Trascrizione completa di Sustainability Under Pressure: AI, Geopolitics, and the Path Forward

last theme revolves 84 00:03:33,450 --> 00:03:35,910 around freight transportation and warehouse automation. 85 00:03:35,910 --> 00:03:39,030 We wanted to understand how freight decarbonization, 86 00:03:39,030 --> 00:03:41,820 use of alternative fuels, warehouse automation, 87 00:03:41,820 --> 00:03:45,120 and AI are shaping the overall landscape, 88 00:03:45,120 --> 00:03:46,680 and what is the implications of these 89 00:03:46,680 --> 00:03:49,500 on energy use, emissions, and waste. 90 00:03:49,500 --> 00:03:51,030 The first theme, which is focused 91 00:03:51,030 --> 00:03:52,590 on governance and geopolitics, 92 00:03:52,590 --> 00:03:55,980 what we see is companies' commitment 93 00:03:55,980 --> 00:03:57,450 to sustainability has increased. 94 00:03:57,450 --> 00:03:59,377 In fact, the question that we asked was, 95 00:03:59,377 --> 00:04:01,680 "Have your commitment to sustainability changed 96 00:04:01,680 --> 00:04:04,110 as a result of policy changes?" 97 00:04:04,110 --> 00:04:06,900 Last year, what company said is a majority of them said 98 00:04:06,900 --> 00:04:09,150 that there is no change in their sustainability commitments, 99 00:04:09,150 --> 00:04:11,310 and a few person did said 100 00:04:11,310 --> 00:04:13,680 that they have increased their commitments. 101 00:04:13,680 --> 00:04:15,630 And interestingly, what we see this year 102 00:04:15,630 --> 00:04:18,150 to the same question is, like, 103 00:04:18,150 --> 00:04:19,830 a significant chunk of them 104 00:04:19,830 --> 00:04:21,600 actually have increased their commitments 105 00:04:21,600 --> 00:04:23,880 across North America, Europe, and Asia. 106 00:04:23,880 --> 00:04:26,700 But the downside is when we ask companies 107 00:04:26,700 --> 00:04:29,760 what has been the impact of tariff uncertainty 108 00:04:29,760 --> 00:04:34,260 and the overall tariff shock as itself on their commitment, 109 00:04:34,260 --> 00:04:37,200 and what we find is, overall, globally, 110 00:04:37,200 --> 00:04:42,200 68% of the companies claim that they had to pause 111 00:04:43,230 --> 00:04:45,840 or scale back some of their sustainability initiatives 112 00:04:45,840 --> 00:04:47,280 because of the shocks 113 00:04:47,280 --> 00:04:49,830 as a result of the uncertainty around tariff. 114 00:04:49,830 --> 00:04:52,410 And even worse, what we see is 115 00:04:52,410 --> 00:04:55,170 one in three companies actually report 116 00:04:55,170 --> 00:04:57,120 increase in their operational emissions 117 00:04:57,120 --> 00:04:59,730 as a result of tariff shocks. 118 00:04:59,730 --> 00:05:02,970 And more than eight in 10 companies 119 00:05:02,970 --> 00:05:05,580 across North America, Asia, and Europe claim 120 00:05:05,580 --> 00:05:08,790 that geopolitical conflicts reduce the impact 121 00:05:08,790 --> 00:05:11,010 of their climate actions that they are taking, 122 00:05:11,010 --> 00:05:12,300 which is really sad. 123 00:05:12,300 --> 00:05:14,610 Moving on to the internal governance part, 124 00:05:14,610 --> 00:05:18,180 what we see is 83% of the respondents say 125 00:05:18,180 --> 00:05:21,180 that sustainability is important to very important 126 00:05:21,180 --> 00:05:22,800 to their long-term success. 127 00:05:22,800 --> 00:05:24,510 However, if you look at 128 00:05:24,510 --> 00:05:27,300 how these sustainability decisions are integrated 129 00:05:27,300 --> 00:05:29,970 into their day-to-day operational aspect, 130 00:05:29,970 --> 00:05:34,320 we see companies that have formal cross-functional team, 131 00:05:34,320 --> 00:05:37,110 53% of them actually integrate sustainability 132 00:05:37,110 --> 00:05:39,570 into their day-to-day operational decisions. 133 00:05:39,570 --> 00:05:40,830 These are the companies 134 00:05:40,830 --> 00:05:44,220 that have only a single sustainability team, 135 00:05:44,220 --> 00:05:45,990 which is not cross-functional, 136 00:05:45,990 --> 00:05:48,390 which has maybe one or two people, 137 00:05:48,390 --> 00:05:50,940 only 13% of them actually claim 138 00:05:50,940 --> 00:05:52,830 that they integrate sustainability 139 00:05:52,830 --> 00:05:54,360 into their operational decisions. 140 00:05:54,360 --> 00:05:55,980 Another interesting thing is 141 00:05:55,980 --> 00:05:57,180 when we looked at companies 142 00:05:57,180 --> 00:06:00,060 that have publicly stated the sustainability goals, 143 00:06:00,060 --> 00:06:02,010 only 51% of them 144 00:06:02,010 --> 00:06:04,860 have a formal cross-functional team structure. 145 00:06:04,860 --> 00:06:07,590 And in terms of the board oversight, 146 00:06:07,590 --> 00:06:10,230 what we find is only 33% of them 147 00:06:10,230 --> 00:06:13,050 have a say at the board level. 148 00:06:13,050 --> 00:06:14,340 And this basically shows 149 00:06:14,340 --> 00:06:15,990 how the internal governance structure 150 00:06:15,990 --> 00:06:17,310 plays a very important role 151 00:06:17,310 --> 00:06:20,190 for companies to be able to invest in sustainability, 152 00:06:20,190 --> 00:06:22,020 also integrate sustainability 153 00:06:22,020 --> 00:06:23,820 into their day-to-day decisions. 154 00:06:23,820 --> 00:06:27,480 Moving on to the next theme, which is AI and sustainability, 155 00:06:27,480 --> 00:06:30,300 we asked whether companies find AI's benefit 156 00:06:30,300 --> 00:06:33,000 to be outweighing the environmental costs. 157 00:06:33,000 --> 00:06:34,620 And interestingly, what we find is 158 00:06:34,620 --> 00:06:36,630 a significant chunk of them say 159 00:06:36,630 --> 00:06:39,090 that they would continue to invest in AI 160 00:06:39,090 --> 00:06:42,780 while taking into account the environmental costs of AI. 161 00:06:42,780 --> 00:06:45,120 And a small percentage actually say 162 00:06:45,120 --> 00:06:46,890 that they have not been investing in AI 163 00:06:46,890 --> 00:06:47,970 because they're very cautious 164 00:06:47,970 --> 00:06:49,710 about the environmental downside. 165 00:06:49,710 --> 00:06:52,710 And

overall, 37% basically say 166 00:06:52,710 --> 00:06:56,310 that AI's benefit clearly outweighs its environmental cost, 167 00:06:56,310 --> 00:06:59,220 and they have been investing in AI to a large extent. 168 00:06:59,220 --> 00:07:03,510 We see that, of course, in terms of AI use, 169 00:07:03,510 --> 00:07:07,950 a lot of companies are using AI for emissions measurement. 170 00:07:07,950 --> 00:07:10,590 They're more than decision making or scenario planning. 171 00:07:10,590 --> 00:07:12,570 And even in terms of emissions measurement, 172 00:07:12,570 --> 00:07:14,220 a lot of companies are using AI 173 00:07:14,220 --> 00:07:17,520 to get data where supplier data is missing, 174 00:07:17,520 --> 00:07:21,150 aggregate data from different sources, and also reporting. 175 00:07:21,150 --> 00:07:22,830 And when we ask companies 176 00:07:22,830 --> 00:07:24,780 what are the different sustainability goals 177 00:07:24,780 --> 00:07:27,720 that AI has been able to help them improve, 178 00:07:27,720 --> 00:07:30,990 57% of them claimed operational efficiency, 179 00:07:30,990 --> 00:07:34,590 and about 47.7% of them said 180 00:07:34,590 --> 00:07:37,770 that AI is basically helping them to reduce emissions. 