This Whisper Report investigates what jobsite tech boosts output most today? At CONEXPO‑CON/AGG, practitioners surface where productivity truly moves—beyond hype—highlighting overlooked levers shaping cycle time, safety, and uptime this year. Read on for the signals that matter now. Cited experts: Nate Jones (Weir–Esco Division), Christopher Sommer (MOBA Automation), Joel Honeyman (Doosan Bobcat), Nicolas Legrand (John Deere).
“This Whisper Report investigates where AI most often fails in ones supply chain. It synthesizes expert perspectives gathered at Manifest 2026 on the recurring breakdown points. Areas affected span logistics and operations, including real‑time data limitations, challenges translating analytics into actionable decisions, and the need for measurable business value. The report incorporates insights from Asendia’s Michael Lorentzen, Rufus Lab’s Gabe Grifoni, and Aptean Supply Chain’s Allan Dow.”
“This Whisper Report investigates what mobile tech trend will blindside CIOs next? Researched on‑site at MWC in Las Vegas, it brings together firsthand perspectives from mobility leaders shaping the next wave of disruption. Insights include GetWireless’ Anthony Besett, Comfone’s Randall Peterson, Canoga Perkins’ Siddharth Khattar, and Schneider Electric’s Katie Boeh, each offering a distinct view into the forces set to catch CIOs off‑guard.”
Target Audience Titles:
Chief Technology Officer, Chief Information Officer, Chief Digital Officer, Chief Innovation Officer
Director of Mobility Strategy, Director of Network & Edge Systems, Director of Wireless Architecture, Product Manager Connected Platforms
Mobile Systems Engineer, Edge/IoT Integration Engineer, Wireless Network Engineer, Firmware & Device Engineer
Key Takeaways
Many CIOs will be blindsided by delaying 5G modernization as networks and modules evolve rapidly.
Travel eSIMs will radically simplify international roaming and cut global mobility costs.
Exploding densities of mobile and robotic assets will outpace current enterprise readiness.
IT–OT misalignment on power and infrastructure planning will create critical edge‑computing bottlenecks.
We took the most frequently asked and most urgent technology questions straight to the mobility and wireless experts gathering at the MWC Las Vegas held at the Fontainebleau. This Whisper Report addresses the question regarding what mobile tech trend will blindside CIOs next as depicted in Figure 1.
Figure 1. Mobile trends that will blindside CIOs next
With more than five years since 5g started rolling out it is easy to ignore the trend of moving to 5G yet many organizations are not paying attention to its growing maturity. As GetWireless’ Anthony Besett denoted, “Potentially not moving to 5G soon enough is going to blindside a lot of CIOS, right? Just because, the industry is evolving really fast. The module manufacturers are pumping out new modules all the time, telling SEC are leading that charge. But more than that is the also the carriers. Their networks are changing and they’re rapidly evolving and they’re moving fast. And so not moving our solutions and not moving new designs to that soon enough it’s definitely going to blindside them.” If you have not yet updated our strategies and architectures to accommodate and leverage all 5g has to offer, be sure to schedule your inquiry with your TBW Advisors LLC analyst.
Does your organization have team members regularly traveling international? If so, managing roaming costs is a common fiscal nightmare. Hopefully this positive blindside revealed by Comfone’s Randall Peterson will make your day. “Travel eSIMs in the roaming business. It’s going to change how people roam internationally. Is going to change how people get their service.” Imagine the same rates as if you bought a disposable phone with local access SIM in every location you travelled? Now image that flexibility without the complexity of sending your teams to a store every time they land in a new country due to software and programmable SIMS?
One blind spot heading like a freight train towards many Chief Information and Chief Technology Officers is highlighted by Canoga Perkins’ Siddharth Khattar. “The fact that so many of the assets and so many of our sensors and everything that we want to work with are actually going to be mobile. We talk about robotics so much and I see that you know in other countries in Asia for instance there are you know people are talking about a density of robots of 500 plus for every 10,000 manufacturing workers in China today when we look at those numbers in the US and in Europe we’re so far behind we’re at about 300 plus 350 robots as compared to 500 plus in other areas.”
But the incoming massive density of connected assets is not the only concern. These assets coming in from the information technology (IT) side but also the operations technology (OT) side as we saw during our research on the Commercial UAV Expo. There is one huge problem. As Schneider Electric’s Katie Boeh highlighted, “The IT side doesn’t necessarily talk to the facility side that may manage their data center infrastructure if they have a legacy on premise data center. And what happens is, hey, we’re making this new technological advancement or we’re making this big investment. can you get me x amount of kilowatts of power and it’s going to be in this form factor in this rack. Those conversations need to start happening earlier because most data centers like legacy brown what we call brownfield data centers don’t have the capacity or maybe even the architecture and power distribution and cooling architecture to support a very high density powered load that’s associated with an AI solution especially like a training solution.”
