Stay Ahead, Stay ONMINE

Facilitating AI integration with simplicity at scale

In partnership withSAP As companies scale, the technology supporting operations can become a liability just as quickly as it becomes an asset. Disconnected systems, site-specific tools, spreadsheets, and manual workarounds can create data silos that make it harder to spot problems early, coordinate responses, and make decisions with confidence. For Jabil, a global manufacturing company with more than 100 sites across more than 30 countries, the answer has been to make integration and simplification a priority. The company adopted a “simplify-first, then-innovate mindset,” says Harish Manohar, SAP IT director at Jabil, recognizing that adding new technologies without first reducing complexity risks creating more risk. The goal is to standardize processes, consolidate where possible, and establish a more consistent data backbone across the organization. “Any innovation without simplification is going to add more complexity,” Manohar says. That philosophy also changes how Jabil approaches modernization. “Any modernization or transformation should add measurable business value,” Manohar says. The company is focused on connecting processes end-to-end across its supply chain and creating a foundation that can scale consistently across regions. Integration comes first because, as Manohar puts it, “the backbone of any contemporary or modern organization is data.” Before organizations can optimize, automate, or apply AI, data needs to flow seamlessly across systems. But doing that across a global organization is hardly straightforward. Jabil’s more than 100 sites operate with different levels of process maturity, legacy systems, and localized workflows, while regulated businesses bring additional compliance requirements. As such, standardizing across different regions and business environments means changing processes and governance without disrupting the operations already in place. The value of that work extends beyond the technology to the people using it. Integrated workflows can offer employees shared visibility into data, reduce manual data reconciliation, and help them move from chasing information to acting on insights. For Jabil, the aim is also to improve real-time visibility into supply chain events, which can enable faster responses to disruptions and reduce operational risk. Looking to the future, that foundation could make AI and automation all the more useful and scalable. With trusted data and integrated systems in place, Jabil is exploring predictive supply chain insights, intelligent exception handling, and AI-driven planning and forecasting. To Manohar, the takeaway is clear: “Simplicity at scale is a very competitive advantage,” and technology investments must ultimately connect to business value and operational resilience. This episode of Business Lab is produced in partnership with SAP. Full Transcript: Megan Tatum: From MIT Technology Review, I’m Megan Tatum, and this is Business Lab, the show that helps business leaders make sense of new technologies coming out of the lab and into the marketplace.Our topic today is enterprise technology integration, and how the benefits of consolidating tools and systems across the supply chain help organizations operate more reliably at scale. When companies reduce tool sprawl and connect their systems more effectively, they gain earlier visibility, faster response, and greater resilience across production lines.My guest today is Harish Manohar, SAP IT Director at Jabil. Jabil has been on a journey to simplify its technology landscape by using SAP Integration Suite as the foundation to connect systems, retire fragmented tools, and enable more consistent operations globally.This podcast is produced in partnership with SAP.Welcome, Harish. Harish Manohar: Hello, Megan. Good morning. Megan: Thank you so much for being here, Harish. Just to start, if we could set some context, can you give us a quick overview of Jabil, the business and its overall transformation journey? Harish: All right. So, about Jabil. Jabil is a global manufacturing company headquartered in St. Petersburg, Florida, USA. We have about 60 years of experience offering comprehensive engineering, supply chain, and manufacturing solutions across different industries. We have a global footprint of about over 100 different sites across 30-plus countries, 140,000-plus employees. We are a trusted partner for more than 400 of the world’s top brands. That’s a little bit about Jabil. Megan: Fantastic. And a lot of scale there, as you’re referring to some of the stats there. As things have got more complex, where did disconnected tools and systems start to slow you down, and what ultimately drove you to make integration a really strategic priority? Harish: I talked about our global footprint across 100-plus sites. With a global footprint always comes complexity about site-specific tools. All of our sites have been in business for a long time, and over the period of years, they had their own tools for their own processes. It’s a little bit disconnected. When we are looking to scale, the first thing we wanted to start looking at is what is this mix of site-specific tools, manual workarounds, spreadsheet-based processes, legacy applications, whatnot? That’s a big technical debt that we have had over the last 25 years. That’s where we started, and that is what led Jabil to make integration a strategic priority because we had limited ability to see issues early across plants, across regions, which would help us to coordinate responses consistently, and also to be able to scale those responses consistently. This complexity created data silos, and in a way delayed robust decision-making. As the complexity increased globally, integration became extremely critical to a few things. It was critical to establishing a single trusted data backbone, which would directly enable faster coordinated responses across the network. We at Jabil, as part of our transformation journey, believe that having the right data at the right time fundamentally changes how we respond to disruptions, which is all about a manufacturing business. How we respond to disruptions. This is where we started our strategic priority towards having a integrated system that drove data consistency across our landscape. Megan: Fantastic. As you have outlined there, there was obviously a real commercial need for this, but how did you think about bringing in those new technologies without adding even more complexity to the mix? Harish: Great question. Whenever we talk about transformation, we talk about all these bleeding-edge technologies that are out there today when it comes to AI and data, cloud, et cetera. But it was very important for us to put a stake in the ground and say and adopt a simplify-first, then-innovate mindset. Because any innovation without simplification is going to add more complexity, just like you mentioned. For us, SAP is our core digital platform. We want to focus on bringing more processes into SAP as much as possible. That is easier said than done because we have been in business for a while, global company, so not all processes exist within SAP at this point in time. We are slowly trying to standardize those processes, and having them under one single source of data would help us scale faster in terms of having data silos. We don’t want data silos across different systems. This is where we started to introduce newer capabilities around SAP. From a cloud standpoint, we have been using SAP’s BTP and Integration Suite, which is proving to be the center stage of all integrations across Jabil. Well, it’s not there yet, but that is the direction that we want to pursue is we don’t want to have a slew of different integration platforms, rather try and see where Integration Suite fits best and where other smaller integration platforms would add more value. Similarly, we have adopted an API-driven, event-based integration approach. That is our best practice that we have put down because we don’t want to keep moving data from one place to the other. That’s not good business practice in the IT world. Most of our integration architectures are API-driven and event-based. That is our focus. Coming back to your new technologies perspective, we want to reuse as much as possible and standardize versus going out and buying these one-off tools that solve for point-in-case use cases. We really don’t want to go down that path. For major processes, we do adopt a best-of-breed approach, but for, let’s say, site-based use cases where a specific site has a particular need for a tool, we try and standardize that and reuse what exists in a different site, for example. There may be some need for a business process change, minor process changes, but that is our direction to make those process changes and reuse what is there already in a different location or a different region. So, that’s one. Lastly, we are heavily aligned with SAP’s clean-core approach when it comes to customization. That has been the challenge for us over the last 25 years where we have been using SAP is our systems are heavily customized because we cater to different customers across the globe. Most of our demands are customer-driven, so we have to put in play these heavy customizations. But now we are taking a pause, and we are saying, “You know what? We have customized so much so far, but now we are moving our systems into RISE, which would enable a clean-core journey in the future.” Now we have to put really good governance criteria and review processes that do not allow heavy customization of our system. We want to move away from that model as much as possible. Again, it’s not easy to do that at this point in time, but there is always a start. Megan: I mean, it sounds like you took a very incremental, intentional approach to this. I mean, as you scaled globally then, what did modernization really look like at the company, and why start with integration? Harish: To that point, we have always looked at transformation, modernization, very objectively. For us, it’s just not about upgrading a system. That’s not what it is. Any modernization or transformation should add measurable business value is our model, is our charter. Having said that, we don’t look at modernization in terms of just upgrades, but in what it gets our business in terms of value. Most of our modernization transformation approaches are focused on connecting processes end-to-end across our supply chain, which is key for our business value. And then we also have a very concerted effort going on in the business community: how to standardize how our plants operate globally. Because, like I mentioned earlier, we have 100-plus plants, different processes, different legal regulations, different countries. It’s very hard for us to come up with one template across the globe, but we are trying to standardize as much as possible. And that’s where we are leveraging SAP’s Signavio, which is our business process management tool. We want to leverage Signavio’s capabilities in helping us standardize these global processes. Now, back to your question, why did integration come first? Because the backbone of any contemporary or modern organization is data. And to get the right data at the right time, integration is the key aspect of the whole optimization exercise. Data needed to flow seamlessly before we start optimizing or automating or even applying AI use cases. This is where integration came first. We wanted to create a single system of record across the operations. Well, when I say “single system of record,” it’s not just SAP, but the ability for us to create those data pipelines across those systems of record being supply chain, planning, inventory, et cetera, et cetera, in that operation space. The result is we want to get to a foundation that helps us scale consistently across our different region. That is our main objective is to, how do we scale as the business grows, as we develop into this bigger organization across different industries? How do we set this foundation that will help us scale consistently? Simplicity, consolidation becomes