181 00:07:37,770 --> 00:07:39,900 I'm not sure if companies are there yet 182 00:07:39,900 --> 00:07:43,350 in terms of finding out the net environmental benefit 183 00:07:43,350 --> 00:07:45,780 of AI on overall emissions, 184 00:07:45,780 --> 00:07:47,970 but what we see is they at least perceive 185 00:07:47,970 --> 00:07:50,700 that AI has basically helped them to measure emissions 186 00:07:50,700 --> 00:07:53,010 and also reduce emissions. 187 00:07:53,010 --> 00:07:56,730 We also focused on the AI use in supply chain. 188 00:07:56,730 --> 00:07:59,880 Where is industrial AI and agentic AI is being deployed, 189 00:07:59,880 --> 00:08:01,860 and what are the benefits of these? 190 00:08:01,860 --> 00:08:04,650 Only 18.5% of the companies say 191 00:08:04,650 --> 00:08:06,930 that they have integrated AI widely 192 00:08:06,930 --> 00:08:09,120 into their organizational functions, 193 00:08:09,120 --> 00:08:10,830 and about 50% of them say 194 00:08:10,830 --> 00:08:13,050 that they broadly use it in multiple functions, 195 00:08:13,050 --> 00:08:14,910 but they haven't integrated it fully. 196 00:08:14,910 --> 00:08:18,510 And we asked, "What is the implication of using AI 197 00:08:18,510 --> 00:08:21,360 in supply chain functions on emissions 198 00:08:21,360 --> 00:08:22,620 or on sustainability goals?" 199 00:08:22,620 --> 00:08:24,780 And what we see is that those 200 00:08:24,780 --> 00:08:28,110 who have integrated AI well into their supply chain, 201 00:08:28,110 --> 00:08:33,110 85.8% of them say that AI actually helps them reduce waste. 202 00:08:33,450 --> 00:08:35,130 And also, 84% of them claim 203 00:08:35,130 --> 00:08:38,100 that AI is helping them identify emissions hotspot, 204 00:08:38,100 --> 00:08:40,170 and 81%

actually say 205 00:08:40,170 --> 00:08:43,080 AI is helping them reduce their energy use or fuel. 206 00:08:43,080 --> 00:08:45,600 What we also find from the report is 207 00:08:45,600 --> 00:08:50,130 close to 63% of the firms say that energy consumption 208 00:08:50,130 --> 00:08:52,560 is one of the top challenges in their supply chain. 209 00:08:52,560 --> 00:08:54,540 I don't think companies are there yet 210 00:08:54,540 --> 00:08:58,500 in terms of finalizing the net environmental benefit of AI. 211 00:08:58,500 --> 00:08:59,820 Going to the last theme, 212 00:08:59,820 --> 00:09:02,910 which is freight decarbonization and warehouse automation, 213 00:09:02,910 --> 00:09:05,850 what we find is a lot of companies 214 00:09:05,850 --> 00:09:08,850 are trying to decarbonize their freight, 215 00:09:08,850 --> 00:09:11,550 but more companies are actually working 216 00:09:11,550 --> 00:09:13,500 on operational efficiency, 217 00:09:13,500 --> 00:09:15,390 increasing operational efficiencies, 218 00:09:15,390 --> 00:09:18,570 rather than actually changing the fuel in the tank. 219 00:09:18,570 --> 00:09:20,910 If you see, 43% of the companies 220 00:09:20,910 --> 00:09:24,690 still use diesel primarily as a fuel, 221 00:09:24,690 --> 00:09:28,530 and also, in terms of regulatory and policy changes, 222 00:09:28,530 --> 00:09:31,440 that has a lot of impact, particularly for North America. 223 00:09:31,440 --> 00:09:34,080 Close to 43% of the firms say 224 00:09:34,080 --> 00:09:37,080 that the regulatory changes have actually 225 00:09:37,080 --> 00:09:39,270 made them rethink about their investments, 226 00:09:39,270 --> 00:09:41,610 and some have actually paused their investments 227 00:09:41,610 --> 00:09:42,810 in sustainability initiatives 228 00:09:42,810 --> 00:09:46,170 because they do not know where the policy is clearly headed. 229 00:09:46,170 --> 00:09:48,360 In terms of warehouse automation, 230 00:09:48,360 --> 00:09:52,830 what we see is 40% of the firms that we surveyed 231 00:09:52,830 --> 00:09:55,590 are either moderately or fully automated, 232 00:09:55,590 --> 00:09:57,330 advanced or fully automated, 233 00:09:57,330 --> 00:10:00,120 and they have also been using AI extensively 234 00:10:00,120 --> 00:10:02,010 in their decision making. 235 00:10:02,010 --> 00:10:04,680 But when we ask them what is the impact 236 00:10:04,680 --> 00:10:08,520 of automation on energy consumption and waste, 237 00:10:08,520 --> 00:10:12,840 what we find is, as the level of automation goes up, 238 00:10:12,840 --> 00:10:15,510 close to 80% of the respondents say 239 00:10:15,510 --> 00:10:17,730 that actually their energy consumption and waste 240 00:10:17,730 --> 00:10:19,950 have gone up as a result of automation. 241 00:10:19,950 --> 00:10:24,450 And so some of the key takeaways from this year's report is, 242 00:10:24,450 --> 00:10:25,800 of course, commitment is strong, 243 00:10:25,800 --> 00:10:29,040 but execution has become increasingly harder. 244 00:10:29,040 --> 00:10:31,050 And in terms of governance, 245 00:10:31,050 --> 00:10:33,480 I think it's important for companies 246 00:10:33,480 --> 00:10:35,460 not just to have goals in place, 247 00:10:35,460 --> 00:10:38,010 but also have the internal governance structures in place 248 00:10:38,010 --> 00:10:40,470 to be able to follow through those commitments. 249 00:10:40,470 --> 00:10:42,270 From a supply chain point of view, 250 00:10:42,270 --> 00:10:45,570 AI is being increasingly embedded in operational decisions, 251 00:10:45,570 --> 00:10:46,950 but not in strategic decisions. 252 00:10:46,950 --> 00:10:49,470 So companies are using AI to measure, 253 00:10:49,470 --> 00:10:51,960 but I think it's high time they use it to manage, 254 00:10:51,960 --> 00:10:54,060 and overall they look at more collaboration 255 00:10:54,060 --> 00:10:55,920 for managing their Scope three emissions. 256 00:10:55,920 --> 00:11:00,030 There is a clear operational efficiency benefits of AI use, 257 00:11:00,030 --> 00:11:02,940 but it's important that we move away from efficiency 258 00:11:02,940 --> 00:11:05,100 to net environmental benefit. 259 00:11:05,100 --> 00:11:07,660 And in terms of freight decarbonization, 260 00:11:07,660 --> 00:11:09,810 more than focusing on incremental gains, 261 00:11:09,810 --> 00:11:13,080 it's important for companies to go into deeper transitions 262 00:11:13,080 --> 00:11:14,610 and use alternative fuels 263 00:11:14,610 --> 00:11:16,620 and get into more capital investment. 264 00:11:16,620 --> 00:11:18,990 So the path forward is not just more goals. 265 00:11:18,990 --> 00:11:21,480 It's better governance, better measurement, 266 00:11:21,480 --> 00:11:23,220 smarter use of AI, 267 00:11:23,220 --> 00:11:26,250 and deeper transition in the physical supply chain. 268 00:11:26,250 --> 00:11:28,170 Let's move on to the panel discussion. 269 00:11:28,170 --> 00:11:30,870 I would want to welcome our panelists. 270 00:11:30,870 --> 00:11:33,720 We have Rachel, who's vice president of ESG 271 00:11:33,720 --> 00:11:35,310 from C.H. Robinson, 272 00:11:35,310 --> 00:11:37,440 Philippine, chief sustainability officer 273 00:11:37,440 --> 00:11:39,000 from Dassault Systemes, 274 00:11:39,000 --> 00:11:42,360 Severine, head of customer impact, CO2 AI, 275 00:11:42,360 --> 00:11:44,280 and Heather, vice president, 276 00:11:44,280 --> 00:11:46,560 enterprise solutions, Breakthrough. 277 00:11:46,560 --> 00:11:50,580 I would begin with a more broad question for each of you, 278 00:11:50,580 --> 00:11:53,820 which is, over the past 12 months, 279 00:11:53,820 --> 00:11:56,280 what is the most change you have seen 280 00:11:56,280 --> 00:11:58,260 in your sustainability conversation 281 00:11:58,260 --> 00:12:00,960 within your organization or within your customers? 282 00:12:00,960 --> 00:12:02,040 Is it AI? 283 00:12:02,040 --> 00:12:03,390 Is it economics? 284 00:12:03,390 --> 00:12:05,400 Is it policy