IT not knowing about OT’s incoming data storage requirements and OT not knowing about IT’s power requirements. OT and IT not communicating is unfortunately a very common trend across all interfaces and integration points between the two parts of an organization. But this problem is magnified in the world of mobility. Katie explained further. “There are analysts in our industry that talk about how by 2030, 50% of the power consumption could be at the edge. What we call the edge as in not in the mega data centers. So think about that, right? How huge we know that these data centers are and how much power they consume and it’s in the news. You hear about it all of a sudden. People who have nothing to do with the data center industry know about these giant data centers. But what they might not realize is that even with all of that that is known, there’s going to be just as much power being consumed at the edge across lots of different devices. So I think that’s something that CIOS need to be prepared for when they’re thinking about their strategy. Is it hybrid? Is it all in the cloud? Is it some combination? Regardless, you need to understand what the power requirements are going to be and you need to start bringing in your facilities people that are responsible for answering those questions of do we have the capacity? What’s possible? Bring them in soon.”
That’s correct. If you are a tech leader, the power problem is also yours to ensure it is solved. Power engineers, engineers in OT, and the engineers in IT all want the same thing. To delight the company’s customers with a successfully working product and/or service. That takes everyone keeping all in the loop from the beginning.
“This Whisper Report investigates what AI breakthrough will transform patient care next. Researched on‑site at CES 2026 in Las Vegas, it explores how AI is reshaping patient care through personalization and continuous insights. The report brings forward perspectives from Dentomi’s Dr. Chun Wang, PointFit’s Kenny Octavius, and Abbott’s Alexander Davies, each emphasizing how individualized measurements and daily health data are transforming how patients understand their conditions and make healthier decisions.”
“This Whisper Report address the question regarding the best practices for integrating AI and ML into our security Systems. It highlights how leaders emphasize protecting PII, using selective data movement, optimizing hardware, choosing the right models, and knowing when AI should not be applied. Insights come from LVT’s Steve Lindsey, Safr’s John Cassise, 360 Privacy’s Trinity Davis, Intel’s Mike Nielsen, RightCrowd’s Jason Bohrer, Bioconnect’s Edsel Shreve, Vaidio’s Marshall Tyler, and Databuoy’s Kathleen Griggs. “
Target Audience Titles:
Chief Technology Officer, Chief Security Officer, Chief Information and Security Officer, Chief Trust Officer, Chief Compliance Officer, Chief Risk Officer
Head of Product, VP of Product, Chief Marking Officer, Data Protection Officer,
Enterprise Architect, Director of Data Protection, Director of Data Governance, Chief Privacy Officer
Key Takeaways
Protect PII rigorously, as regulations vary widely and AI accelerates exposure risks.
Use selective data movement and confidential computing to minimize PII transfer and strengthen security.
Apply the three‑way test: AI must improve speed, accuracy, or cost efficiency to justify deployment.
Choose NDAA‑compliant, learning‑capable hardware to ensure secure and adaptive edge performance.
We took the most frequently asked and most urgent technology questions straight to the cyber physical security experts gathering at ISC West 2025. This Whisper Report addresses the question regarding what are the best practices for integrating AI and machine learning into our security systems as depicted in Figure 1. Just in case anyone is not sure that AI has a place in security, LVT’s Steve Lindsey said it best, “physical security and the problems and threats we’re dealing with are just increasing and increasing the problem is our budgets to deal with those are staying the same so the mathematical equation says that we have to do more with less.” It’s a matter of simple math. Since we are dealing with the cyber physical world at ISC West, we will start with cautions specifically regarding PII information (personally identifiable information) and then highlight best practice recommendations.
When it comes to the cyber physical security world and AI, one must keep in mind that some data is PII data. One cannot do anything with AI unless the PII data is protected. As Safr’s John Cassise called out, “we are talking about PII so that means that we’re dealing with people’s personal information and this is a situation that that changes from state to state sometimes even county to county so you need to have a platform that is flexible enough to accommodate.” At the same time, keep in mind as 360 Privacy’s Trinity Davis cautions, “we’re super concerned about AI. AI is actually bit driven by Big Data we’re actually seeing a lot of these language models actually turn up they expedite the process in which somebody can identify your PII.” Thus, the environment for PII is dynamic that varies by location while at the same time is increasingly under attack due to AI.
Safr’s John Cassise was quick to point out that it is about, “how we transmit data? Is it secured? Is it secure at rest in transit but also do I have the flexibility to decide that this particular piece of information isn’t necessary so I don’t need to move that around my system?” To that we would like to remind clients and subscribers, it is possible to do better than only encryption at rest and in transit. Specifically, it is possible to also be secure while computing leveraging confidential computing available in most public clouds. For additional research on confidential computing see, Industry Whispers: Public is Private – Confidential Computing in the Cloud | TBW ADVISORS.
In terms of selecting what data to move, Cassise goes on to further explain, “for instance the human readable face I don’t necessarily need to move for my system to operate so do I choose an a variation that allows me to not move that around but just the biometric signature.” This approach is also supported by Intel RealSense’s Mike Nielsen. “Authentication without distributing PII.. about 512 bytes that’s irreversible back to a human image now I would then go back to that camera it would evaluate me again generate a new template and then we compare those templates so we’re not comparing my face we’re comparing a template generated as 80 points and the relational distances of those points on my face.” While this is part of the standard, we heard about it often during our coverage for Conference Whispers: ISC West 2025 but did not hear about it during our coverage for Conference Whispers: Identiverse 2025. That said, once I inquired if the PII information was transferred to the badge or a hash – all confirmed the solutions kept to the standard.