strategic assets at scale. Megan: Absolutely. And you touched on some of the complexities there of doing this at a scale that Jabil is at with its international footprint. What were some of the biggest challenges in your view in terms of rolling this out across regions, and how did that more standardized approach that you’ve mentioned there help? Harish: Absolutely. I would like to reiterate some of those key challenges I mentioned. One hundred-plus sites, different sites have different maturity levels in terms of how they approach processes. They have a multitude of different legacy systems, localized processes, workarounds, spreadsheets, and the change management that exists within each site is very different. And we do have a footprint of highly regulated businesses. And when it comes to regulated businesses, that comes with its own set of challenges around qualification and CSD processes, et cetera. These are the key challenges that we are up against. Now, the standardization helped us provide consistent workflows, data flows, and governance across sites. Now, we are not there at 100%, but we are working towards that, providing consistent workflows, data pipelines, and governance across sites. And we want to enable faster rollouts of our new bleeding edge technologies. For example, when I talked about SAP’s BTP or SAP Signavio or any other new SAP tool or non-SAP tool, traditionally our ability to deploy those had a challenge around the heavy customization that is required for each and every site. Now, the standardization approach takes that heavy customization out, which enables a faster rollout of those newer technologies. And then lastly, we want to scale across all of our plants. I think initially we want a target of about 40-plus plants with shared processes that are consistent across the different regions. We want to shift from a site-by-site operations model to more of an enterprise-capability approach. Megan: Right, and fascinating. And you touched on the people management aspect of this as well, because obviously this isn’t just about technology, it’s about people too. So, from the employee side, how did this shift to a more simplified landscape change the day-to-day experience for people compared to juggling multiple tools at once? Harish: Great question. And I’ve been hearing direct feedback from our business community on some of these transformation initiatives on how those have changed their daily jobs significantly. Before we embarked on this transformation journey, any employee, any persona. You take a buyer, you take an inventory planner, you take a finance analyst, we go by personas. They had to deal with multiple tools, manual coordination, data reconciliation, especially in the finance space, inconsistent processes across different regions. And then the time spent reconciling data resulted in delay of making decisions, robust decisions. This was the before. But now, since we are moving towards this newer standardization and more of an integration approach, we are able to achieve, to a certain extent, a single integrated workflow across different systems. We have built some key processes that will enable the single integrated workflows across systems. The users, our business community, irrespective of their roles in the organization, have clear visibility and shared data across their teams, which is very important. Earlier, they were dealing with different versions of the data, local workbooks, spreadsheets, and then the time spent talking to each other and reconciling what is the right data? What is the single source of truth? That we are trying to peel away that layer and get to that where the employees don’t have to deal with that kind of complexity. This reduces manual effort and enables faster issue resolution when it comes to actual disruptions. Employees move from chasing information to focusing on acting on insights, which is where I think the new age of AI comes into play. I’ll talk about that in a little bit, but technology becomes an enabler of decision-making, and it’s no more an overhead. That’s where we want to go. Megan: Fantastic. Such an important element of this, isn’t it, that people side of things? And we’ve touched briefly on this idea of value you’ve talked about before, because with an initiative of this scale, ROI is always front and center, of course. What benefits stood out most for you, and how important was better visibility in particular across systems? Harish: Megan, I talked about how modernization and transformation for Jabil means measurable business value, which is directly connected to the ROI. We don’t do any transformation initiatives just because we want to do it from an IT standpoint. Any investment that we make in a transformation or a modernization initiative has to have a deliverable business case that is approved, signed off by business, because that is the only way true transformation happens, if IT and business are a partner as part of this transformation journey. The biggest benefit that we have seen in this initiative is we are striving to reach, attain real-time visibility across our supply chain events. That is the biggest benefit that we see, faster response to disruptions and exceptions. And we are working to reduce our operational risk significantly by operating in this newer model. One example I can give you is the unified workflows that I talked about earlier. It enabled earlier identification of missing materials and faster resolution across our sites. When it comes to a manufacturing company that has a global footprint, materials are the backbone of our whole supply chain process, right? Having a unified workflow, which is able to identify missing materials early in the game, was a game changer for our whole operations community. Real-time analytics allow instant supply chain adjustments without delays. We are focusing a lot on getting analytics, a global analytic footprint in place that allows instant supply chain adjustments without any delays. That’s where AI is going to play a major role currently, and also in the near future. And again, when you talk about visibility. Visibility is not just about reporting what is there in the system. Visibility directly should enable scenario modeling for our users to make strategic adjustments in their processes, which visibility also should make way for proactive decision-making, and also foster business continuity. This is how we look at visibility at Jabil. Megan: Right. And you’re still on this journey, of course, but now that Jabil has a strong integration foundation in place, what does it unlock next for you, and how are you thinking about AI and automation as you’ve touched on a couple of times? Harish: Yeah, we have talked about a couple of times around AI. So, we strongly believe at Jabil, a strong integration foundation enables event-driven, real-time processes, robust decision-making, scalable automation, and all of this enable easier adoption of AI use cases. And again, we are in the new age of AI. We are working towards getting to a AI-enabled enterprise, but having these foundations in place truly fast tracks our approach of AI use cases. Our key focus areas, when I’m thinking about AI and automation in the immediate future, are predictive supply chain insights, intelligent exception handling, which is key to our business operations from a site operation standpoint. Intelligent exception handling is very, very key. On the supply chain side, I talked about predictive insights. That is also absolutely important. All of this enables AI-driven planning and forecasting capabilities. For us, AI should augment true decision-making and robust decision-making, and deliver measurable value, not just experiment AI in use cases. We want to move beyond just experimenting AI in our business processes, but we want that AI that we implement to truly augment the decision-making process that we have, and also deliver key business value. How does all this connect to integration? Integration ensures AI has access to trusted data, and also enables the ability to act across multiple systems in a global company like Jabil. Megan: Fantastic. And if we could just finish, I suppose, with a little bit of advice for others, for other leaders, perhaps, dealing with tool sprawl at the moment, what are some key lessons you would say you’ve learned about prioritizing integration right from the start? Harish: Absolutely. When it comes to tool sprawl, we can go all day about what are the different areas of tool sprawl? For example, application development, we have a multitude of tools; via integration, we have a multitude of tools. Data, we have a multitude of tools, but let’s just focus on integration. That’s the core topic here. I would recommend folks that are in transformative roles in their organizations to start with integration as a foundation and not as an afterthought, right? Prioritize simplification over adding a slew of different tools to address different capabilities. Try and simplify as much as possible before we start your upgrade or your transformation journey. Standardize over locally optimizing tools. Try and get to that. Try and get the business community, your key SMEs in the business space, to understand the value of standardization and simplification of processes and how that enables your business to deliver value faster. Second one, after prioritize: build a single source of truth for data as much as possible. I’m not saying it’s going to be always the case where an organization as in the scale of Jabil will be able to function just with SAP. They’re going to have different systems, but try and get to a model where you’re working with a single source of truth and not locally siloed data sources, right? Next is focus on building a scalable integration architecture. Don’t just confine yourselves to the current state where you are, and build something in place that will only serve you for the next six months to a year. No, that’s not the goal. Anything that you build as an integration architecture should be scalable, and should serve the organization for the next three to five years. That’s how I look at it. When I’m putting in a new architecture pattern or a new event-driven insights, I look at, “Okay, where is Jabil going to be two years, three years down the line? Would this suffice for that scale?” That’s how I look at it. Then focus on outcomes and not just technology. Focus on outcomes: speed, visibility, resilience, and not just technology deployment, because end of the day, IT and business should partner on the business value and not just technology upgrades. Going back, simplicity at scale is a very competitive advantage, and technology investments must tie directly to business value and operational resilience. That’s how we look at Jabil in terms of our tool sprawl and how we prioritize integration right from the start. And that’s what I would suggest to other leaders that are looking to advance in this space. Megan: Fantastic. Brilliant and very comprehensive advice. Thank you ever so much, Harish. And thank you ever so much for joining us. That was Harish Manohar, SAP IT Director at Jabil, whom I spoke with from Brighton in England. That’s it for this episode of Business Lab. I’m your host, Megan Tatum. I’m a contributing editor at Insights, the custom publishing division of MIT Technology Review. We were founded in 1899 at the Massachusetts Institute of Technology, and you can find us in print, on the web, and at events each year around the world. For more information about us and the show, please check out our website at technologyreview.com. This show is available wherever you get your podcasts. And if you enjoyed this episode, we hope you’ll take a moment to rate and review us. Business Lab is a production of MIT Technology Review, and this episode was produced by Giro Studios. Thanks so much for listening. Goodbye. This content was produced by Insights, MIT Technology Review’s custom content arm, not its editorial staff. It was researched and written by humans, with any AI tools that may have been used limited to production processes under human oversight.