uncertainty? 285 00:12:05,400 --> 00:12:07,470 Or is it customer? 286 00:12:07,470 --> 00:12:09,540 Maybe we can start with Rachel, you. 287 00:12:09,540 --> 00:12:11,420 - Do I have to choose from one of those listed? 288 00:12:11,420 --> 00:12:13,380 I mean, all of the above. 289 00:12:13,380 --> 00:12:16,200 Two comments I would make about the last 12 to 18 months: 290 00:12:16,200 --> 00:12:19,290 in this room and the people that we talk to all the time, 291 00:12:19,290 --> 00:12:21,840 we all know the importance of sustainability. 292 00:12:21,840 --> 00:12:23,640 We know how it ties to business case, 293 00:12:23,640 --> 00:12:25,050 but there are plenty of people 294 00:12:25,050 --> 00:12:27,030 that don't go to New York Climate Week 295 00:12:27,030 --> 00:12:29,040 that hear a very different narrative 296 00:12:29,040 --> 00:12:30,600 and probably had very different thoughts 297 00:12:30,600 --> 00:12:31,740 about what was going to be happening 298 00:12:31,740 --> 00:12:33,150 over the 12 to 18 months, 299 00:12:33,150 --> 00:12:34,680 especially in the United States. 300 00:12:34,680 --> 00:12:36,660 What I do think has shifted slightly, 301 00:12:36,660 --> 00:12:39,780 and I don't know if it's necessarily internal to Robinson, 302 00:12:39,780 --> 00:12:41,220 but what we're seeing some of 303 00:12:41,220 --> 00:12:46,220 is maybe a focusing in on the things that are most important 304 00:12:46,380 --> 00:12:49,170 to a company's business and to their stakeholders, 305 00:12:49,170 --> 00:12:50,370 which is how we've always talked 306 00:12:50,370 --> 00:12:52,410 about sustainability in the past, 307 00:12:52,410 --> 00:12:54,450 but this is kind of pressure-testing it right now 308 00:12:54,450 --> 00:12:56,910 with so many other things happening externally, 309 00:12:56,910 --> 00:12:59,760 geopolitically and economically. 310 00:12:59,760 --> 00:13:01,650 Really, what are the things that we know 311 00:13:01,650 --> 00:13:04,800 are the most critical for our business strategy 312 00:13:04,800 --> 00:13:07,230 to our stakeholders to either help mitigate risk 313 00:13:07,230 --> 00:13:09,180 or capitalize on opportunities? 314 00:13:09,180 --> 00:13:10,500 - Yeah, I'll second that. 315 00:13:10,500 --> 00:13:13,950 I would say what's really changed in the last 12 months 316 00:13:13,950 --> 00:13:18,660 is that we are seeing an increased focus on action 317 00:13:18,660 --> 00:13:21,150 rather than evidence building. 318 00:13:21,150 --> 00:13:23,400 I mean, I've been in the sustainability sector 319 00:13:23,400 --> 00:13:25,080 for over 25 years, 320 00:13:25,080 --> 00:13:26,910 and there was such a long time 321 00:13:26,910 --> 00:13:29,310 where we were supposed to build the evidence 322 00:13:29,310 --> 00:13:32,490 of making the case of why we need to act 323 00:13:32,490 --> 00:13:34,950 and why we need to have climate goals. 324 00:13:34,950 --> 00:13:38,580 And the good news is that with all the noise 325 00:13:40,170 --> 00:13:43,620 and negative zeitgeist that's going on, 326 00:13:43,620 --> 00:13:46,560 people are really focusing on action. 327 00:13:46,560 --> 00:13:50,040 And it's also true that what you just said, Rachel, 328 00:13:50,040 --> 00:13:53,190 is that because there is so much competition 329 00:13:53,190 --> 00:13:55,770 as well on capital allocation, 330 00:13:55,770 --> 00:13:58,410 you need to make a better business case 331 00:13:58,410 --> 00:14:01,620 of what the sustainability is going to bring to you, 332 00:14:01,620 --> 00:14:03,090 and that means more action 333 00:14:03,090 --> 00:14:06,360 and more tangible results to scale that. 334 00:14:06,360 --> 00:14:07,980 - I will continue towards that. 335 00:14:07,980 --> 00:14:12,240 So the first thing on our side is what we get to ask for. 336 00:14:12,240 --> 00:14:14,850 So CO2 AI, I will introduce who we are 337 00:14:14,850 --> 00:14:16,980 because I'm not sure you're familiar with us. 338 00:14:16,980 --> 00:14:20,640 So we are a AI sustainability global company, 339 00:14:20,640 --> 00:14:23,220 and we help a large company 340 00:14:23,220 --> 00:14:26,190 solve their complex issue toward the supply chain. 341 00:14:26,190 --> 00:14:28,800 So what company ask us for, 342 00:14:28,800 --> 00:14:30,990 and it echoes what Philippine just said, 343 00:14:30,990 --> 00:14:34,350 is that before they asked for us for measurement 344 00:14:34,350 --> 00:14:37,260 to answer the reporting question. 345 00:14:37,260 --> 00:14:40,170 And today, what they're asking us for 346 00:14:40,170 --> 00:14:44,700 is more business case-led use case. 347 00:14:44,700 --> 00:14:48,450 What they want to achieve is sustainability impacts, 348 00:14:48,450 --> 00:14:50,520 but also profit impact. 349 00:14:50,520 --> 00:14:55,520 And the second thing that I see also is who is in the room. 350 00:14:56,130 --> 00:15:00,300 Beforehand, we used to work mostly with sustainability team. 351 00:15:00,300 --> 00:15:03,750 Over the last year, we are working across function, 352 00:15:03,750 --> 00:15:05,910 sustainability partnering together 353 00:15:05,910 --> 00:15:10,080 with our procurements colleague, R&D, 354 00:15:10,080 --> 00:15:11,940 and even legal and finance 355 00:15:11,940 --> 00:15:16,740 when you look at packaging decision, EPR, and so on. 356 00:15:16,740 --> 00:15:18,450 - Breakthrough helps leading shippers 357 00:15:18,450 --> 00:15:23,130 manage their freight, fuel, and sustainability decisions 358 00:15:23,130 --> 00:15:25,380 with data-driven influence, 359 00:15:25,380 --> 00:15:27,420 really helping them get a better understanding 360 00:15:27,420 --> 00:15:30,210 of what's happening in their transportation. 361 00:15:30,210 --> 00:15:31,740 Much of that here in the North America 362 00:15:31,740 --> 00:15:33,180 sits within Scope three, 363 00:15:33,180 --> 00:15:36,030 meaning they don't have direct visibility to that. 364 00:15:36,030 --> 00:15:39,450 So we are helping