LVT’s Steve Lindsey got right to the point in terms of how he recommends selecting AI projects. “It has to make things faster, more accurate, and lower cost and if technology isn’t solving one of those three questions, then it’s really not useful to us.” Now those are three business problems most organizations can appreciate. As we have repeatedly advised, AI project must solve business problems – it is not just about using ‘AI’. If you are unsure if your project is a great candidate to solve with current technology, be sure to schedule your inquiry so a TBW Advisors expert can advise you appropriately.
RightCrowd’s Jason Bohrer recommends the ever-growing area of Agentic AI with a bit of caution. “There’s a lot of unique opportunities around how you best adopt some of the agent capabilities associated with AI right. It all has to be controlled and approved through the proper channels to make sure you’re driving efficiency, but it also has the proper approval processes associated with it too and we also have Incorporated that some of that into our platform as well.” Before one can dive into Agentic AI, one’s processes must be optimized and data cleaned. If this challenge is your Mt. Everest, be sure to schedule your inquiries with your analyst. At TBW Advisors we offer a lot of firsthand experience and expertise in process optimization and the creation and optimization of advanced data mesh.
If your hardware can compromise your solution, this is a problem anywhere in IT. In the cyber physical world where the hardware can be located out on remote edges, hardware selection becomes even more critical. As Safr’s John Cassise stated, “number one we need to make sure that we’re using chipsets that are NDAA compliant right because we’re talking about privacy and we can’t be using chips from Chinese manufacturers that potentially are giving vulnerabilities.” But the hardware can do more than just stay compliant and secure. As Bioconnect’s Edsel Shreve declared, “these devices .. are learning devices they have an NPU chip whether you call it API AI or machine learning one of the things these devices do is every single time you use them they’re actually improving the template they’re learning and so over time you just get a stronger and stronger template.”
The best practice in any organization is to leverage existing organizational assets. For example, as Bioconnect’s Edsel Shreve explains, “We see AI tools and machine learning coming into place is taking all of the telemetry and data from these systems right just in terms of just this performance of the system or any issues about how they react on a network if servers or readers are dropping offline.” Leveraging existing organizational data particularly telemetry data, is a great practice for any organization. It is important to ensure the data has quality before looking for patterns or making decisions based on the data.
One great practice when deploying AI within your organization particularly in the space of cyber physical security is ensuring the ROI. Specifically, as LVT’s Steve Lindsey pointed out, “what AI is helping us to be able to do is to start being a force multiplier for our people. And it doesn’t limit itself to just computer vision models being able to detect things. There has to be intelligence that consumes those detections and now can intelligently make a decision on what should I do with this. As intelligence gets smarter it can actually help deter and do things for us before humans get
involved in fact at LVT we find that up to 90% of the time an effective deterrence that is believable will get the person to go away which means that five 5 to 10% of the time we’re dealing with somebody who’s desperate or not lucid and they’re going to do it anyway.” Only bothering human security agents in 10% of the incidents when they are needed? That will enable staff to do more with less.
Selecting the best model for your use case sounds like an obvious best practice but it is more nuanced than one might think. As Viadio’s Marshall Tyler articulated, “technology takes different resources and there are a lot of different models out there you want tried and true model optimization based on your needs for how accurate how quickly and how cost effectively you want to be able to respond to different types of incidents. Technology takes different resources and there are a lot of different models out there. You want tried and true model optimization based on your needs for how accurate how quickly and how cost effectively you want to be able to respond to different types of incidents.” Its about accommodating the entire solution needs and how a given model fits into the solution requirements.
Kathleen Griggs from Databuoy shared a brilliant best practice regarding the use of AI for security. “When it comes to a life safety situation, we’ve designed our system to get it right. To filter it out based on physics and what we know about the signal and that’s where we feel like it’s not the best place to put AI really.” In other words, when the exact precise math of physics can give you an exact answer, why use AI to approximate. This is particularly true in life and death scenarios.
We often advise, it is never about if a specific model meets your needs. AI models will fail. It is about bringing together a collection of models to achieve the solution. It is always about the soluton succeeding. One valuable model to add into a solution is one that can identify behaviors. As Intel’s Mike Nielsen reportedv, “we’re seeing the industry do now is using some of the same techniques to
identify behaviors and objects and “ in the context of physical security to identify bad stuff that could be happening is it actually a gun that’s that there’s a high fidelity way to determine a weapon by looking at a weapon against a database of weapons behaviors like am I reaching for a gun that’s a much lower fidelity thing to do but it still allows Security Professionals to act and respond if a machine detects that somebody may be taking something out of a pocket that they should be doing so those same techniques that we apply to facial Biometrics we are seeing the same techniques being applied in the industry to detect objects detect behaviors and then detect emotions pull those three together and evaluate what action should be taken as a result.”
A true best practice for layering together various models or algorithms is one commonly referred to as CNNs. As Intel’s Mike Nielsen highlighted, “we apply convolutional neural networks which is a classic but Advanced technique of evaluating an image through layers partitioning that to multiple algorithms to determine things like is it a human being face is that face an actual person is it a mask are they wearing glasses are they wearing a hat are they wearing a Covid mask and we use multiple layering technique with CNNs that allows the machine to learn exactly what is on the face is it an actual face and then applying additional techniques to determine whose face it belongs to.”