In partnership withSAP

As companies scale, the technology supporting operations can become a liability just as quickly as it becomes an asset. Disconnected systems, site-specific tools, spreadsheets, and manual workarounds can create data silos that make it harder to spot problems early, coordinate responses, and make decisions with confidence. For Jabil, a global manufacturing company with more than 100 sites across more than 30 countries, the answer has been to make integration and simplification a priority.

The company adopted a “simplify-first, then-innovate mindset,” says Harish Manohar, SAP IT director at Jabil, recognizing that adding new technologies without first reducing complexity risks creating more risk. The goal is to standardize processes, consolidate where possible, and establish a more consistent data backbone across the organization. “Any innovation without simplification is going to add more complexity,” Manohar says.

That philosophy also changes how Jabil approaches modernization. “Any modernization or transformation should add measurable business value,” Manohar says. The company is focused on connecting processes end-to-end across its supply chain and creating a foundation that can scale consistently across regions. Integration comes first because, as Manohar puts it, “the backbone of any contemporary or modern organization is data.” Before organizations can optimize, automate, or apply AI, data needs to flow seamlessly across systems.

But doing that across a global organization is hardly straightforward. Jabil’s more than 100 sites operate with different levels of process maturity, legacy systems, and localized workflows, while regulated businesses bring additional compliance requirements. As such, standardizing across different regions and business environments means changing processes and governance without disrupting the operations already in place.

The value of that work extends beyond the technology to the people using it. Integrated workflows can offer employees shared visibility into data, reduce manual data reconciliation, and help them move from chasing information to acting on insights. For Jabil, the aim is also to improve real-time visibility into supply chain events, which can enable faster responses to disruptions and reduce operational risk.

Looking to the future, that foundation could make AI and automation all the more useful and scalable. With trusted data and integrated systems in place, Jabil is exploring predictive supply chain insights, intelligent exception handling, and AI-driven planning and forecasting. To Manohar, the takeaway is clear: “Simplicity at scale is a very competitive advantage,” and technology investments must ultimately connect to business value and operational resilience.

This episode of Business Lab is produced in partnership with SAP.

Full Transcript:

Megan Tatum: From MIT Technology Review, I’m Megan Tatum, and this is Business Lab, the show that helps business leaders make sense of new technologies coming out of the lab and into the marketplace.

Our topic today is enterprise technology integration, and how the benefits of consolidating tools and systems across the supply chain help organizations operate more reliably at scale. When companies reduce tool sprawl and connect their systems more effectively, they gain earlier visibility, faster response, and greater resilience across production lines.

My guest today is Harish Manohar, SAP IT Director at Jabil. Jabil has been on a journey to simplify its technology landscape by using SAP Integration Suite as the foundation to connect systems, retire fragmented tools, and enable more consistent operations globally.

This podcast is produced in partnership with SAP.

Welcome, Harish.

Harish Manohar: Hello, Megan. Good morning.

Megan: Thank you so much for being here, Harish. Just to start, if we could set some context, can you give us a quick overview of Jabil, the business and its overall transformation journey?

Harish: All right. So, about Jabil. Jabil is a global manufacturing company headquartered in St. Petersburg, Florida, USA. We have about 60 years of experience offering comprehensive engineering, supply chain, and manufacturing solutions across different industries. We have a global footprint of about over 100 different sites across 30-plus countries, 140,000-plus employees.

We are a trusted partner for more than 400 of the world’s top brands. That’s a little bit about Jabil.

Megan: Fantastic. And a lot of scale there, as you’re referring to some of the stats there. As things have got more complex, where did disconnected tools and systems start to slow you down, and what ultimately drove you to make integration a really strategic priority?

Harish: I talked about our global footprint across 100-plus sites. With a global footprint always comes complexity about site-specific tools. All of our sites have been in business for a long time, and over the period of years, they had their own tools for their own processes. It’s a little bit disconnected.

When we are looking to scale, the first thing we wanted to start looking at is what is this mix of site-specific tools, manual workarounds, spreadsheet-based processes, legacy applications, whatnot? That’s a big technical debt that we have had over the last 25 years. That’s where we started, and that is what led Jabil to make integration a strategic priority because we had limited ability to see issues early across plants, across regions, which would help us to coordinate responses consistently, and also to be able to scale those responses consistently. This complexity created data silos, and in a way delayed robust decision-making.

As the complexity increased globally, integration became extremely critical to a few things. It was critical to establishing a single trusted data backbone, which would directly enable faster coordinated responses across the network. We at Jabil, as part of our transformation journey, believe that having the right data at the right time fundamentally changes how we respond to disruptions, which is all about a manufacturing business. How we respond to disruptions. This is where we started our strategic priority towards having a integrated system that drove data consistency across our landscape.

Megan: Fantastic. As you have outlined there, there was obviously a real commercial need for this, but how did you think about bringing in those new technologies without adding even more complexity to the mix?

Harish: Great question. Whenever we talk about transformation, we talk about all these bleeding-edge technologies that are out there today when it comes to AI and data, cloud, et cetera. But it was very important for us to put a stake in the ground and say and adopt a simplify-first, then-innovate mindset. Because any innovation without simplification is going to add more complexity, just like you mentioned.