them collect that information, 365 00:15:39,450 --> 00:15:41,550 being able to ingest that into our system 366 00:15:41,550 --> 00:15:44,640 and use that for not only the emissions calculation, 367 00:15:44,640 --> 00:15:47,850 but also for building decarbonization roadmaps 368 00:15:47,850 --> 00:15:49,020 going forward. 369 00:15:49,020 --> 00:15:52,110 And what I would echo is that shift 370 00:15:52,110 --> 00:15:54,540 towards that cross-functional team. 371 00:15:54,540 --> 00:15:56,220 In my world, the decision makers 372 00:15:56,220 --> 00:15:58,290 sit within the operations, transportation, 373 00:15:58,290 --> 00:15:59,700 procurement organization. 374 00:15:59,700 --> 00:16:02,700 Those are the folks that are paying for the solutions 375 00:16:02,700 --> 00:16:04,680 to help them reduce their emissions, 376 00:16:04,680 --> 00:16:07,710 but it needs alignment with the sustainability team. 377 00:16:07,710 --> 00:16:09,900 In addition to that, it's the fact 378 00:16:09,900 --> 00:16:11,850 that the conversation is shifting away 379 00:16:11,850 --> 00:16:15,667 from just calculating and reporting emissions into, 380 00:16:15,667 --> 00:16:17,670 "How do I reduce my emissions? 381 00:16:17,670 --> 00:16:18,960 What is the cost for that? 382 00:16:18,960 --> 00:16:21,810 Who are the carriers that can help me execute that? 383 00:16:21,810 --> 00:16:24,120 And what are the trade-offs that I might have to consider 384 00:16:24,120 --> 00:16:26,430 as I make those choices?" 385 00:16:26,430 --> 00:16:30,080 - So that points to Severine. 386 00:16:30,080 --> 00:16:32,790 We see one of the striking findings in our report 387 00:16:32,790 --> 00:16:35,580 is the increasing use of AI in sustainability, 388 00:16:35,580 --> 00:16:37,560 particularly in the measurement space. 389 00:16:37,560 --> 00:16:40,200 So where do you see are the quickest wins 390 00:16:40,200 --> 00:16:42,210 in your interactions with companies, 391 00:16:42,210 --> 00:16:44,430 and what differentiates companies 392 00:16:44,430 --> 00:16:46,920 that use AI to measure emissions 393 00:16:46,920 --> 00:16:50,850 versus those who use AI to reduce carbon? 394 00:16:50,850 --> 00:16:53,280 - So I will start with one fact. 395 00:16:53,280 --> 00:16:55,620 One of the quick win is unglamorous 396 00:16:55,620 --> 00:16:57,930 because it's working on data. 397 00:16:57,930 --> 00:17:02,160 I'm pretty sure around you, like, the data is quite messy, 398 00:17:02,160 --> 00:17:04,200 unstructured, fragmented, 399 00:17:04,200 --> 00:17:08,280 and scattered around different system, file, and so on. 400 00:17:08,280 --> 00:17:12,660 So what AI does the best is it ingests, 401 00:17:12,660 --> 00:17:15,510 it harmonize those different fragmented data set 402 00:17:15,510 --> 00:17:19,650 that you have, and it fills the gaps where it's missing. 403 00:17:19,650 --> 00:17:22,620 So that's quite the quick win that I see. 404 00:17:22,620 --> 00:17:26,100 Let me share with you a concrete

example. 405 00:17:26,100 --> 00:17:28,470 So we're working with one of the largest 406 00:17:28,470 --> 00:17:30,810 food and beverage company in the world, 407 00:17:30,810 --> 00:17:35,810 and they have about 30,000 material to categorize. 408 00:17:36,990 --> 00:17:41,990 So materials, they are spread across different system, 409 00:17:42,480 --> 00:17:47,480 different country, different formats, and no shared logic. 410 00:17:48,030 --> 00:17:52,170 So every reporting cycle is done by hand, 411 00:17:52,170 --> 00:17:54,390 and you can't carry over 412 00:17:54,390 --> 00:17:57,090 what you have learned from one year to another. 413 00:17:57,090 --> 00:18:00,600 So what we have done, AI has built a model, 414 00:18:00,600 --> 00:18:05,430 and the model is able to judge the sources of the data 415 00:18:05,430 --> 00:18:10,080 to fill the data gap where you need to estimate it, 416 00:18:10,080 --> 00:18:14,220 but also to escalate where it's unclear. 417 00:18:14,220 --> 00:18:15,510 Because at the end of the day, 418 00:18:15,510 --> 00:18:18,840 it's quite important to keep a human in the loop 419 00:18:18,840 --> 00:18:22,710 to make the final decision on which data you want to keep 420 00:18:22,710 --> 00:18:25,050 and which is not the right one. 421 00:18:25,050 --> 00:18:28,470 So to give you a key number to keep in mind, 422 00:18:28,470 --> 00:18:33,090 they had 60% of those 30,000 material categorized. 423 00:18:33,090 --> 00:18:36,713 With that AI model, we were able to bring them to 96%, 424 00:18:38,280 --> 00:18:41,700 which enables them not only to showcase 425 00:18:41,700 --> 00:18:43,500 the effort they have done 426 00:18:43,500 --> 00:18:46,260 in term of recycling their material, 427 00:18:46,260 --> 00:18:51,260 but also to claim that from a packaging and tax liability 428 00:18:51,330 --> 00:18:53,880 when speaking about EPR. 429 00:18:53,880 --> 00:18:58,680 In term of measuring versus reducing here, 430 00:18:58,680 --> 00:19:01,980 I will say it's not a technology gap. 431 00:19:01,980 --> 00:19:04,380 It's more of a mindset gap. 432 00:19:04,380 --> 00:19:06,480 The companies that are coming to us, 433 00:19:06,480 --> 00:19:09,930 either they are looking into data for reporting, 434 00:19:09,930 --> 00:19:13,980 or they are looking into data for decision making. 435 00:19:13,980 --> 00:19:17,310 And let me give you a concrete example with that. 436 00:19:17,310 --> 00:19:19,560 I work a lot with my clients 437 00:19:19,560 --> 00:19:23,070 on how to engage their supply chain. 438 00:19:23,070 --> 00:19:25,863 When you ask your supplier about data, 439 00:19:26,970 --> 00:19:28,730 what is your end goal with it? 440 00:19:28,730 --> 00:19:33,540 Do you only want the data capture the primary related data 441 00:19:33,540 --> 00:19:38,250 for reporting, or do you want to make a decision out of it? 442 00:19:38,250 --> 00:19:40,687 Think of a decision from, 443 00:19:40,687 --> 00:19:44,880 "I want to develop a low-carbon alternative for my material. 444 00:19:44,880 --> 00:19:47,520 I want to redesign it. 445 00:19:47,520 --> 00:19:50,070 I want to have an impact on my packaging." 446 00:19:50,070 --> 00:19:53,070 And for me, I see it a clear benefit. 447 00:19:53,070 --> 00:19:55,380 - My next question is to you, Philippine. 448 00:19:55,380 --> 00:19:57,180 When we hear from senior leaders, 449 00:19:57,180 --> 00:19:58,013 a lot of them say 450 00:19:58,013 --> 00:20:01,050 that they want to invest in sustainability initiatives, 451 00:20:01,050 --> 00:20:04,770 but when those investment decisions go to the CFO, 452 00:20:04,770 --> 00:20:07,560 oftentimes it's about the business case, right? 453 00:20:07,560 --> 00:20:10,350 So what stops companies from transitioning 454 00:20:10,350 --> 00:20:13,170 from climate goals to action today? 455 00:20:13,170 --> 00:20:16,110 Is it because of data and technology challenges, 456 00:20:16,110 --> 00:20:18,270 or is it because they're failing to understand 457 00:20:18,270 --> 00:20:20,880 the economic value of those investments? 458 00:20:20,880 --> 00:20:22,260 - That's a very good question. 459 00:20:22,260 --> 00:20:24,750 It's not a question of technology gap 460 00:20:24,750 --> 00:20:27,960 so much as it is a question of mindset, really, 461 00:20:27,960 --> 00:20:32,280 and whether or not they want to use the data 462 00:20:32,280 --> 00:20:34,230 that they have access to today 463 00:20:34,230 --> 00:20:36,750 through virtual twins, for instance, 464 00:20:36,750 --> 00:20:41,750 or through a generative AI embedded in virtual twins. 