Last but definitely not least, Vaidio’s Marshall Tyler gave some really sound advice for a must follow best practice. “It’s really important you’re looking at one the pedigree of the company that’s been doing the AI. Is this something they just started are they trying to use fancy new Technologies? Make sure that you’re thinking about how fast you can get answers, how accurate those answers are, how efficiently and cost effectively you can drive those answers.” TBW Advisors LLC has witnessed countless examples of AI projects that wasted millions and months because they didn’t work with someone with extensive true experience. Reduce your risk and increase your success by scheduling your inquiry with your TBW Advisors expert to get the best advise available before charging ahead.
“This Whisper Report investigates how Gen AI will reshape enterprise finance operations. Researched on‑site at Money 20/20 USA 2025 in Las Vegas, it examines how financial operations are evolving under accelerating automation and intelligence. The report highlights perspectives from AutoRek’s Nicholas Botha, Veratad’s Thomas Canfarotta, Globant’s Erin StillWell, Oracle’s James Calise, Zoominfo’s Brandon Tucker, localpayment’s Ezequiel Israel, and IPQS’ Shea Craft.”
We took the most frequently asked and most urgent technology questions straight to the fintech professionals gathering at the Sands Convention Center in Las Vegas for Money 20/20 USA 2025. This Whisper Report addresses the question regarding how GenAI will reshape enterprise finance ops as depicted in Figure 1.
AutoRek’s Nicholas Botha brings us the first change noticed in financial operations. “Training your teams and members to be able to utilize this (GenAI) to save your teams time and doing the mundane activity is really where it’s going to add value.” Many look forward to getting rid of the mundane and burdensome tasks. Veratad’s Thomas Canfarotta couldn’t agree more. “We’re seeing amazing strides with Gemini’s ability to do these laborious processes that have taken long amounts of time with lots of people and being able to automate them.” In fact, Thomas had some very specific tasks in mind. “And this includes onboarding and identity verification.”
Globant’s Erin Stillwell revealed an exciting result of GenAI in Fintech. “It could also be the standpoint of agents being embedded into different teams to accelerate outcomes.” Erin went on to further explain. “If you think through from a finance op standpoint, especially from an enterprise perspective, there’s multiple systems internally likely multiple databases. to even document files, data warehouses and all of that can really be consistent or brought together with AI and different tools to streamline, create dashboards, automate and really take the manual piece out of it and have smarter intelligence with decisions that the executives need to make.”
Oracle’s James Calise highlights that GenAI is. “Changing the interface that we’ve grown to know.”
James further demonstrated his point. “Where the interface has always been a web browser or a mobile phone, this is the next leap where the chat experience and really taking it to the next level with agents working on our behalf is going to completely revamp how we think about inter interacting with enterprise technology. It’s no longer going to be you asking to you know you going to a website to go and perform a function. That function is going to be happening automatically based on events in real time empowered through you know your conversation and chat.”
Perhaps one of the most exciting aspects was shared by Zoominfo’s Brandon Tucker. “More than ever, it’s critical to get your data foundation correct.” Brandon further contended, “Right now, people are under the belief that AI is just going to solve all those problems for them, but it really won’t be able to um without getting that foundational unified data model correct.” Many organizations have been doing band aid transformations and never took the time to truly establish an enterprise data fabric. If this is feeling a little too familiar be sure to book your inquiry with your TBW Advisors LLC analysts immediately. We can walk you through step-by-step enabling you to leverage our firsthand experience event if you have outsourced the work.
Sometimes perspective in the industry helps one recognize how an industry is reshaping as illustrated by localpayment’s Ezequiel Israel. “When I started payments 10 years, 15 years ago, the regular normal SLA (service level agreement) was about 2 or 3 days. Today, people are expecting payments to complete in two or three minutes.” If a customer expects something in minutes versus days, the enterprise and its infrastructure must evolve or the customers will simply go elsewhere to have their expectations met.
Our sixth and final impact on financial ops coming from GenAI comes to us from IPQS’ Shea Craft. Put simply, it’s “the velocity of abuse is increasing, the barrier of entry for abuse and fraud, and sort of legacy, sort of methods where somebody doesn’t know how to program, somebody doesn’t know where to go for, you know, committing fraud or abuse is getting a lot easier. you know, using fraud as a service, platforms, things like that, just make it a lot more accessible.”
Published to clients: February 24, 2026 ID: TBW2115
Published to Whisper Club: February 24, 2026
Analyst(s): Dr. Doreen Galli
Photojournalist(s): Dr. Doreen Galli
Abstract:
“This Whisper Report investigates how will AI change warehouse architecture. Researched at the Retail, Supply Chain and Logistics Expo in Las Vegas, it highlights how AI boosts worker guidance, accelerates operations, improves predictive decisions, and reshapes automation across physical and digital systems. It also stresses fragmented tech stacks and future robot‑centric warehouse design. Quoted: Steve Harris (Warehouse Craft), Priya Katyal (PGS360), Petros Dertsakyan (oloround), Rodrigo Hernandez (Bazarup), Sean Elmurib (Backops AI), Naushad Ahmed (MetaOption), Ingo Pietruska (Lufthansa).”
