Year: 2026

Sreekumar NarayananChief Growth Officer, BNB Security &Automation solutions In an industry that often gets measured only on what went wrong, BNB Security and Automation Solutions has spent the last few years quietly reshaping a different story – what goes right when protection, safety, comfort and operations are treated as one connected promise to the customer This is not a technology story. It’s a workplace story. It’s about the guard at the gate who needs clarity, not complexity. It’s about the facility head who wants fewer surprises, not more dashboards. It’s about the security leader who is asked every month – to ‘do more with less’ without compromising safety. And it’s about organizations that are finally recognizing a truth they lived through in the last decade – a workplace is not just a building. It is a living system. When it is healthy, business runs smoother. When it is ignored, business bleeds quietly – through downtime, fatigue, hidden losses and preventable incidents. BNB’s work sits in that real-world space between risk and routine – where a small failure becomes a big disruption and where a simple improvement can compound into meaningful savings. Over time, this has shaped a core approach – ‘make workplaces safer, smoother and more accountable – without adding burden to the people who run them.’ Where BNB started the shift: From ‘Security Projects’ to ‘Workplace Outcomes’ A few years ago, the market largely treated physical security as a project category – equipment, installation, handover, warranty and goodbye! But customers were changing. They weren’t just asking for ‘systems,’ they were asking for outcomes such as: BNB’s shift began when it started listening differently – not only to the procurement checklist, but to the lived reality of operations teams: security, administration, facility management, EHS, IT and leadership. From these conversations came a simple thesis: A workplace becomes truly secure only when safety, comfort, access, visibility, discipline and accountability move together. That thesis is what later evolved into BNB’s broader ‘Total Workplace Solution’ mindset – an approach that doesn’t treat security as a standalone island, but as part of a wider ecosystem that includes day-to-day operations, maintenance, compliance, energy awareness and employee well-being. What BNB achieved: The work that actually changed the game BNB’s progress can be understood through five achievements – each grounded in practical realities. 1. Turning ‘Systems’ into Everyday Reliability Many organizations already have equipment in place. The real pain is that it doesn’t behave like a dependable system. It behaves like a set of disconnected parts. BNB’s project teams learned to focus on what customers care about most: This translated into a stronger delivery style – tighter handover discipline, clearer documentation, better commissioning rituals and service readiness that begins before the site is ‘completed.’ It also changed the language BNB used with customers. Instead of selling components, BNB started selling operational confidence. 2. Making security and operations measurable – without making them complicated The workplace produces signals every day – entry and exit patterns, peak movement, exceptions, repeated alarms, delays, congestion points and compliance gaps. BNB’s learning was that these signals become valuable only when they are turned into simple questions: It’s about the guard at the gate who needs clarity, not complexity. It’s about the facility head who wants fewer surprises, not more dashboards. It’s about the security leader who is asked every month – to ‘do more with less’ without compromising safety. And it’s about organizations that are finally recognizing a truth they lived through in the last decade – a workplace is not just a building. It is a living system This thinking gave rise to BNB Cognira as a business layer – not as a ‘fancy product,’ but as a way to bring order and meaning to what already exists. In many places, the biggest breakthrough wasn’t adding something new. It was simply making the existing environment legible. A practical example: repeated alarms in the same zone. In many sites, alarms become background noise. People stop trusting them. BNB’s approach helped customers separate alarms that are actionable, frequent but harmless, genuine risk indicators, and that are maintenance problems disguised as ‘security alerts.’ That distinction matters because it changes behavior. It also changes cost. 3. Expanding the definition of ‘protection’ to include well-being and comfort Security leaders increasingly sit in meetings where the business asks about employee well-being, workplace readiness, comfort complaints, absenteeism patterns, productivity drops linked to environment, and ESG expectations and reporting pressures. This is where ThermoG and the broader BNB Workplace thinking became relevant – not as a separate business line, but as a reinforcement of the same idea – a safe workplace is a well-run workplace. It’s about the guard at the gate who needs clarity, not complexity. It’s about the facility head who wants fewer surprises, not more dashboards. It’s about the security leader who is asked every month – to ‘do more with less’ without compromising safety. And it’s about organizations that are finally recognizing a truth they lived through in the last decade – a workplace is not just a building. It is a living system If a meeting room is always uncomfortable, people stop using it. If ventilation is uneven, complaints rise and trust falls. If basic environmental conditions are poorly managed, the building becomes a daily friction point. BNB’s contribution here has been to treat environment not as ‘facility’s problem’ and not as ‘just HVAC,’ but as a measurable part of workplace experience – something that can be tracked, improved and linked to operational discipline. When comfort improves, complaints reduce. When complaints reduce, response workload reduces. When workload reduces, teams can focus on higher-risk issues. This is how small improvements compound. 4. Building an innovation practice that stays close to field reality Innovation can become a trap when it’s detached from operations. BNB Innovation Lab has been shaped with a different discipline – build only what improves outcomes in the field. That means: simplifying what operators see and do; strengthening how exceptions are handled;…