465 00:20:41,970 --> 00:20:44,550 It's how they want to use that data. 466 00:20:44,550 --> 00:20:47,760 Are they going to use it in a holistic manner 467 00:20:47,760 --> 00:20:50,790 that allows to embed sustainability 468 00:20:50,790 --> 00:20:53,190 from the design stage of the product 469 00:20:53,190 --> 00:20:55,320 through the production, distribution, 470 00:20:55,320 --> 00:20:58,260 and until the end of life of the product 471 00:20:58,260 --> 00:21:01,020 to ensure that there's more circularity? 472 00:21:01,020 --> 00:21:04,710 Or are they going to use it just to report 473 00:21:04,710 --> 00:21:06,900 how their supplies are doing? 474 00:21:06,900 --> 00:21:10,350 To your point today, what the technology can do, 475 00:21:10,350 --> 00:21:12,120 what virtual twins can do, for instance, 476 00:21:12,120 --> 00:21:16,620 is that they allow you to track and measure 477 00:21:16,620 --> 00:21:19,440 what's going on all through your supply chain. 478 00:21:19,440 --> 00:21:21,630 They allow you to adapt 479 00:21:21,630 --> 00:21:24,900 because the granularity of the data 480 00:21:24,900 --> 00:21:27,600 that you're able to get today means 481 00:21:27,600 --> 00:21:31,650 that you're able to make strategic arbitrage in real time. 482 00:21:31,650 --> 00:21:35,700 And so you can decide to go for one supplier 483 00:21:35,700 --> 00:21:38,700 because it's

going to be more sustainably sourced, 484 00:21:38,700 --> 00:21:40,950 or decide on another material 485 00:21:40,950 --> 00:21:44,580 because it's going to have increased recyclability 486 00:21:44,580 --> 00:21:46,200 at the end of the product. 487 00:21:46,200 --> 00:21:48,030 For instance, for product, 488 00:21:48,030 --> 00:21:51,390 it allows to optimize the weight-material ratio. 489 00:21:51,390 --> 00:21:55,260 So enabling you, when you produce a given product, 490 00:21:55,260 --> 00:21:58,800 to meet your constraints in terms of regulation, 491 00:21:58,800 --> 00:22:00,090 in terms of safety, 492 00:22:00,090 --> 00:22:02,910 in terms of what you want your end product to be, 493 00:22:02,910 --> 00:22:04,590 but at the same time, make sure 494 00:22:04,590 --> 00:22:09,590 that you use the least amount of resource to do that. 495 00:22:09,630 --> 00:22:12,180 And it allows you also to imagine. 496 00:22:12,180 --> 00:22:14,970 So imagine, for instance, new material, 497 00:22:14,970 --> 00:22:17,970 and I think that's where the groundbreaking increase 498 00:22:17,970 --> 00:22:20,520 in sustainability can occur as well, 499 00:22:20,520 --> 00:22:24,180 is through innovation in new materials. 500 00:22:24,180 --> 00:22:25,290 - Rachel, to you. 501 00:22:25,290 --> 00:22:28,230 One of the interesting findings from our study 502 00:22:28,230 --> 00:22:30,450 on the freight decarbonization theme 503 00:22:30,450 --> 00:22:32,730 is the customer and tender requirements 504 00:22:32,730 --> 00:22:36,270 as one of the strongest drivers of freight decarbonization, 505 00:22:36,270 --> 00:22:40,320 68% in North America and 67% in Europe. 506 00:22:40,320 --> 00:22:44,910 However, what we also see is 43% of the companies say 507 00:22:44,910 --> 00:22:46,680 that their fleets run on diesel. 508 00:22:46,680 --> 00:22:51,600 So if there is strong customer drive, 509 00:22:51,600 --> 00:22:54,327 why hasn't the fuel in the tank changed? 510 00:22:54,327 --> 00:22:56,100 And from a shipper point of view, 511 00:22:56,100 --> 00:22:57,540 is it long-term commitments 512 00:22:57,540 --> 00:23:01,590 or higher price for a lower-emission fuel, 513 00:23:01,590 --> 00:23:03,570 or is it something else? 514 00:23:03,570 --> 00:23:05,490 - First, I'll say I'm thinking back 515 00:23:05,490 --> 00:23:07,350 to even probably like three or four years ago 516 00:23:07,350 --> 00:23:10,260 being in rooms like this, specifically on the freight side, 517 00:23:10,260 --> 00:23:11,280 and the conversation 518 00:23:11,280 --> 00:23:14,070 about bringing procurement into the discussion 519 00:23:14,070 --> 00:23:16,290 around sustainability wasn't a best practice 520 00:23:16,290 --> 00:23:17,850 at that point with freight. 521 00:23:17,850 --> 00:23:21,060 And so it's nice to see that this is gaining traction 522 00:23:21,060 --> 00:23:22,920 because I do think it's an important piece. 523 00:23:22,920 --> 00:23:24,630 So I'm with C.H. Robinson. 524 00:23:24,630 --> 00:23:26,310 We are a logistics service provider, 525 00:23:26,310 --> 00:23:28,140 and I say that just to kind of set the stage 526 00:23:28,140 --> 00:23:29,340 for what our business model is, 527 00:23:29,340 --> 00:23:33,060 which is we work with all modes, air, rail, truck. 528 00:23:33,060 --> 00:23:34,080 We're global. 529 00:23:34,080 --> 00:23:36,000 We don't own any of those assets. 530 00:23:36,000 --> 00:23:41,000 And so 99.4% or more of our emissions are Scope three. 531 00:23:42,000 --> 00:23:45,900 And we also work with 90,000 customers a year 532 00:23:45,900 --> 00:23:46,733 that are shippers, 533 00:23:46,733 --> 00:23:48,420 and that's a really, really wide variety. 534 00:23:48,420 --> 00:23:51,330 So again, there's some of them that are very mature 535 00:23:51,330 --> 00:23:54,000 and sophisticated in their sustainability work, 536 00:23:54,000 --> 00:23:55,500 and there's some that they just aren't there. 537 00:23:55,500 --> 00:23:56,880 So there's a big range, 538 00:23:56,880 --> 00:23:57,900 and when I speak to this, 539 00:23:57,900 --> 00:23:58,890 it's going to be kind of the average. 540 00:23:58,890 --> 00:24:00,600 So to your point about the tenders, 541 00:24:00,600 --> 00:24:02,940 there's a whole piece to that 542 00:24:02,940 --> 00:24:04,200 that I think we need to unpack, 543 00:24:04,200 --> 00:24:06,900 which is it's very nice to hear 544 00:24:06,900 --> 00:24:08,400 that you all are seeing more alignment 545 00:24:08,400 --> 00:24:09,630 internally with customers. 546 00:24:09,630 --> 00:24:10,950 I would say that's still a challenge. 547 00:24:10,950 --> 00:24:12,750 We have some customers are great with that, 548 00:24:12,750 --> 00:24:13,890 or shippers are great about that, 549 00:24:13,890 --> 00:24:15,510 but getting that alignment 550 00:24:15,510 --> 00:24:17,737 before you get into the procurement process around, 551 00:24:17,737 --> 00:24:19,440 "What are our priorities, 552 00:24:19,440 --> 00:24:20,970 and what are we actually going after?" 553 00:24:20,970 --> 00:24:22,770 And having the sustainability people 554 00:24:22,770 --> 00:24:24,000 and the transportation people, 555 00:24:24,000 --> 00:24:27,600 and everyone needs to be in the conversation ahead of time. 556 00:24:27,600 --> 00:24:29,130 There's a range in what we're getting asked. 557 00:24:29,130 --> 00:24:30,460 Sometimes it's kind of a, 558 00:24:30,460 --> 00:24:33,330 "Tell us about your sustainability program or policy," 559 00:24:33,330 --> 00:24:34,687 all the way through, 560 00:24:34,687 --> 00:24:37,140 "Price out every single lane you have 561 00:24:37,140 --> 00:24:39,420 for EV or for alternative fuels." 562 00:24:39,420 --> 00:24:42,090 So I think that that can be a really important driver, 563 00:24:42,090 --> 00:24:44,370 and there has to be the follow-on, 564 00:24:44,370 --> 00:24:45,750 which is making sure 565 00:24:45,750 --> 00:24:47,100 that those are asking the right questions, 566