Chief Technology Officer, Chief Information Officer, Chief Supply Chain Officer, VP of Warehouse Operations, Director of Logistics Strategy, Head of Automation & Robotics
Machine Learning Engineer, Applied Scientist, Robotics Engineer, Computer Vision Engineer, Data Engineer, Data Scientist, AI Solutions Developer, Automation Controls Engineer, Embedded Systems Engineer, Platform Engineer, AI Agent Developer
We took the most frequently asked and most urgent technology questions straight to the professionals gathering at the Las Vegas Convention Center for the Retail, Supply Chain, and Logistics Expo. This Whisper Report addresses the question regarding how will AI change warehouse architecture? as depicted in Figure 1.
Figure 1. How will AI change warehouse architecture?
The first change is suggested by Warehoues Craft’s Steve Harris. “It actually will change quite a few of the functions as far as directing employees. It will never replace employees. There’s always going to be a hands-on aspect as aspect to a warehouse. AI though will allow you to use some of those employees. It makes those employees smarter. For instance with our specific software allows them to if they don’t understand a process to ask a pro about a process and get clarification on that. So shortens the process requires them or doesn’t require them to go ask somebody else but takes a maybe a 5 or 10 minute delay and that AI is going to actually shorten that to just the time it takes to get the answer back from AI” Nothing like instant help from an expert while on the job to provide much needed clarity.
Beyond human collaboration, expect AI to show systemic gains. The second change is suggested by PGS360’s Priya Katyal. “The speed of delivery of different solutions, different problems that we have to solve for our customers to help make everything more efficient and fast track the solutions that we provide.” oloround’s Petros Dertsakyan couldn’t agree more. “Help with optimization and better operational flow. Make it lower cost, more efficient, but also there’s a lot of predictive information that Auwill come out of this that can’t be done individually now with the basic models that exist. So you’ll have better ability to like predict do predictive skew modeling uh reorder rates and inventory distribution also decide better on what will sell won’t sell and maybe even beforehand detect where you should have things go and where you should up marketing information for because you know it will sell better there and also seasonality. It’ll give you good seasonality, predictions, and potential future forcasts.”
Beyond collaboration and systemic changes, AI will also cause physical changes to the warehouse that affect the technical architecture as discussed by Bazarup’s Rodrigo Hernandez. “Automatization of processes, right? So AI will not only apply to to warehousing but really every process in terms of substituting with artificial intelligence manual processes that they exist. When we talk about warehousing, it goes even all the way to robots operating what people do today. And that’s not even futuristic. That’s happening today in bigger warehouses. So, at some point, it’s going to make processes more efficient. It’s going to make them cost saving as well. And you’re going to need less and less manual work to do better processes. So, I think that’s the best the best way to describe it.”
But the automation will not be restricted only to the physical warehouse. Backops AI’s Sean Elmurib Suggested. “a lot of parts of the supply chain, a lot of parts of the tech stack are very fragmented. Right? An operator can have four or five different software that they need to go pull data in from. And so what we realized is why not aggregate all that data into a centralized platform and then on top of that run agents against. So that’s kind of where I think uh you know supply chain type is headed and where warehouse automation is headed as well.” MetaOption’s Naushad Ahmed provide a more concrete example. “AI is going to do instead of user making a decision or predetermination user is making especially with the big warehouses where you have a 10,000 mains you have the multiple floors… AI is going to make those recommendations based on all the history and how exactly you are picking guys you are picking the product how the products are moving within the Warehouses.” Yet keep in mind. As Lufthansa’s Ingo Pietruska elaborated at some point in time, “warehouses will be built for robots, not for humans anymore.” For today, that is still a bit into the future.
Published to clients: February 17, 2026 ID: TBW2086
Published to Whisper Club: February 17, 2026
Analyst(s): Dr. Doreen Galli
Abstract:
“This Whisper Report investigates how AI and behavioral analytics enhances identity security. It highlights how organizations manage identity scale and emerging threats using behavioral baselines, anomaly detection, and contextual risk scoring. Researched at Identiverse held in Las Vegas, it incorporates quoted insights from Lumos’ Janani Nagarajan, GitGuardian’s Dwayne McDaniel, CyberSolve’s Ankush Kappor, Oasis’ Guy Feinberg, Simeio’s Octabio Lopez, Clarity Security’s James Davidson, Cubeless’ Treb Ryan, Apono’s Ofir Stein, Keeper Security’s Craig Lurey, Imprivata’s Diron Chain, and Panini’s Jim Harris.”
We took the most frequently asked and most urgent technology questions straight to the Technologists gathering at Identiverse 2025 held at Mandalay Bay in Las Vegas. This Whisper Report addresses the question regarding of how can AI and behavioral analytics enhance identity security?
In short there are two big motivations driving the adoption of AI and behavioral analytics. First, as Lumos’ Janani Nagarajan reported, “It is really critical to know the difference that in identity where it becomes harder with tons and tons of applications tons and tons of identities including machine identities. Those people are accessing, in addition to the machines, they’re accessing the same apps and it becomes a tangled web of permissions entitlements. It really becomes complex to operate at human scale. You cannot throw in more people to solve this problem. And this is where AI and analytics plays a huge role in solving for identity.” In other words, the mere scale of the identity space in most organizations demands AI to effectively manage.