For us, SAP is our core digital platform. We want to focus on bringing more processes into SAP as much as possible. That is easier said than done because we have been in business for a while, global company, so not all processes exist within SAP at this point in time. We are slowly trying to standardize those processes, and having them under one single source of data would help us scale faster in terms of having data silos. We don’t want data silos across different systems.

This is where we started to introduce newer capabilities around SAP. From a cloud standpoint, we have been using SAP’s BTP and Integration Suite, which is proving to be the center stage of all integrations across Jabil. Well, it’s not there yet, but that is the direction that we want to pursue is we don’t want to have a slew of different integration platforms, rather try and see where Integration Suite fits best and where other smaller integration platforms would add more value.

Similarly, we have adopted an API-driven, event-based integration approach. That is our best practice that we have put down because we don’t want to keep moving data from one place to the other. That’s not good business practice in the IT world. Most of our integration architectures are API-driven and event-based. That is our focus.

Coming back to your new technologies perspective, we want to reuse as much as possible and standardize versus going out and buying these one-off tools that solve for point-in-case use cases. We really don’t want to go down that path. For major processes, we do adopt a best-of-breed approach, but for, let’s say, site-based use cases where a specific site has a particular need for a tool, we try and standardize that and reuse what exists in a different site, for example. There may be some need for a business process change, minor process changes, but that is our direction to make those process changes and reuse what is there already in a different location or a different region. So, that’s one.

Lastly, we are heavily aligned with SAP’s clean-core approach when it comes to customization. That has been the challenge for us over the last 25 years where we have been using SAP is our systems are heavily customized because we cater to different customers across the globe. Most of our demands are customer-driven, so we have to put in play these heavy customizations.

But now we are taking a pause, and we are saying, “You know what? We have customized so much so far, but now we are moving our systems into RISE, which would enable a clean-core journey in the future.” Now we have to put really good governance criteria and review processes that do not allow heavy customization of our system. We want to move away from that model as much as possible. Again, it’s not easy to do that at this point in time, but there is always a start.

Megan: I mean, it sounds like you took a very incremental, intentional approach to this. I mean, as you scaled globally then, what did modernization really look like at the company, and why start with integration?

Harish: To that point, we have always looked at transformation, modernization, very objectively. For us, it’s just not about upgrading a system. That’s not what it is. Any modernization or transformation should add measurable business value is our model, is our charter. Having said that, we don’t look at modernization in terms of just upgrades, but in what it gets our business in terms of value.

Most of our modernization transformation approaches are focused on connecting processes end-to-end across our supply chain, which is key for our business value. And then we also have a very concerted effort going on in the business community: how to standardize how our plants operate globally. Because, like I mentioned earlier, we have 100-plus plants, different processes, different legal regulations, different countries. It’s very hard for us to come up with one template across the globe, but we are trying to standardize as much as possible. And that’s where we are leveraging SAP’s Signavio, which is our business process management tool. We want to leverage Signavio’s capabilities in helping us standardize these global processes.

Now, back to your question, why did integration come first? Because the backbone of any contemporary or modern organization is data. And to get the right data at the right time, integration is the key aspect of the whole optimization exercise. Data needed to flow seamlessly before we start optimizing or automating or even applying AI use cases. This is where integration came first.

We wanted to create a single system of record across the operations. Well, when I say “single system of record,” it’s not just SAP, but the ability for us to create those data pipelines across those systems of record being supply chain, planning, inventory, et cetera, et cetera, in that operation space.

The result is we want to get to a foundation that helps us scale consistently across our different region. That is our main objective is to, how do we scale as the business grows, as we develop into this bigger organization across different industries? How do we set this foundation that will help us scale consistently? Simplicity, consolidation becomes strategic assets at scale.

Megan: Absolutely. And you touched on some of the complexities there of doing this at a scale that Jabil is at with its international footprint. What were some of the biggest challenges in your view in terms of rolling this out across regions, and how did that more standardized approach that you’ve mentioned there help?

Harish: Absolutely. I would like to reiterate some of those key challenges I mentioned. One hundred-plus sites, different sites have different maturity levels in terms of how they approach processes. They have a multitude of different legacy systems, localized processes, workarounds, spreadsheets, and the change management that exists within each site is very different. And we do have a footprint of highly regulated businesses. And when it comes to regulated businesses, that comes with its own set of challenges around qualification and CSD processes, et cetera. These are the key challenges that we are up against.

Now, the standardization helped us provide consistent workflows, data flows, and governance across sites. Now, we are not there at 100%, but we are working towards that, providing consistent workflows, data pipelines, and governance across sites. And we want to enable faster rollouts of our new bleeding edge technologies. For example, when I talked about SAP’s BTP or SAP Signavio or any other new SAP tool or non-SAP tool, traditionally our ability to deploy those had a challenge around the heavy customization that is required for each and every site. Now, the standardization approach takes that heavy customization out, which enables a faster rollout of those newer technologies.

And then lastly, we want to scale across all of our plants. I think initially we want a target of about 40-plus plants with shared processes that are consistent across the different regions. We want to shift from a site-by-site operations model to more of an enterprise-capability approach.

Megan: Right, and fascinating. And you touched on the people management aspect of this as well, because obviously this isn’t just about technology, it’s about people too. So, from the employee side, how did this shift to a more simplified landscape change the day-to-day experience for people compared to juggling multiple tools at once?

Harish: Great question. And I’ve been hearing direct feedback from our business community on some of these transformation initiatives on how those have changed their daily jobs significantly. Before we embarked on this transformation journey, any employee, any persona. You take a buyer, you take an inventory planner, you take a finance analyst, we go by personas. They had to deal with multiple tools, manual coordination, data reconciliation, especially in the finance space, inconsistent processes across different regions. And then the time spent reconciling data resulted in delay of making decisions, robust decisions. This was the before.

But now, since we are moving towards this newer standardization and more of an integration approach, we are able to achieve, to a certain extent, a single integrated workflow across different systems. We have built some key processes that will enable the single integrated workflows across systems. The users, our business community, irrespective of their roles in the organization, have clear visibility and shared data across their teams, which is very important. Earlier, they were dealing with different versions of the data, local workbooks, spreadsheets, and then the time spent talking to each other and reconciling what is the right data? What is the single source of truth? That we are trying to peel away that layer and get to that where the employees don’t have to deal with that kind of complexity.

This reduces manual effort and enables faster issue resolution when it comes to actual disruptions. Employees move from chasing information to focusing on acting on insights, which is where I think the new age of AI comes into play. I’ll talk about that in a little bit, but technology becomes an enabler of decision-making, and it’s no more an overhead. That’s where we want to go.

Megan: Fantastic. Such an important element of this, isn’t it, that people side of things? And we’ve touched briefly on this idea of value you’ve talked about before, because with an initiative of this scale, ROI is always front and center, of course. What benefits stood out most for you, and how important was better visibility in particular across systems?

Harish: Megan, I talked about how modernization and transformation for Jabil means measurable business value, which is directly connected to the ROI. We don’t do any transformation initiatives just because we want to do it from an IT standpoint. Any investment that we make in a transformation or a modernization initiative has to have a deliverable business case that is approved, signed off by business, because that is the only way true transformation happens, if IT and business are a partner as part of this transformation journey.

The biggest benefit that we have seen in this initiative is we are striving to reach, attain real-time visibility across our supply chain events. That is the biggest benefit that we see, faster response to disruptions and exceptions. And we are working to reduce our operational risk significantly by operating in this newer model.

One example I can give you is the unified workflows that I talked about earlier. It enabled earlier identification of missing materials and faster resolution across our sites. When it comes to a manufacturing company that has a global footprint, materials are the backbone of our whole supply chain process, right? Having a unified workflow, which is able to identify missing materials early in the game, was a game changer for our whole operations community.