00:24:47,100 --> 00:24:48,633 and then how are you engaging beyond that? 567 00:24:48,633 --> 00:24:52,020 So I just think there's more nuance that needs to happen 568 00:24:52,020 --> 00:24:52,980 beyond just the RFP, 569 00:24:52,980 --> 00:24:54,270 and that's where forums like this 570 00:24:54,270 --> 00:24:55,800 or making sure that you're collaborating 571 00:24:55,800 --> 00:24:58,290 and having discussions with the shippers, with the carriers, 572 00:24:58,290 --> 00:25:01,620 with everyone in the room through whatever venue that is, 573 00:25:01,620 --> 00:25:02,820 is really important. 574 00:25:02,820 --> 00:25:03,660 And it goes beyond 575 00:25:03,660 --> 00:25:05,130 just what the shipper has to be doing too, 576 00:25:05,130 --> 00:25:06,480 like, how are we thinking? 577 00:25:06,480 --> 00:25:10,080 As an LSP, what can we be doing to educate our shippers 578 00:25:10,080 --> 00:25:11,670 and our carriers on what works 579 00:25:11,670 --> 00:25:13,957 so they're not just looking at every single lane, like, 580 00:25:13,957 --> 00:25:15,900 "Here's where the EV could work really well. 581 00:25:15,900 --> 00:25:17,730 Here's where alternative fuels could work really well," 582 00:25:17,730 --> 00:25:19,830 so that we're having more of a strategic conversation 583 00:25:19,830 --> 00:25:21,270 beyond the RFP. 584 00:25:21,270 --> 00:25:23,760 - Heather, to you, my question is, 585 00:25:23,760 --> 00:25:26,043 there are a number of freight decarbonization solutions 586 00:25:26,043 --> 00:25:28,080 that are available out there. 587 00:25:28,080 --> 00:25:31,200 So what do you think should companies focus on? 588 00:25:31,200 --> 00:25:33,900 Should it be a portfolio of those solutions, 589 00:25:33,900 --> 00:25:36,810 or should they look at lane by lane? 590 00:25:36,810 --> 00:25:38,880 - Certainly it's a lane-by-lane choice 591 00:25:38,880 --> 00:25:40,380 with a portfolio of solutions. 592 00:25:40,380 --> 00:25:42,930 There is no one-stop shop when it comes 593 00:25:42,930 --> 00:25:44,790 to alternative energies. 594 00:25:44,790 --> 00:25:49,140 A shipper is moving goods across regions. 595 00:25:49,140 --> 00:25:52,380 They need to understand where their routed lanes 596 00:25:52,380 --> 00:25:55,680 are going to pass by electric charging stations, 597 00:25:55,680 --> 00:25:58,470 where they're going to pass by renewable diesel 598 00:25:58,470 --> 00:26:01,050 fueling stations or renewable natural gas 599 00:26:01,050 --> 00:26:03,000 or compressed natural gas stations. 600 00:26:03,000 --> 00:26:07,620 They can't just use one solution and apply it nationwide 601 00:26:07,620 --> 00:26:10,470 or regional across entire regions. 602 00:26:10,470 --> 00:26:13,500 So that is absolutely a key strategy here, 603 00:26:13,500 --> 00:26:15,570 is being willing to flex 604 00:26:15,570 --> 00:26:17,490 and being willing to use the data 605 00:26:17,490 --> 00:26:20,700 to decide where these opportunities might exist. 606 00:26:20,700 --> 00:26:22,590 A big part of what my team does 607 00:26:22,590 --> 00:26:25,680 is make recommendations for carrier partners 608 00:26:25,680 --> 00:26:28,800 that are executing alternative energy today. 609 00:26:28,800 --> 00:26:31,350 I'm guiding our shippers to ask 610 00:26:31,350 --> 00:26:34,830 more specific questions about alternative energy. 611 00:26:34,830 --> 00:26:36,330 It's important for them to know 612 00:26:36,330 --> 00:26:39,420 if their carrier partners do have sustainability goals, 613 00:26:39,420 --> 00:26:41,280 but what is that going to do 614 00:26:41,280 --> 00:26:43,950 to help them actually reduce their emissions? 615 00:26:43,950 --> 00:26:45,090 Very little. 616 00:26:45,090 --> 00:26:46,260 The questions that a shipper 617 00:26:46,260 --> 00:26:48,517 should be asking carrier partners is, 618 00:26:48,517 --> 00:26:51,270 "Do you invest in alternative energy equipment? 619 00:26:51,270 --> 00:26:53,040 Where do you have this equipment? 620 00:26:53,040 --> 00:26:55,200 Would you be willing to partner with me 621 00:26:55,200 --> 00:26:57,570 on an investment in this space?" 622 00:26:57,570 --> 00:27:01,380 And certainly the longer contract periods 623 00:27:01,380 --> 00:27:03,300 is a key point here. 624 00:27:03,300 --> 00:27:06,360 When a shipper wants to use renewable natural gas 625 00:27:06,360 --> 00:27:09,930 to move goods, that requires a truck with a CNG engine. 626 00:27:09,930 --> 00:27:12,390 There is a premium on those trucks. 627 00:27:12,390 --> 00:27:15,990 So to ask a carrier to invest in that equipment, 628 00:27:15,990 --> 00:27:18,660 it's a big ask, and it's a question that needs to come 629 00:27:18,660 --> 00:27:22,590 with a longer-term commitment on that freight. 630 00:27:22,590 --> 00:27:26,040 So that's a big piece of this strategy. 631 00:27:26,040 --> 00:27:27,600 To use a sports analogy, 632 00:27:27,600 --> 00:27:30,090 people need a lot of at-bats in this space. 633 00:27:30,090 --> 00:27:31,740 They need to practice. 634 00:27:31,740 --> 00:27:34,560 They need to set up the right tracking and audit systems 635 00:27:34,560 --> 00:27:36,330 to be able to identify 636 00:27:36,330 --> 00:27:39,150 where an alternative energy is being used, 637 00:27:39,150 --> 00:27:40,590 what is the feedstock, 638 00:27:40,590 --> 00:27:42,060 what's the right carbon intensity 639 00:27:42,060 --> 00:27:44,820 to be applying on their emissions calculations. 640 00:27:44,820 --> 00:27:46,890 And that's not something that just happens naturally. 641 00:27:46,890 --> 00:27:49,020 It takes effort, it takes planning, 642 00:27:49,020 --> 00:27:51,840 and it takes a strong partnership with the carriers. 643 00:27:51,840 --> 00:27:54,930 So certainly it's going to be a portfolio approach. 644 00:27:54,930 --> 00:27:56,700 - Heather, can I just a follow-on to that? 645 00:27:56,700 --> 00:27:58,500 One thing that I think has also changed 646 00:27:58,500 --> 00:28:00,780 from your