The second reason to adoption AI and behavioral analytics in identity is because as Dwayne McDaniel of GitGuardian affirmed, “ ways to attack someone is to assume their identity and act on their behalf in a weird way this is especially true for machines.” Furthermore, AI is being used against the identity space to steal someone’s identity – specifically as deep fakes. As CyberSolve’s Ankush Kappor argued, “AI is changing the scenario in a dramatic sense in two ways one the adversary now has a lot more options to play with deep fakes are a big problem where previously you could use facial parameters for authentication and so on so forth with deep fakes that is that is no longer the case so there’s a cause for concern right there that are existing control is now breaking down because of AI.” But facial IDs are not the only identity form let alone the only biometric identity under attack from AI. Kappor went on further to explain, “voice-based authentication is also under risk you’ve seen companies like ElevenLabs and the kind of ease with which you can actually clone somebody’s voice a concern the last thing that I would like to really point out.”
Example Use Cases in Identity
Now that we understand why leveraging AI and behavioral analytics is important in the identity space, let’s dive into the use cases as depicted in Figure 1.
A common starting point in behavioral analytics is to create an analyze a behavior graph. Oasis’ Guy Feinberg suggested, “We use AI to identify the baseline for the behavior of different identities so we can create this graph to show you the different anomalies. When there’s a threat actors utilizing this identity or a deviation from the business justification of the original identity the use that why we provision it for. AI is a way for us to identify faster with better accuracy uh and also it helps us kind of fingerprint different threat actors that target different type of non-human identities as their favorite factor.” This graph is then used as Simeio’s Octavio Lopez summarized, “What AI is going to be able to assist us practitioners with IM (Identity Management) is being able to make you get signal out of the noise that we see every day. Whether it’s like identities being able to figure out what roles they need to have or even just combing through all the statistical data that comes from all the systems ,AI is going to be really useful and being able to make our lives a lot easier.”
One popular signal noise AI is great at identifying is that of unused access. Per Clarity Security’s James Davidson, “Governance is all about understanding who has access to what and is it appropriate the behavioral analytics is how that access that exists is being used so one of the mistakes people make is you know you have a company you’re operating all the time you’re creating new access to solve problems but you’re not keeping track of that access that you created and then you’re not keeping track of how that access is being used so we’ve started incorporating behavioral analytics things like have you even logged intothe software if you’re not logging in then maybe you don’t need it.” A useful example was provided by Lumos’ Janani Nagarajan. “’Hey I see sales have access to these CRM apps which is great but I see these three people not using them. Can you make sure that you put them back to the pool and maybe you know give them at least a warning that they’re not using it?’ That that means your least privilege access stays intact. The security risks are driven down but your productivity is not compromised.” Imagine that. In one step you not only improve your security by reducing unused access but potentially reduce your software licensing fees.
While it is important to identify unused access, unusual access is also critical to monitor. CyberSolve’s Ankush Kappor proposed, “looking in data looking at usage patterns of uh users to come up with risk scores and then determine which usage patterns are more risky for example if you normally access a certain application from certain locations in the US and one fine day connections start coming in you know uh from Asia that’ll trip up a few flags and then that analytics can prompt you for a higher level of authentication.”
One use case end users can really get behind was brought up by Treb Ryan of Cubeless. “What I think what we really use AI for is to come up with answers in integrations that they’re transparent to the user so when they get in it just works.” As Apono’s Ofir Stein expanded on, “few that we already did for example user experience we provide list privilege with AI agent that help you to get access to what you need only what you need in the platform this is actually take the least privilege approach into the day-to-day.” Finally for those not enjoying those pesky challenge questions, CyberSolve’s Ankush Kappor shares the AI modernized version. “previously systems were limited to a hard hard-coded set of questions that the user could answer for example to validate you know which school I went to and so on but if AI can be enriched with more aspects of my personality and privacy concerns are taken care of – then there is a vast variety of questions that can be asked of me that probably only I can answer and answer in a certain way.”
Fortunately, the benefits of monitoring identity and access information go beyond the identity space. In fact, as Keeper Security’s Craig Lurey contends what he appreciates most about AI in Identity is, “the ability to monitor and detect threats in regards to privilege sessions. So if you’re connecting to like a database or a Linux server or Windows server or something like that it’ll actually monitor the interactions. It will look for any high-risk type of actions and look for any malicious activity and so it does this all zero knowledge. The customer posts what we call the keeper gateway and it allows them to monitor this activity. It’ll automatically lock and kill the session if it detects any suspicious activity and then the administrator can then go back and review what took place and there’s an AI analysis um that actually summarizes the whole transaction and lets them know what happened and it’s a really perfect application of AI for threat detection.” Identity is critical to enabling threat detection and an identity solution enhanced with behavioral data and analytics is just simply better.
A common area of concern within enterprise security is always all those edge devices and endpoints. Fortunately, Imprivata’s Diron Chain has you covered. “We are able to take machine learning and AI functionality embedded within our system single sign on multifactor authentication and shared endpoint access to make sure that we understand who did what when on what machine. And the visibility in and around that allows the organization to get a lot smarter in terms of operational efficiency utilization. Taking analytics powered by AI to look for pattern anomalies. Ways in which they can analyze big data in a way that is actionable.”