Real-time analytics allow instant supply chain adjustments without delays. We are focusing a lot on getting analytics, a global analytic footprint in place that allows instant supply chain adjustments without any delays. That’s where AI is going to play a major role currently, and also in the near future.

And again, when you talk about visibility. Visibility is not just about reporting what is there in the system. Visibility directly should enable scenario modeling for our users to make strategic adjustments in their processes, which visibility also should make way for proactive decision-making, and also foster business continuity. This is how we look at visibility at Jabil.

Megan: Right. And you’re still on this journey, of course, but now that Jabil has a strong integration foundation in place, what does it unlock next for you, and how are you thinking about AI and automation as you’ve touched on a couple of times?

Harish: Yeah, we have talked about a couple of times around AI. So, we strongly believe at Jabil, a strong integration foundation enables event-driven, real-time processes, robust decision-making, scalable automation, and all of this enable easier adoption of AI use cases. And again, we are in the new age of AI. We are working towards getting to a AI-enabled enterprise, but having these foundations in place truly fast tracks our approach of AI use cases.

Our key focus areas, when I’m thinking about AI and automation in the immediate future, are predictive supply chain insights, intelligent exception handling, which is key to our business operations from a site operation standpoint. Intelligent exception handling is very, very key. On the supply chain side, I talked about predictive insights. That is also absolutely important. All of this enables AI-driven planning and forecasting capabilities.

For us, AI should augment true decision-making and robust decision-making, and deliver measurable value, not just experiment AI in use cases. We want to move beyond just experimenting AI in our business processes, but we want that AI that we implement to truly augment the decision-making process that we have, and also deliver key business value.

How does all this connect to integration? Integration ensures AI has access to trusted data, and also enables the ability to act across multiple systems in a global company like Jabil.

Megan: Fantastic. And if we could just finish, I suppose, with a little bit of advice for others, for other leaders, perhaps, dealing with tool sprawl at the moment, what are some key lessons you would say you’ve learned about prioritizing integration right from the start?

Harish: Absolutely. When it comes to tool sprawl, we can go all day about what are the different areas of tool sprawl? For example, application development, we have a multitude of tools; via integration, we have a multitude of tools. Data, we have a multitude of tools, but let’s just focus on integration. That’s the core topic here.

I would recommend folks that are in transformative roles in their organizations to start with integration as a foundation and not as an afterthought, right? Prioritize simplification over adding a slew of different tools to address different capabilities. Try and simplify as much as possible before we start your upgrade or your transformation journey. Standardize over locally optimizing tools. Try and get to that. Try and get the business community, your key SMEs in the business space, to understand the value of standardization and simplification of processes and how that enables your business to deliver value faster.

Second one, after prioritize: build a single source of truth for data as much as possible. I’m not saying it’s going to be always the case where an organization as in the scale of Jabil will be able to function just with SAP. They’re going to have different systems, but try and get to a model where you’re working with a single source of truth and not locally siloed data sources, right?

Next is focus on building a scalable integration architecture. Don’t just confine yourselves to the current state where you are, and build something in place that will only serve you for the next six months to a year. No, that’s not the goal. Anything that you build as an integration architecture should be scalable, and should serve the organization for the next three to five years. That’s how I look at it. When I’m putting in a new architecture pattern or a new event-driven insights, I look at, “Okay, where is Jabil going to be two years, three years down the line? Would this suffice for that scale?” That’s how I look at it.

Then focus on outcomes and not just technology. Focus on outcomes: speed, visibility, resilience, and not just technology deployment, because end of the day, IT and business should partner on the business value and not just technology upgrades.

Going back, simplicity at scale is a very competitive advantage, and technology investments must tie directly to business value and operational resilience. That’s how we look at Jabil in terms of our tool sprawl and how we prioritize integration right from the start. And that’s what I would suggest to other leaders that are looking to advance in this space.

Megan: Fantastic. Brilliant and very comprehensive advice. Thank you ever so much, Harish. And thank you ever so much for joining us. That was Harish Manohar, SAP IT Director at Jabil, whom I spoke with from Brighton in England.

That’s it for this episode of Business Lab. I’m your host, Megan Tatum. I’m a contributing editor at Insights, the custom publishing division of MIT Technology Review. We were founded in 1899 at the Massachusetts Institute of Technology, and you can find us in print, on the web, and at events each year around the world. For more information about us and the show, please check out our website at technologyreview.com.

This show is available wherever you get your podcasts. And if you enjoyed this episode, we hope you’ll take a moment to rate and review us. Business Lab is a production of MIT Technology Review, and this episode was produced by Giro Studios. Thanks so much for listening. Goodbye.

This content was produced by Insights, MIT Technology Review’s custom content arm, not its editorial staff. It was researched and written by humans, with any AI tools that may have been used limited to production processes under human oversight.

Shape
Shape
Stay Ahead

Explore More Insights

Stay ahead with more perspectives on cutting-edge power, infrastructure, energy,  bitcoin and AI solutions. Explore these articles to uncover strategies and insights shaping the future of industries.

Shape

Palo Alto Networks buys Console to boost agentic security

“We built Console around a simple idea: people should be able to express an operational goal, and intelligent software should handle the complexity required to achieve it,” said Console CEO and co-founder Andrei Serban in a statement. “Our customers have already proven that agents can dramatically slash overhead and transform

Read More »

Mainframe shops tap AI for system insights and recommendations

After much discussion, planning and investment, the mainframe community is moving from “AI enthusiasm to pragmatic adoption,” according to the report: “AI has moved from experimentation to strategic planning, with mainframe organizations seeming to take a more pragmatic approach,” the report states. “That pragmatism is visible in the kinds of

Read More »

Energy Secretary Saves Coal-Fired Generation from Going Offline in Florida

WASHINGTON—U.S. Secretary of Energy Chris Wright today issued an emergency order to keep affordable, reliable, and secure coal generation online and address critical grid reliability issues in Florida. The emergency order directs the Orlando Utilities Commission (OUC) to ensure that Unit 1 at the Stanton Energy Center (Stanton) in Orlando, Florida, a coal-fired power plant remains available to operate. Unit 1 was slated to enter a premature extended cold shutdown in June 2026. “Taking reliable generation offline compromises energy reliability and needlessly raises energy costs for Americans,” Secretary Wright said. “The Trump Administration will continue to ensure that Floridians have access to affordable, reliable, and secure energy to power their homes.” As outlined in DOE’s Resource Adequacy Report, power outages could increase by 100 times in 2030 if the U.S. continues to take reliable power offline. Thanks to President Trump’s leadership, coal plants across the country are being saved from premature retirement and reversing plans to shut down. In 2025, more than 17 gigawatts of coal-powered electricity generation were saved from going offline. This order is in effect beginning on September 2, 2026, through November 30, 2026.                                                                                             ###

Read More »

Energy Department Announces National Petroleum Council Report to Unlock America’s Vast Energy Resources

