\u003EThe principles are clear. The opportunity is real. The question now is execution.\u003C\/p\u003E\u003Cp\u003EIf 2026 is the year to put points on the board, supply chain leaders must move from experimentation to engineered progress. That begins with clarity.\u003C\/p\u003E\u003Ch3\u003E1. Define a Multi-Year AI Value Vision\u003C\/h3\u003E\u003Cp\u003EDevelop a concrete view of how AI will create value in your organization over the next several years. Not a collection of pilots. Not a list of tools. A clear articulation of where and how AI will improve productivity, strengthen decision quality, and increase operational reliability.\u003C\/p\u003E\u003Cp\u003EThat vision should:\u003C\/p\u003E\u003Cul\u003E\u003Cli\u003EClarify where AI will augment human decision-making versus automate tasks\u003C\/li\u003E\u003Cli\u003EIdentify the business outcomes you expect to improve (service, cost, inventory, resilience, productivity)\u003C\/li\u003E\u003Cli\u003EGuide decisions on organizational design, platform selection, governance, and partnerships\u003C\/li\u003E\u003Cli\u003EEstablish sequencing - what you will enable now versus what must wait\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003EWithout a defined direction, AI efforts default to software deployment. With it, technology becomes a lever for measurable operational improvement.\u003C\/p\u003E\u003Ch3\u003E2. Enable Broad, Responsible Access\u003C\/h3\u003E\u003Cp\u003ECapability development accelerates when access is not unnecessarily constrained. Ensure that team members at every level - from executives to frontline planners - have access to approved enterprise AI tools and agent-building capabilities, along with practical training tied to real workflows.\u003C\/p\u003E\u003Cp\u003EEffective enablement includes:\u003C\/p\u003E\u003Cul\u003E\u003Cli\u003EEnterprise licensing and governance that remove friction while protecting data\u003C\/li\u003E\u003Cli\u003EHands-on guidance tied directly to day-to-day supply chain work - reporting, master data cleanup, production monitoring, inventory analysis, schedule validation\u003C\/li\u003E\u003Cli\u003EClear operating guardrails that define appropriate data use and boundaries\u003C\/li\u003E\u003Cli\u003ELeadership support for responsible experimentation\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003ERestricting access may feel prudent. In practice, it slows learning and reinforces dependency on centralized teams. Broad enablement builds capability across the organization.\u003C\/p\u003E\u003Ch3\u003E3. Create Local Ideation and Scaling Mechanisms\u003C\/h3\u003E\u003Cp\u003EDurable progress does not originate only from centralized programs. It often begins at the front line.\u003Cbr\u003ELeaders should create simple, visible mechanisms for individuals and teams to experiment within defined guardrails and to share what they are building.\u003C\/p\u003E\u003Cp\u003EThis includes:\u003C\/p\u003E\u003Cul\u003E\u003Cli\u003ERecurring forums or showcases where teams present working solutions\u003C\/li\u003E\u003Cli\u003ECurated libraries of effective prompts, workflows, and agents\u003C\/li\u003E\u003Cli\u003EClear channels for submitting ideas and documenting results\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003EMost importantly, organizations must be able to move from local experimentation to scaled adoption. That requires:\u003C\/p\u003E\u003Cul\u003E\u003Cli\u003EIdentifying the strongest minimum viable solutions emerging from the field\u003C\/li\u003E\u003Cli\u003ERefining and hardening them into repeatable workflows\u003C\/li\u003E\u003Cli\u003EProductizing and scaling what demonstrably improves performance\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003EThe objective is not activity. It is building capability that compounds over time.\u003C\/p\u003E\u003Cp\u003EThese steps are straightforward. They require intention and follow-through. That is what separates durable capability from scattered experimentation.\u003C\/p\u003E\u003Cp\u003EIt is not too late to lead. The last several years have provided lessons - technical, organizational, and cultural. Leaders who absorb those lessons and design deliberately for scale will build AI capabilities that strengthen over time.