Targeting the heart of the problem in identity theft, adding hehavioral AI can make all the difference. For human identity theft, Git Guardian’s Dwayne McDaniel offered up this viewpoint. “how do I know I can trust this person well if I haven’t described a specific set of things I’m allowed to do and I only ever do those things thumbs up i get a good score. If I all of a sudden start doing weird things it’s like wait a minute you don’t seem trustworthy anymore but that takes actual contextual analysis the fact I detect identity theft.” But detecting identity theft isn’t only for human identities, McDaniel went on to further explain the benefits to machine identity. “can this machine get into the system and retrieve this data under certain circumstances that’s completely normal operation how it’s going to do its work otherwise but now it’s starting to look up other database tables now it’s starting to do other things in that data source that it’s not supposed to do there’s no way a human can keep up with that level of analysis. AI on the other hand can at machine speed and alert someone to raise a flag say wait a minute something right something’s gone wrong in system so I actually see a pretty bright future for this particular use case with AI.” Please denote that he said at machine speed. As we covered in Conference Whispers: Black Hat 2019, threats can execute a complete ransomware attack for years in under 30 minutes. Expecting someone on call to get the alert, get online and stop something that fast is simply not reasonable.
AI is a new fun tool that many like to find an excuse to use to play with it. Panini’s Jim Harris offered some very wise advice, “Don’t reinvent the wheel but how can we incorporate those solutions such as things that come from Fiserv and other companies that are in that space to leverage our capabilities with theirs to deliver a whole solution for a customer.” In other words – clients should schedule an inquiry, let’s check what is available on the market that fits your specific needs. You might just save yourself a lot of time and money.
Published to clients: February 10, 2026 ID: TBW2099
Published to Whisper Club: February 10, 2026
Analyst(s): Dr. Doreen Galli
Photojournalist(s): Dr. Doreen Galli
ABSTRACT
“This Whisper Report explores how CTOs should rethink organizational design in the world with Generative AI. Generative AI introduces structural shifts that accelerate delivery and reshape skills, workflows, and talent strategy. The research was conducted at HR Tech in Las Vegas. It highlights how agile cycles, cross‑functional skills, and HR collaboration strengthen organizational resilience.Quotes come from leaders at RChilli, Darwinbox, FitFirst, Fountain, FranklinCovey, Eightfold AI, Gem, and Aptia USA.”
Published to Whisper Club: January 27, 2026 ID: TBW2095
Analyst(s): Dr. Doreen Gal
Photojournalist(s): Dr. Doreen Galli
Abstract:
This Whisper Report investigates how will drones change enterprise data strategy. It draws on insights gathered at the Commercial UAV Expo 2025 in Las Vegas, where UAV experts described the growing data volume, multi‑use potential, and rising compliance pressures shaping enterprise architectures. The report highlights strategic alignment, cross‑industry collaboration, and the challenge of converting drone data into actionable insights. It cites Barry Paul (Blue Nose Drones), Jason San Souci (Drone Ops USA), Kevin Teen (Aloft), Bill Reynolds (Central UAS Technologies), and Vik Chaudhry (Buzz Solutions).
Coverage on Computer Talk Radio.
Target Audience Titles:
Chief Data Officer, Chief Information Officer, Chief Technology Officer, Chief Digital Officer, Chief Information Officer
VP Data Strategy, VP AI & Analytics, VP Infrastructure/Cloud
Enterprise Data Architects, Cloud Platform Engineers, AI/ML Engineers, Data Governance Leads, DataOps Engineers, UAV Program Managers, Geospatial Analysts, Security Architects
Key Takeaways
Enterprises must begin with outcomes, not drone hardware, ensuring data strategy alignment before investing in UAV technologies.
UAV operations generate massive, multi‑use data requiring scalable architectures and disciplined reuse across missions and time.
Cross‑industry collaboration and regulatory data‑sharing mandates will reshape how organizations exchange, govern, and leverage drone‑collected information.
Organizations need compliant, secure infrastructure capable of turning large, disparate drone data streams into actionable, time‑saving insights.
How will drones change enterprise data strategy?
We took the most frequently asked and most urgent technology questions straight to the commercial UAV professionals gathering at Commercial UAV Expo 2025 held in Las Vegas. This Whisper Report addresses the question regarding How will drones change enterprise data strategy? Figure 1 represents the five strategic shifts coming for the enterprise due to the drone mandate.
Like many newer technologies, it is easy to fall into the trap of spending budget on the shiny thing everyone is talking about. But there is a reason the best CIOs and CTOs ask what you are trying to accomplish versus rubber stamping the technology acquisition. As Drone Ops USA’s Jason San Couci
contended, “So enterprises that are using drones are starting the wrong way. They’re starting with what equipment’s out there. They get they see the shiny things that are out here in this industry and they’re like, man, what can I do with that? No, they’re doing it wrong. They need to look at what outcomes that they need to actually that they’re doing it for. Right?” Drone Ops USA’s Jason San Couci went on to further explain. “I want to know what the data is going to be used for, what the analytics are going to be. So therefore, I can work backwards. What equipment do I need? What accuracy do I need? I can’t answer those questions at the beginning, right? It’s kind of like saying, I have this tool. I have a hammer. And I have a piece of wood. I want to go build a house. You’re not going to do that. You’re not going to build a house. You have to be like, you know what? I want to build a house. What materials do I need to be able to do that? What specialties do I need? What people what experts do I need? What subconscious do I need? What’s the timeline? What’s the budget? What’s all those things? That’s working the right way. People in this industry have been doing that wrong.”