WASHINGTON — The U.S. Department of Energy’s (DOE) Office of Hydrocarbons and Geothermal Energy today announced the release of the National Petroleum Council’s (NPC) American Resources for a Secure Future: A National Cooperative Subsurface Assessment Program report, which provides recommendations to strengthen America’s understanding of its vast subsurface resources and support expanded domestic energy and mineral development. Requested by DOE, the report examines opportunities to improve how the United States assesses, characterizes, and manages its subsurface resources—including oil and natural gas, geothermal energy, critical minerals, coal, geologic hydrogen, and underground storage—through stronger public-private coordination, modern data systems, advanced technologies, and workforce development.  The report advances President Trump’s commitment to restore American energy dominance by reducing unnecessary barriers to resource development and to deliver affordable, reliable, and secure energy for the American people. “The United States possesses extraordinary subsurface resources that are fundamental to our nation’s energy security, economic prosperity, and industrial competitiveness,” said DOE Under Secretary of Energy Kyle Haustveit. “The National Petroleum Council’s report provides an important framework for strengthening our understanding of the subsurface and advancing the technologies needed to unlock its full potential. These recommendations will help DOE advance President Trump’s agenda to unleash American energy, strengthen domestic supply chains, and secure our nation’s energy future.” The report identifies five key areas to strengthen America’s ability to assess and develop its subsurface resources: Strengthen National Coordination. The report recommends establishing a more coordinated national approach to subsurface resource assessments through stronger collaboration among federal and state agencies, Tribal governments, academia, and industry, supported by a long-term planning process to identify national priorities.  Modernize Data. It emphasizes expanding federal-state data acquisition efforts, improving public access to geological information through a national data portal, preserving valuable legacy data, and evaluating opportunities to responsibly improve access to industry data that

Read More »

DOE Selects Community Partners to Receive Waste to Energy and Materials Recovery Technical Assistance

WASHINGTON—The U.S. Department of Energy’s Alternative Fuels and Feedstocks Office (AFFO) and the National Laboratory of the Rockies (NLR) have selected recipients for the FY26 Waste to Energy and Materials Technical Assistance program. Through this program, NLR will provide free guidance to state, local, and Tribal governments to use new technologies that turn waste into energy or recover valuable materials like critical minerals.  The program aims to help local officials create sensible solutions for their waste management issues, fill knowledge gaps, and plan and carry out implementation approaches that fit their communities. This year, the program has expanded to include additional municipal solid waste streams like electronics, industrial wastewater, and other byproducts.  Now in its sixth year, the technical assistance program has supported 67 entities in 31 states and territories. FY26 selections include: Community Name American Samoa Power Authority City of Boise, Idaho Cherokee Nation Natural Resources, Oklahoma Village of Coal Valley, Illinois Guam Energy Office Hudson Valley Regional Council, New York Kodiak Island Borough, Alaska Los Angeles County Public Works, California Metlakatla Indian Community, Arkansas Township of Montclair, New Jersey City of New Bedford, Massachusetts Oregon Department of Energy, Oregon South Central Regional Council of Governments, Connecticut Thompson Township, Pennsylvania Ulster County Resource Recovery Agency, New York Washington State Department of Commerce, Office of Renewable Fuels To learn more about the technical assistance program, visit NLR’s Waste to Energy and Materials Technical Assistance for State, Local, and Tribal Governments webpage. If you have questions, please see frequently asked questions or contact the Waste to Energy and Materials Technical Assistance Team.

Read More »

Santos targets Q4 2026 FID for Papua LNG plant

Santos Ltd. is on track to take fourth-quarter 2026 final investment decision (FID) on the 5.6 million tonne/year (tpy) Papua LNG plant at Caution Bay, Papua New Guinea, with project financing and government-led development discussions advancing. At plateau, Papua LNG would contribute about 1 million tpy of Santos equity LNG and roughly 11 million boe/year of equity oil, the company said in its first-half 2026 earnings report and call. Papua LNG would use 4 million tpy of production from new electric liquefaction trains and as much as 2 million tpy of tolling production from ExxonMobil Corp.’s already operating 8-million tpy PNG LNG plant, in which Santos is also a partner. Santos recently took FID on its PNG LNG oil infill drilling campaign, and expects to start drilling fourth-quarter 2026. Santos said it has several options to backfill PNG LNG production if Papua LNG does not proceed but emphasized that all parties remain focused on reaching a Papua LNG FID this year. The company cited Muruk, P’nyang, and Usano as possible resources for such backfill. Muruk has estimated natural gas resources of 1-3 tcf and P’nyang estimated recoverable reserves of 4.36 tcf. Usano, in the PD-L2 production license area, is primarily an oil project, with an estimated 85 million bbl of oil in place but would produce associated gas as well. Santos plans to drill a test well on it in early 2028. TotalEnergies SE holds 40.1% interest in Papua LNG and it the project’s operator. ExxonMobil holds 37.1% interest, with Santos and the state holding the bulk of the balance. Santos equity is 17.7-22.8% depending on government exercise of its back-in rights. ENEOS (formerly JX Nippon) holds a minor participating interest.

Read More »

North American rig count drops 8 units, erasing last week’s gain

The rig count in North America is down 8 units this week, according to data from Baker Huges Inc. With 804 rigs running across North America for the week ended Aug. 21, the drop erased the previous week’s 8-unit gain. There were 5 fewer rigs drilling in the US this week for a total of 588. The count is 50 more than were drilling during the same period last year. A 2-unit drop in offshore rigs left 10 working this week. One fewer rig was drilling in inland waters, leaving 2 still working. The number of rigs drilling on land decreased by 2 to 576. That count is up 53 from the same period in 2025. Three fewer rigs were oil-directed in the US and its waters this week for a total of 452. There were 127 gas-directed rigs working, down one from last week. The number of unclassified rigs working this week decreased by 1 unit to 9. Of the major US oil and gas producing states, Texas saw the largest increase. Four rigs were added to the state’s total this week to bring the count to 281, 41 more than were drilling during the same period last year. New Mexico and Louisiana each dropped 3 rigs to end the week with counts of 96 and 35, respectively. Wyoming’s rig count fell by a single unit this week to leave 9 rigs working. The overall rig count in Canada fell by 3 units to 216. The count is up 36 units from this time a year ago. Of those 216 rigs working, 148 were drilling for oil, down 3 from last week. The number of gas-directed rigs in Canada was unchanged at 65. Three units were unclassified, unchanged from last week.

Read More »

Ring’s 2027 target: 10% growth for 10% less

Boosted by an increase in horizontal drilling across its Central Basin Platform (CBP) operations, the leaders of Ring Energy Inc., The Woodlands, Tex., expect a big pop in the company’s 2027 financials. Speaking Aug. 18 at the EnerCom Denver conference, chairman and chief executive officer Paul McKinney said the Permian basin-focused operator has “an incredible runway of high-return opportunities” in the CBP using technologies refined by operators in the Midland and Delaware basins on either side of Ring’s holdings. Recent developments, he said, have made it easier for Ring and others active in the CBP, which has shallower reservoirs, to drill longer wells. Two years ago, half of the wells Ring drilled were horizontal. This year, that figure is on pace to be 81%. The length of new wells is similarly shifting to being at least 1.5 miles: In 2024, new wells of that length accounted for only 5% of Ring’s activity but that will be 70% this year. Those advancements are set to create a big payoff for Ring, which had total production of just under 20,000 boe/d in the second quarter. “The capital is kind of the story,” McKinney told EnerCom attendees. “We believe that we will deliver 10% production growth for 10% less capital in 2027 […] All this means meaningful upside in adjusted free cash flow. It means a significant increase in earnings.”