\u003C\/p\u003E\u003Cp\u003EThat kind of progress is not flashy. It does not depend on moonshots or fully autonomous systems operating in isolation. It depends on clarity, access, discipline, and accountability.\u003C\/p\u003E\u003Cp\u003EIn 2026, novelty will attract attention. Durability will create an advantage.\u003C\/p\u003E\u003Cp\u003EThe organizations that win will not be the ones with the most pilots. They will be the ones who consistently translate AI into measurable operational improvement.\u003C\/p\u003E\u003Cp\u003EThis is the year to move from experimentation to engineered results.\u003C\/p\u003E\u003Ch2\u003E\u003Cstrong\u003EPut points on the board.\u003C\/strong\u003E\u003C\/h2\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EIn 2026, supply chain leaders must move beyond experimentation with AI to achieve consistent, measurable results by focusing on practical, scalable applications that augment human decision-making and improve productivity.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Practical guidance to drive real progress in 2026."}],"uid":"27233","created_gmt":"2026-02-18 17:20:05","changed_gmt":"2026-02-24 00:01:16","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2026-02-24T00:00:00-05:00","iso_date":"2026-02-24T00:00:00-05:00","tz":"America\/New_York"},"extras":[],"hg_media":{"679399":{"id":"679399","type":"image","title":"AI-Driven Decision Intelligence  Across the Supply Chain","body":null,"created":"1771877803","gmt_created":"2026-02-23 20:16:43","changed":"1772457797","gmt_changed":"2026-03-02 13:23:17","alt":"Illustration of AI-driven supply chain decision intelligence, featuring analytics dashboards and AI\u2011powered insights supporting materials management, production scheduling, inventory management, transportation, and demand planning.","file":{"fid":"263562","name":"bnr-CM-AI-DrivenDecisionIntelligence_1024x1024.jpg","image_path":"\/sites\/default\/files\/2026\/02\/23\/bnr-CM-AI-DrivenDecisionIntelligence_1024x1024.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/02\/23\/bnr-CM-AI-DrivenDecisionIntelligence_1024x1024.jpg","mime":"image\/jpeg","size":163591,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/02\/23\/bnr-CM-AI-DrivenDecisionIntelligence_1024x1024.jpg?itok=Cmb-KmGb"}},"674087":{"id":"674087","type":"image","title":"Chris Gaffney","body":"\u003Cp\u003EChris Gaffney\u003C\/p\u003E","created":"1717067903","gmt_created":"2024-05-30 11:18:23","changed":"1771883375","gmt_changed":"2026-02-23 21:49:35","alt":"Chris Gaffney, Managing Director, Georgia Tech Supply Chain and Logistics Institute","file":{"fid":"257557","name":"chris-gaffney_scl.jpg","image_path":"\/sites\/default\/files\/2024\/05\/30\/chris-gaffney_scl.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2024\/05\/30\/chris-gaffney_scl.jpg","mime":"image\/jpeg","size":129544,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2024\/05\/30\/chris-gaffney_scl.jpg?itok=_M0fOBTF"}},"679403":{"id":"679403","type":"image","title":"Michael Barnett","body":null,"created":"1771883408","gmt_created":"2026-02-23 21:50:08","changed":"1771883408","gmt_changed":"2026-02-23 21:50:08","alt":"Michael Barnett","file":{"fid":"263563","name":"Barnett-Michael-2022.jpg","image_path":"\/sites\/default\/files\/2026\/02\/23\/Barnett-Michael-2022.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/02\/23\/Barnett-Michael-2022.jpg","mime":"image\/jpeg","size":21649,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/02\/23\/Barnett-Michael-2022.jpg?itok=RzHA96wO"}}},"media_ids":["679399","674087","679403"],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/news-events\/newsletters","title":"View past SCL newsletters and join our mailing list"},{"url":"https:\/\/www.scl.gatech.edu\/","title":"Georgia Tech Supply Chain and Logistics Institute"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[{"id":"194606","name":"Artificial Intelligence"},{"id":"42911","name":"Education"},{"id":"145","name":"Engineering"}],"keywords":[{"id":"2556","name":"artificial intelligence"},{"id":"194489","name":"scl-spot"},{"id":"167074","name":"Supply Chain"},{"id":"187190","name":"-go-gtmi"}],"core_research_areas":[{"id":"39461","name":"Manufacturing, Trade, and Logistics"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":["info@scl.gatech.edu"],"slides":[],"orientation":[],"userdata":""}}}