first question over the last 12 to 18 months 647 00:28:00,780 --> 00:28:03,390 is for so long when we would talk to shippers, 648 00:28:03,390 --> 00:28:05,400 they were so dead set on EV, 649 00:28:05,400 --> 00:28:07,260 and that was the only thing they ever wanted to do. 650 00:28:07,260 --> 00:28:10,800 It'd be like, "I need all of my freight on an EV tomorrow." 651 00:28:10,800 --> 00:28:12,690 And then you look at their freight, 652 00:28:12,690 --> 00:28:14,490 and it's in rural Alabama. 653 00:28:14,490 --> 00:28:17,220 And now I feel like shippers are more understanding 654 00:28:17,220 --> 00:28:18,510 of the fact that there are limitations, 655 00:28:18,510 --> 00:28:21,090 and there's a plethora of options that they can talk to, 656 00:28:21,090 --> 00:28:22,530 and that comes from education, 657 00:28:22,530 --> 00:28:23,820 I'm sure from groups like yours as well. 658 00:28:23,820 --> 00:28:25,020 But that has started to shift 659 00:28:25,020 --> 00:28:28,230 that people are seeing kind of more of a portfolio solution. 660 00:28:28,230 --> 00:28:29,097 - 100%. 661 00:28:29,097 --> 00:28:33,390 And I would add, in North America specifically, 662 00:28:33,390 --> 00:28:37,890 I know this was one of the responses in the survey here, 663 00:28:37,890 --> 00:28:40,980 we are still seeing shippers want to take advantage 664 00:28:40,980 --> 00:28:43,740 of alternative energy despite some of the rollbacks 665 00:28:43,740 --> 00:28:46,110 from a federal policy standpoint. 666 00:28:46,110 --> 00:28:48,480 Renewable diesel is the first option that I lean into 667 00:28:48,480 --> 00:28:50,610 with shippers if they're moving any freight 668 00:28:50,610 --> 00:28:53,340 across California, Oregon, and Washington. 669 00:28:53,340 --> 00:28:56,190 Those are LCFS states where the cost of renewable diesel 670 00:28:56,190 --> 00:28:59,610 is typically at parity with ultra-low-sulfur diesel. 671 00:28:59,610 --> 00:29:01,410 Great first solution. 672 00:29:01,410 --> 00:29:06,410 Renewable natural gas is available across the entire US, 673 00:29:06,630 --> 00:29:08,550 also a great solution if they're willing 674 00:29:08,550 --> 00:29:11,700 to make a longer-term commitment with their carriers. 675 00:29:11,700 --> 00:29:14,490 EV, much tougher, as I think everybody knows. 676 00:29:14,490 --> 00:29:17,040 Works really great in port dray situations, 677 00:29:17,040 --> 00:29:20,340 works really great in short-haul situations. 678 00:29:20,340 --> 00:29:23,310 It's a little bit trickier with longer-haul movements 679 00:29:23,310 --> 00:29:25,530 and heavier freight too. 680 00:29:25,530 --> 00:29:28,920 - Philippine, to you, the question is, 681 00:29:28,920 --> 00:29:31,050 companies are increasingly finding 682 00:29:31,050 --> 00:29:33,180 supply chain visibility and traceability 683 00:29:33,180 --> 00:29:35,400 to be less of a challenge. 684 00:29:35,400 --> 00:29:37,200 How do you use digital twins 685 00:29:37,200 --> 00:29:39,210 and other data-driven technologies? 686 00:29:39,210 --> 00:29:43,140 How do you use that to be able to identify the right product 687 00:29:43,140 --> 00:29:46,353 or make better decisions even before the emissions occur? 688 00:29:47,460 --> 00:29:50,400 - Yeah, we can use virtual twins today 689 00:29:50,400 --> 00:29:52,260 at a very granular level. 690 00:29:52,260 --> 00:29:55,830 It really goes at the school level. 691 00:29:55,830 --> 00:29:58,230 It's really super macro, 692 00:29:58,230 --> 00:30:01,320 so you can optimize at every stage. 693 00:30:01,320 --> 00:30:03,870 And today, one of the main argument as well 694 00:30:03,870 --> 00:30:06,060 for moving to more sustainability 695 00:30:06,060 --> 00:30:10,050 is the adaptability to the disruption of the supply chain. 696 00:30:10,050 --> 00:30:11,970 And what we're finding is that 697 00:30:11,970 --> 00:30:16,410 through virtual twins generated with generative AI, 698 00:30:16,410 --> 00:30:18,180 you can actually adapt 699 00:30:18,180 --> 00:30:20,790 to changing circumstances much faster. 700 00:30:20,790 --> 00:30:22,230 In the last 18 months, 701 00:30:22,230 --> 00:30:25,080 because of geopolitical uncertainty mainly, 702 00:30:25,080 --> 00:30:29,700 disruptions to supply chains have increased by 40%. 703 00:30:29,700 --> 00:30:33,300 And so we've had clients turning to us 704 00:30:33,300 --> 00:30:37,980 to help them identify how they can fix those disruption 705 00:30:37,980 --> 00:30:41,430 and how best to be agile and resilient 706 00:30:41,430 --> 00:30:45,390 in reacting and adapting to these changing circumstances. 707 00:30:45,390 --> 00:30:47,460 I think we do have the tools. 708 00:30:47,460 --> 00:30:49,590 What I was saying earlier, it's a question of mindset, 709 00:30:49,590 --> 00:30:53,370 but it's a question as well of knowledge and know-how 710 00:30:53,370 --> 00:30:55,650 and sharing best practices. 711 00:30:55,650 --> 00:30:59,640 Because even if this technology are available 712 00:30:59,640 --> 00:31:02,850 and can have a tremendous impact, 713 00:31:02,850 --> 00:31:06,030 people don't necessarily know about it yet. 714 00:31:06,030 --> 00:31:08,070 And there's a lot of know-how 715 00:31:08,070 --> 00:31:10,020 and knowledge sharing to be done. 716 00:31:10,020 --> 00:31:12,360 - My next question to you, Severine, 717 00:31:12,360 --> 00:31:16,080 we see that the collaboration among companies 718 00:31:16,080 --> 00:31:17,730 to manage their Scope three emissions 719 00:31:17,730 --> 00:31:19,263 have gone up significantly, 720 00:31:20,160 --> 00:31:22,620 but still companies point out supplier data 721 00:31:22,620 --> 00:31:24,030 to be the hardest challenge 722 00:31:24,030 --> 00:31:26,730 when it comes to managing Scope three emissions. 723 00:31:26,730 --> 00:31:30,090 How much of this challenge could AI solve? 724 00:31:30,090 --> 00:31:32,580 And how much of this does it boil down 725 00:31:32,580 --> 00:31:36,510 to building supplier trust,

investing in your supplier, 726 00:31:36,510 --> 00:31:39,090 training them, and things like that? 727 00:31:39,090 --> 00:31:41,100 - I think it's a mix of both. 728 00:31:41,100 --> 00:31:43,650 From a capability point of view, 729 00:31:43,650 --> 00:31:46,320 AI is answering the question. 730 00:31:46,320 --> 00:31:48,900 And let me give you a concrete example. 731 00:31:48,900 --> 00:31:52,260 So when we are working with your customer, 732 00:31:52,260 --> 00:31:54,630 the key to engage supplier, 733 00:31:54,630 --> 00:31:57,780 and especially their low-maturity supplier 734 00:31:57,780 --> 00:32:00,150 whose emission matters, 735 00:32:00,150 --> 00:32:04,977 is to enable them with methodology, tooling, and so on. 736 00:32:04,977 --> 00:32:08,670 And AI is able to answer that. 737 00:32:08,670 --> 00:32:11,100 So we have equipped them with an agent. 738 00:32:11,100 --> 00:32:14,490 Something similar is that a chatbot you're all using 739 00:32:14,490 --> 00:32:16,200 on a day-to-day basis. 740 00:32:16,200 --> 00:32:20,100 Pretty much the supplier is able to feed that agent 741 00:32:20,100 --> 00:32:21,780 with the data that relates 742 00:32:21,780 --> 00:32:23,970 to their product carbon footprint, 743 00:32:23,970 --> 00:32:28,970 bill of material, energy, transportation, and so on. 744 00:32:29,160 --> 00:32:31,740 And the agent will enable them 745 00:32:31,740 --> 00:32:35,520 to compute a PACT-compliant PCF. 746 00:32:35,520 --> 00:32:36,757 You're going to tell me, 747 00:32:36,757 --> 00:32:41,757 "Okay, but then how am I sure I can trust the data?" 748 00:32:41,910 --> 00:32:45,900 Then this is important to have an expert, a human in a loop, 749 00:32:45,900 --> 00:32:49,020 to verify not only the methodology, 750 00:32:49,020 --> 00:32:51,810 but also the accuracy of the data 751 00:32:51,810 --> 00:32:55,380 that they feed the AI agent with. 752 00:32:55,380 --> 00:32:57,840 - My next question is for all the panelists. 753 00:32:57,840 --> 00:33:00,810 We see, of course, AI being increasingly used. 754 00:33:00,810 --> 00:33:05,810 So what it takes from using AI in different use cases 755 00:33:06,090 --> 00:33:08,250 to deploying at scale, right? 756 00:33:08,250 --> 00:33:10,440 Is it data? 757 00:33:10,440 --> 00:33:11,280 Is it governance? 758 00:33:11,280 --> 00:33:12,360 Is it people? 759 00:33:12,360 --> 00:33:16,650 Is it a business case or the broader ecosystem? 760 00:33:16,650 --> 00:33:18,510 - I think it's all of the above, 761 00:33:18,510 --> 00:33:21,510 but more importantly, it's really tangible results. 762 00:33:21,510 --> 00:33:26,510 And I think sustainability, the tracking, the measurement, 763 00:33:26,550 --> 00:33:31,170 the enablement of more holistic strategic decision making 764 00:33:31,170 --> 00:33:34,710 through that tracking and measurement of trustworthy data 765 00:33:34,710 --> 00:33:37,590 and connecting of all the ecosystem means 766 00:33:37,590 --> 00:33:41,910 that sustainability is