Read More »

VMware by Broadcom: Product, service and support news

Customer concerns loom as VMware Explore event approaches Aug. 19, 2024: This year’s VMware Explore marks the first time for the flagship customer event since Broadcom finalized its acquisition of VMware last November. Enterprise customers have questions about VMware’s future direction, licensing changes, and product roadmap following Broadcom’s takeover. Customers want to continue to see innovation across the VMware portfolio, says one analyst. They also want to see Broadcom focus on integration, interface design, and an easier adoption path.  Broadcom distrust drives sales for VMware competition Aug. 14, 2024: Concerns about the new direction VMware is taking are driving some enterprise customers to consider alternative platforms from vendors such as Scale Computing, Nutanix and Oxide Computer. Scale Computing said in its most recent quarterly earnings announcement that sales have taken off and its new customers have doubled over the past year, thanks in part to Broadcom’s changes to VMware sales operations. Nutanix hunts disgruntled VMware customers July 01, 2024: Nutanix began aggressively courting VMware customers who might be open to jumping ship in the wake of VMware’s purchase by Broadcom and some of the unpopular moves that followed. In addition, Nutanix recently signed key partnerships with some unlikely on-and-off competitors: Dell, Cisco and HPE.  Broadcom tosses VMware users a bone, extends vSphere 7 support six months July 25, 2024: Broadcom has announced that VMware vSphere 7.x users will get six additional months of support for the product. VMware vSphere 7, which was launched in 2020, was scheduled to go out of support in April 2025 but will now be maintained until October 2025. Broadcom bolsters VMware Edge Compute Stack June 26, 2024: A slew of updates in VMware ECS 3.5 are aimed at helping customers more easily manage edge devices, applications, and infrastructure across multiple locations. Updates include zero-touch orchestration capabilities, pull-based architecture, and edge

Read More »

AMD Helios Takes AI Infrastructure Fight to Rack Scale

AMD is escalating its challenge to Nvidia with Helios, a rack-scale AI system that puts the company squarely into the race to define how the next generation of AI factories are built. Unveiled in production form at AMD’s Advancing AI 2026 event in San Francisco, Helios combines 72 Instinct MI455X GPUs with sixth-generation EPYC “Venice” CPUs, Pensando networking and AMD’s ROCm software stack. The significance goes beyond another generation of faster accelerators. Like Nvidia’s Vera Rubin platform, Helios treats the rack as an integrated compute system in which GPUs, CPUs, memory, networking, power delivery and cooling increasingly have to be engineered together. For data center operators, that means the competitive battle between the two chip companies is moving directly into infrastructure design. AMD said Helios is now in production, with deployments beginning during the second half of 2026. The Rack Becomes the System Helios is built around AMD’s Instinct MI455X, a liquid-cooled accelerator based on the company’s CDNA 5 architecture and equipped with HBM4 memory. A complete Helios rack delivers 72 GPUs along with EPYC host CPUs and Pensando networking for front-end, scale-up and scale-out traffic. AMD is positioning the platform for both large-scale training and increasingly important inference workloads. AMD says Helios can deliver up to 30% more inference tokens per dollar than a competing system. The company also claims the MI455X provides more peak AI compute and substantially greater memory capacity than Nvidia’s Rubin GPU. Those numbers are AMD benchmarks rather than independent comparisons. But the larger architecture may matter more than the percentages. AI infrastructure is rapidly moving beyond the model of servers being installed as largely independent pieces of IT equipment. Accelerators have to exchange enormous volumes of data with each other while CPUs orchestrate workloads and networking connects increasingly large clusters across rows, halls and

Read More »

Moses Lake Moves From Bitcoin to AI and HPC

Moses Lake and the Quincy Effect Moses Lake should not be understood as an isolated rural data center project. It sits within the larger Grant County infrastructure ecosystem that helped make nearby Quincy one of the defining hyperscale markets of the cloud era. Keel has called Moses Lake “adjacent to one of the most proven data center markets in the United States,” noting that hyperscale infrastructure has operated around Quincy for nearly two decades. In its Q1 remarks, management argued that increasingly constrained regional power leaves operators seeking incremental Pacific Northwest capacity with fewer options. The Grant County Economic Development Council’s data center inventory includes Microsoft, NTT Data, Sabey, Vantage, Intuit and other operators. The organization counts more than 1.5 million square feet of data center operations in the county and points to a diverse fiber network and Grant County PUD’s Columbia River hydroelectric resources as core advantages. That existing cluster changes the equation for an 18-MW project. The headline AI developments of 2026 are increasingly measured in hundreds of megawatts or gigawatts. But another market exists underneath those megacampus announcements: operators that need tens of megawatts in the right geography on a timeline measured in quarters rather than many years. An 18-MW facility with power, fiber, equipment and construction underway can therefore be strategically more relevant than its relatively modest capacity suggests. Keel had previously secured an option for another 10 MW near Moses Lake, but management said during its second-quarter call that it has relinquished that option and is now focused exclusively on the existing 18 MW. The decision further distinguishes Moses Lake from the industry’s race to advertise ever-larger pipelines. This project is about getting capacity online. A Second Life for Crypto Power That may ultimately be the larger Moses Lake story. Bitcoin miners assembled portfolios around

Read More »

ISE Expo 2026: DCF Takes Stage with JLL, TIA

AI Infrastructure’s New Calculus: Speed, Quality and the Race to Revenue NASHVILLE — The defining question in data center development has become brutally simple: How quickly can a site get to revenue? Power availability sits at the center of that calculation. But as AI pushes development into new geographies and compresses construction schedules, an increasingly complicated set of infrastructure dependencies sits behind the megawatts — equipment, suppliers, construction capacity, fiber, optical connectivity, workforce and the quality systems needed to make all of it work reliably. That tension framed a Data Center Frontier-led fireside discussion at EndeavorB2B’s ISE Expo 2026 between Sean Farney, Vice President of Data Center Strategy at JLL, and Dave Stehlin, CEO of the Telecommunications Industry Association (TIA). The conversation began with a new data center quality initiative. It quickly expanded into something larger: an examination of what happens when time to revenue becomes the organizing principle for an entire infrastructure industry. “There is absolutely, positively no room for pause right now,” Farney said. DCE 9000 Meets the AI Buildout For TIA, the answer begins with a problem Google brought to the association last year. According to Stehlin, Google was seeing recurring quality and delivery problems among operational technology suppliers — the companies providing equipment such as generators, cooling systems and other physical infrastructure required to make a data center operate. TIA responded by developing DCE 9000, or Data Center Excellence 9000, a third-party-certifiable quality management standard for the data center infrastructure supply chain. Stehlin said more than 70 companies are now participating in the effort, ranging from hyperscalers and data center operators to major infrastructure manufacturers. The first draft is expected in September. That is an unusually compressed development cycle for an industry standard. “Typically standards take five years to get implemented,” Stehlin said. “In nine months, we’re

Read More »

The Phantom Data Center Effect: When Perception Precedes Project Reality

Moving Beyond Speculation The answer is not simply earlier marketing campaigns or more aggressive public relations programs. Effective engagement requires understanding local concerns, motivations and political dynamics—and recognizing when community opposition reflects a durable constraint rather than a communications problem. We need to realize when no means no, and not interpret it as “try harder.” Phantom perception also can’t be handled by any one operator in any one market; this must be a collective, such as a crowd-sourced data platform, market by market. What our industry needs are clearer frameworks for evaluating digital infrastructure against these additional community-readiness criteria, because speculation is increasingly filling information gaps before formal projects reach the public process. Organizations such as OIX have begun working toward that objective. Its Digital Infrastructure Framework is modeled on traditional master planning and is intended to help communities evaluate what infrastructure they have, what they need and what they want as they plan for future technology requirements. The framework includes assessment criteria spanning investment readiness, policy, risk, sustainability and resilience. Greater transparency can narrow the gap between perception and reality. But greater transparency will not eliminate speculation, and unfortunately, it also won’t eliminate fear. Large infrastructure projects have always attracted public interest and scrutiny, and data centers are unlikely to become invisible again as AI demand accelerates. The question is how the industry responds to that visibility. The Next Stage of Data Center Development Community reaction to perceived data center development represents another potential source of site-selection intelligence. If communities begin reacting to a project before a developer has formally advanced one, that response can offer an early indication of whether a market is receptive to large-scale digital infrastructure or already approaching its political limit. This gives operators and investors another axis to measure: not just megawatts, fiber routes,