But starting with the technology versus the problem isn’t the only issue. The existing data strategy might be outright ignored. Jason San Souci expanded further. “enterprise data strategy is something that’s been underlooked and underfunded for a long time because what they’re doing is they’re keeping a lot of this data in silos and they’re not using their existing enterprise data to augments or enhance the data that’s coming from any robotic system, drones, uncrewed systems, whatever it happens to be. So, they’re putting them in another silo and that’s a huge mistake.”
Most organizations do not really appreciate what big data truly is before they start working with the volumes of data that come from any sensor based solutions – including the numerous sensors on UAVs. Aloft’s Kevin Teen provided a meaningful example to demonstrate how the data volumes expand rapidly. “And so let’s say we send a pilot out for a survey or a construction update. While they’re out there, there are other opportunities. We don’t need to send another pilot out or launch a drone in the box or something like that to go look at something specific. Go inspect this bolt or go check this roof for leaks or, you know, where it might need paint or something along those lines. From that initial flight, from that initial data capture, we can then reuse a lot of that information and even kind of go back over time. Let’s say there’s a rust spot developing on an oil tank or something like that. we could go back and identify how frequently this happens, how long has this issue not been caught yet.” Kevin went on to further explain that optimizations are indeed possible. “I think the multi-use of the data that we’re collecting is going to be an important part of how we streamline and pull all that information out together.” Multi-use was a big term we heard repeatedly at the Commercial UAV expo during all conversations involving data. Barry Paul of Blue Nose Drones contended “not only can we do what the problem is that we need to solve right then, but there’s a lot of other things that can be utilized out of what a drone can collect for them. What kind of data? What other use cases or problems can we solve for a company.” As Central UAS Technologie’s Bill Reynolds nicely summarized, “The enterprise data demand that drones will put onto agencies and companies is immense in terms of the size both in imagery and aerial applications.” If you haven’t felt it yet, the data wave from UAV’s is coming to an enterprise near you.
Now that we realize the data will be voluminous and internally each organization should organize and efficiently, and repeatedly leverage data for multiple purposes, our next challenge arises. How do we get collaboration within an industry or sector or even cross-sectors? As Zepher’s Dustin Brewer noted, “going to take a collaborative effort between several of us that do collect data from our enterprise use cases like search and rescue, DoD, and being able to integrate those into other parts of the industry and have some of that cross communication. I think that’s going to increase collaborative efforts and more of a community effort in order to provide pilots the information that they need to either increase their skills or apply that to their industry that they’re either working towards or working within.” Identification of a lost child by drone has much in common with identification with a destructive and invasive animal in a massive crop.
But some sharing of the data may not be optional. Kenji Sugahara from the Oregon’s Department of Aviation clarified. “Drones will definitely change your data strategy, especially if you’re working in a government environment because all that data that is acquired is for the public record.” But what if you strictly work with private industry? Kenji has news for you as well. “With private industry, there will be increasing data storage requirements, especially under part 108 in the proposed rule that it that it is. What it proposes under part 108 is data retention. So there are will be data retention requirements. So not only for flight data, but you’re also talking about personnel data, you’re also talking about training data, you’re talking about maintenance data. So there’s going to be have to be a comprehensive data management strategy.”
All of this data and collaboration or regulatory sharing requirements create infrastructure and compliance challenges. As Buzz Solutions Vik Chaudhry emphasized, “they have purchased all these UAVs, aerial vehicles, drones. They’re doing a lot of with these kind of mobile sensors, there’s a lot of data that is generated. So at the enterprise level, utilities face a challenge on how to store and manage all that data. That’s where they are trying to build cloud infrastructure platforms within their systems. Obviously that has to satisfy their IT and cyber security compliance. But they’re also looking for software platforms that can visualize all this data especially imagery.” With the mountain of technical challenges, it is easy to lose sight of the goal. As Vik went on to further explain, “How can they make the system more robust but also how can they derive insights from that data because that’s where the real power is. Collecting the data is one piece. Flying your drones is one piece. But the whole of the challenge starts when you have to derive the insights from that data.” As summarized by FlytBase’s Deep Gupta, “The new strategy is what do I do with this much data?”
The problem, as articulated by Aloft’s Kevin Teen is here. “We are now just collecting a ton of more information, more data than we were getting before.” The challenge, as clarified by FlyteBase’s Deep Gupta is real. “How do I gather insights? How do I save time?” Our mission, as shared by Buzz Solutions’ Vik Chaudhry. “How can they make the system more robust but also how can they derive insights from that data because that’s where the real power is. Collecting the data is one piece. Flying your drones is one piece. But the whole of the challenge starts when you have to derive the insights from that data.”
If you are faced with data siloes and a fleet of drones and don’t know where to start or are not sure you are on the correct path. This is the exact time to schedule an inquiry with your analyst. Their first hand experience working with the complexities of voluminous disparate sensor data sets in creating a cohesive data fabric have immeasurable value on your success.