a positive AI application. 767 00:33:41,910 --> 00:33:46,910 And for that reason, it's providing tangible results. 768 00:33:47,310 --> 00:33:50,883 And as such, it has a potential to scale quite quickly. 769 00:33:51,750 --> 00:33:53,490 - I think also all of the above. 770 00:33:53,490 --> 00:33:54,870 I mean, that's a really hard one. 771 00:33:54,870 --> 00:33:56,340 They're all such important inputs 772 00:33:56,340 --> 00:33:58,830 to make sure that you're doing this well. 773 00:33:58,830 --> 00:34:02,190 Certainly, the way that C.H. Robinson would think about it 774 00:34:02,190 --> 00:34:04,890 as we start is a business problem 775 00:34:04,890 --> 00:34:06,900 that you're solving is critical first 776 00:34:06,900 --> 00:34:08,460 because you're not getting into hobby AI. 777 00:34:08,460 --> 00:34:09,897 And when we're thinking about sustainability 778 00:34:09,897 --> 00:34:13,060 and the impacts, the net positive, 779 00:34:13,060 --> 00:34:14,730 if you're really focused 780 00:34:14,730 --> 00:34:15,900 on the things that are most important, 781 00:34:15,900 --> 00:34:18,750 that's going to help with the efficient use of it. 782 00:34:18,750 --> 00:34:20,430 I think the governance component is huge 783 00:34:20,430 --> 00:34:21,840 to make sure that you're doing this 784 00:34:21,840 --> 00:34:23,940 in a responsible way from the start. 785 00:34:23,940 --> 00:34:24,773 We're all learning, 786 00:34:24,773 --> 00:34:26,160 but to have something in place 787 00:34:26,160 --> 00:34:28,650 to be able to flex with is huge. 788 00:34:28,650 --> 00:34:30,180 And I think you've said it so many times, 789 00:34:30,180 --> 00:34:32,010 that importance of the human in the loop, 790 00:34:32,010 --> 00:34:34,050 all the process flows that are around that 791 00:34:34,050 --> 00:34:35,580 and the change management with it. 792 00:34:35,580 --> 00:34:36,413 If what you're trying to do 793 00:34:36,413 --> 00:34:40,290 is execute on a broad scale across an enterprise, 794 00:34:40,290 --> 00:34:42,450 having people come along with you is critical. 795 00:34:42,450 --> 00:34:44,130 You need their feedback. 796 00:34:44,130 --> 00:34:46,890 - I think what strikes me about this conversation 797 00:34:46,890 --> 00:34:48,120 is that I actually believe 798 00:34:48,120 --> 00:34:51,570 that AI is a contributor to the collaboration 799 00:34:51,570 --> 00:34:54,600 that we're seeing across teams internally. 800 00:34:54,600 --> 00:34:57,840 So it feeds right back into that initial conversation 801 00:34:57,840 --> 00:35:00,480 that we had about the decision makers, 802 00:35:00,480 --> 00:35:03,180 the procurement, transportation, operations teams 803 00:35:03,180 --> 00:35:05,190 connecting with sustainability. 804 00:35:05,190 --> 00:35:08,400 It facilitates those discussions, answers questions, 805 00:35:08,400 --> 00:35:11,550 gives practical recommendations for options 806 00:35:11,550 --> 00:35:13,890 to reduce emissions in the network. 807 00:35:13,890 --> 00:35:15,600 But on the governance side, 808 00:35:15,600 --> 00:35:18,840 bad data just means bad decisions faster, 809 00:35:18,840 --> 00:35:21,180 which is not a good solution. 810 00:35:21,180 --> 00:35:23,100 So certainly data and governance 811 00:35:23,100 --> 00:35:25,410 is really critical here too. 812 00:35:25,410 --> 00:35:28,050 - To close the loop on that question for me, 813 00:35:28,050 --> 00:35:31,350 I will advise you to keep it narrow. 814 00:35:31,350 --> 00:35:34,590 I mean, AI is unlocking so many use cases, 815 00:35:34,590 --> 00:35:38,010 but don't try to solve it all at once. 816 00:35:38,010 --> 00:35:41,700 You are not doing something over with your company. 817 00:35:41,700 --> 00:35:45,630 So name a problem, name a pain point 818 00:35:45,630 --> 00:35:49,140 where you can drive sustainability impact out of it, 819 00:35:49,140 --> 00:35:54,060 but also bolt your model and look for proof point. 820 00:35:54,060 --> 00:35:56,970 And with that in mind, that direction, 821 00:35:56,970 --> 00:35:58,410 keep in mind three things. 822 00:35:58,410 --> 00:36:00,090 There is this framework 823 00:36:00,090 --> 00:36:03,090 that for me puts quite of a guidance, 824 00:36:03,090 --> 00:36:06,360 is 10% on your algorithm, 825 00:36:06,360 --> 00:36:09,540 20% on your data and technology, 826 00:36:09,540 --> 00:36:12,030 and the remaining 70% 827 00:36:12,030 --> 00:36:14,760 is around the people and the process. 828 00:36:14,760 --> 00:36:17,850 So I echo what my colleague was saying here. 829 00:36:17,850 --> 00:36:20,640 Do not underestimate the change management 830 00:36:20,640 --> 00:36:23,040 that goes with your AI use cases, 831 00:36:23,040 --> 00:36:25,230 but really keep it narrower. 832 00:36:25,230 --> 00:36:27,540 - All right, thank you so much, panelists, 833 00:36:27,540 --> 00:36:29,160 for an insightful discussion. 834 00:36:29,160 --> 00:36:31,525 Thank you so much, everyone, for joining us. 835 00:36:31,525 --> 00:36:34,108 (upbeat music) 836 00:36:36,240 --> 00:36:39,600 - That wraps up this episode of "Supply Chain Frontiers." 837 00:36:39,600 --> 00:36:42,300 A big thank you to the panelists for sharing their expertise 838 00:36:42,300 --> 00:36:43,830 and insights into the current state 839 00:36:43,830 --> 00:36:46,350 of sustainability and supply chain. 840 00:36:46,350 --> 00:36:51,210 To learn more about the lab, visit sustainable.mit.edu. 841 00:36:51,210 --> 00:36:53,250 This episode of "Supply Chain Frontiers" 842 00:36:53,250 --> 00:36:57,330 was recorded live at Climate Week New York City 2026. 843 00:36:57,330 --> 00:37:00,750 Our sound editors are Dave Lashinsky and Danielle Simpson 844 00:37:00,750 --> 00:37:02,730 and David Benjamin Sound. 845 00:37:02,730 --> 00:37:05,310 Our producer is myself, Mackenzie Berry. 846 00:37:05,310 --> 00:37:07,020 Be sure to check out previous episodes 847 00:37:07,020 --> 00:37:12,020 of "Supply Chain Frontiers" at ctl.mit.edu/podcasts 848 00:37:12,840 --> 00:37:15,453 or search for us on your preferred podcast platform. 849 00:37:16,320 --> 00:37:17,460 I'm Mackenzie Berry. 850 00:37:17,460 --> 00:37:18,600 Thanks for listening, 851 00:37:18,600 --> 00:37:21,256 and we'll catch you next time on "Supply Chain Frontiers." 852 00:37:21,256 --> 00:37:23,839 (upbeat music)