Read More »

Corvex Tests a Faster Path to Liquid-Cooled AI Infrastructure

The customer agreement expanded an earlier commitment and includes dedicated high-speed storage and CPUs in addition to GPUs. Corvex initially delivered capacity during the first quarter and continued deployment through the second and third quarters. By its Aug. 14 earnings update, the company said the multi-year Blackwell agreement had been fully delivered. Corvex reported approximately $22 million in contracted annualized recurring revenue from compute that was live and accepted by customers. The expansion was financed through debt, customer prepayments and cash on hand rather than additional equity issuance. But the most noteworthy aspect of the project may be the deployment itself. Corvex installed high-density, liquid-cooled NVIDIA HGX B200 systems inside an existing air-cooled data center and says it commissioned the capacity approximately two weeks after the equipment arrived. Instead of rebuilding the facility around a central liquid-cooling system, Corvex worked with Lenovo to use Lenovo Neptune liquid-to-air cooling technology. Liquid removes heat from the servers and transfers it to the existing air-cooled facility infrastructure. The cluster uses Lenovo ThinkSystem systems equipped with NVIDIA HGX B200 GPUs, NVIDIA Quantum-2 QM9700 InfiniBand for GPU traffic, NVIDIA Spectrum SN5600 switches for storage networking and SN2201 switches for management traffic. Corvex says the design allowed it to place high-density Blackwell infrastructure into the existing facility without a conventional facility-wide liquid-cooling conversion. Lenovo, in a case study of the deployment, contrasts the approximately two-week commissioning period with what it describes as typical data center upgrade timelines of seven to 12 months or more. That has significance beyond a single cluster. Power availability and suitable data center capacity increasingly constrain GPU deployment. If the approach proves repeatable, liquid-to-air cooling could allow some existing air-cooled facilities with sufficient power and other supporting infrastructure to accommodate higher-density AI systems without first undergoing a full central liquid-cooling conversion. For

Read More »

Microsoft will invest $80B in AI data centers in fiscal 2025

And Microsoft isn’t the only one that is ramping up its investments into AI-enabled data centers. Rival cloud service providers are all investing in either upgrading or opening new data centers to capture a larger chunk of business from developers and users of large language models (LLMs).  In a report published in October 2024, Bloomberg Intelligence estimated that demand for generative AI would push Microsoft, AWS, Google, Oracle, Meta, and Apple would between them devote $200 billion to capex in 2025, up from $110 billion in 2023. Microsoft is one of the biggest spenders, followed closely by Google and AWS, Bloomberg Intelligence said. Its estimate of Microsoft’s capital spending on AI, at $62.4 billion for calendar 2025, is lower than Smith’s claim that the company will invest $80 billion in the fiscal year to June 30, 2025. Both figures, though, are way higher than Microsoft’s 2020 capital expenditure of “just” $17.6 billion. The majority of the increased spending is tied to cloud services and the expansion of AI infrastructure needed to provide compute capacity for OpenAI workloads. Separately, last October Amazon CEO Andy Jassy said his company planned total capex spend of $75 billion in 2024 and even more in 2025, with much of it going to AWS, its cloud computing division.

Read More »

John Deere unveils more autonomous farm machines to address skill labor shortage

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Self-driving tractors might be the path to self-driving cars. John Deere has revealed a new line of autonomous machines and tech across agriculture, construction and commercial landscaping. The Moline, Illinois-based John Deere has been in business for 187 years, yet it’s been a regular as a non-tech company showing off technology at the big tech trade show in Las Vegas and is back at CES 2025 with more autonomous tractors and other vehicles. This is not something we usually cover, but John Deere has a lot of data that is interesting in the big picture of tech. The message from the company is that there aren’t enough skilled farm laborers to do the work that its customers need. It’s been a challenge for most of the last two decades, said Jahmy Hindman, CTO at John Deere, in a briefing. Much of the tech will come this fall and after that. He noted that the average farmer in the U.S. is over 58 and works 12 to 18 hours a day to grow food for us. And he said the American Farm Bureau Federation estimates there are roughly 2.4 million farm jobs that need to be filled annually; and the agricultural work force continues to shrink. (This is my hint to the anti-immigration crowd). John Deere’s autonomous 9RX Tractor. Farmers can oversee it using an app. While each of these industries experiences their own set of challenges, a commonality across all is skilled labor availability. In construction, about 80% percent of contractors struggle to find skilled labor. And in commercial landscaping, 86% of landscaping business owners can’t find labor to fill open positions, he said. “They have to figure out how to do

Read More »

2025 playbook for enterprise AI success, from agents to evals

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 is poised to be a pivotal year for enterprise AI. The past year has seen rapid innovation, and this year will see the same. This has made it more critical than ever to revisit your AI strategy to stay competitive and create value for your customers. From scaling AI agents to optimizing costs, here are the five critical areas enterprises should prioritize for their AI strategy this year. 1. Agents: the next generation of automation AI agents are no longer theoretical. In 2025, they’re indispensable tools for enterprises looking to streamline operations and enhance customer interactions. Unlike traditional software, agents powered by large language models (LLMs) can make nuanced decisions, navigate complex multi-step tasks, and integrate seamlessly with tools and APIs. At the start of 2024, agents were not ready for prime time, making frustrating mistakes like hallucinating URLs. They started getting better as frontier large language models themselves improved. “Let me put it this way,” said Sam Witteveen, cofounder of Red Dragon, a company that develops agents for companies, and that recently reviewed the 48 agents it built last year. “Interestingly, the ones that we built at the start of the year, a lot of those worked way better at the end of the year just because the models got better.” Witteveen shared this in the video podcast we filmed to discuss these five big trends in detail. Models are getting better and hallucinating less, and they’re also being trained to do agentic tasks. Another feature that the model providers are researching is a way to use the LLM as a judge, and as models get cheaper (something we’ll cover below), companies can use three or more models to

Read More »

OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has taken a more aggressive approach to red teaming than its AI competitors, demonstrating its security teams’ advanced capabilities in two areas: multi-step reinforcement and external red teaming. OpenAI recently released two papers that set a new competitive standard for improving the quality, reliability and safety of AI models in these two techniques and more. The first paper, “OpenAI’s Approach to External Red Teaming for AI Models and Systems,” reports that specialized teams outside the company have proven effective in uncovering vulnerabilities that might otherwise have made it into a released model because in-house testing techniques may have missed them. In the second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning,” OpenAI introduces an automated framework that relies on iterative reinforcement learning to generate a broad spectrum of novel, wide-ranging attacks. Going all-in on red teaming pays practical, competitive dividends It’s encouraging to see competitive intensity in red teaming growing among AI companies. When Anthropic released its AI red team guidelines in June of last year, it joined AI providers including Google, Microsoft, Nvidia, OpenAI, and even the U.S.’s National Institute of Standards and Technology (NIST), which all had released red teaming frameworks. Investing heavily in red teaming yields tangible benefits for security leaders in any organization. OpenAI’s paper on external red teaming provides a detailed analysis of how the company strives to create specialized external teams that include cybersecurity and subject matter experts. The goal is to see if knowledgeable external teams can defeat models’ security perimeters and find gaps in their security, biases and controls that prompt-based testing couldn’t find. What makes OpenAI’s recent papers noteworthy is how well they define using human-in-the-middle

Read More »