Ramit LuthraPrincipal Consultant – North America at 5Tattva Artificial intelligence has moved from strategic discussion to operational reality. For CIOs and CISOs, AI is no longer a future initiative to be evaluated. It is already embedded in development pipelines, service desks, analytics platforms, and business decision workflows, often through tools adopted faster than governance and security models can adapt. This creates a familiar leadership tension. The business expects speed and measurable outcomes. Technology and security leaders are expected to protect data, manage risk, and maintain regulatory posture. AI intensifies this challenge by introducing new data flows, opaque processing, and third-party dependencies that traditional controls were never designed to fully govern. What makes this moment different is not the technology itself, but the direction of travel. The way organizations adopt AI today is reshaping how cybersecurity risk is defined, how audits are conducted, and how confidence is established with boards, customers, and regulators. Taken together, these perspectives outline key technology and cybersecurity predictions for 2026, reflecting how AI governance, risk management, and audit practices are expected to evolve as AI becomes embedded across the enterprise. Rather than predicting specific tools or timelines, the most reliable way to discuss the future of AI governance is to identify the pressures that are already changing organizational behavior. Safe prediction #1: Most AI risk will come from normal business use, not attacks The dominant cybersecurity risk associated with AI will not be sophisticated adversaries or novel exploits. Instead, it will stem from ordinary employees and systems using AI as intended. Sensitive data will enter prompts, be retained in logs, reused by vendors, or embedded in downstream outputs without malicious intent. Traditional data loss prevention tools struggle in this environment because nothing appears abnormal. From an audit perspective, this means reviews will increasingly focus on how data moves through AI systems during legitimate use, not just whether AI tools are formally approved or blocked. Early enterprise adoption patterns indicate that this risk is already materializing as AI becomes part of routine business workflows. Safe prediction #2: Data exfiltration will be redefined by governance, not malware Historically, data exfiltration implied clear violations or breaches. In AI-enabled environments, data can leave the organization quietly, legally, and repeatedly. The core question shifts from ‘Was data stolen?’ to ‘Did we understand, approve, and monitor this data use?’ As a result, audit evidence will increasingly include data classification rules, AI usage policies, vendor retention terms, and monitoring of prompt behavior. This prediction aligns closely with how regulators already evaluate cloud and third-party risk. Taken together, these pressures point toward a broader shift in how audits themselves are designed and interpreted. Safe prediction #3: Audits will evolve from control checks to decision validation Technology audits are moving away from static control verification toward validation of decision-making processes. In the AI context, auditors will ask why a specific AI use case was approved, what risks were identified and accepted, how outcomes are monitored over time, and who has the authority to intervene if behavior changes. Governance artifacts such as AI inventories, risk tiering frameworks, approval records, and exception logs will become central audit evidence. This mirrors established trends seen in standards such as ISO 27001, ISO/ IEC 42001, and the NIST AI Risk Management Framework. Safe prediction #4: AI governance will become a confidence signal for leadership Boards, customers, and regulators are less interested in whether AI is used and more interested in whether it is governed. Organizations that can clearly explain how AI decisions are made, monitored, and corrected will face less friction, fewer surprises, and faster approvals. In this context, audits increasingly function as confidence mechanisms rather than mere compliance artifacts. Trust, rather than technical detail, will drive regulatory and customer confidence. While regulatory approaches will differ by geography, expectations around accountability and explainability are converging. Safe prediction #5: Strong audits will enable faster AI adoption, not slower Organizations without clear AI governance often swing between two extremes – freezing innovation altogether or allowing uncontrolled experimentation. Both outcomes increase risk. Well-designed audits that clarify boundaries, ownership, and accountability allow teams to move faster, with fewer internal debates and less reliance on shadow AI usage. Here, the audit function becomes an enabler of scale rather than a brake on innovation, echoing the role audits previously played during cloud adoption, outsourcing, and DevOps transitions. Why audits matter more as AI accelerates AI introduces uncertainty, while audits introduce structure. In an AI-enabled enterprise, audits now serve three audiences simultaneously. CIOs and CISOs gain clarity and defensibility, business teams gain permission to innovate safely, and regulators and customers gain assurance that risk is being governed. This triangulation explains why audits are becoming increasingly important, not less so, as AI adoption accelerates. What CIOs and CISOs should do now CIOs and CISOs should begin by assuming that AI is already in use and focus on discovery rather than prohibition. Mapping AI data flows is more important than cataloging AI tools alone, particularly understanding where sensitive data enter and exits AI systems. AI use cases should be classified by risk and impact so that governance is applied where it matters most. Audits should be designed around decisions rather than documents, ensuring they capture intent, oversight, and accountability. Finally, leaders should be prepared to explain AI governance in simple terms, because confidence comes from clarity, not technical depth. Conclusion The future of AI governance will not be defined by regulation alone or by technology breakthroughs. It will be shaped by how well organizations can demonstrate control, intent, and accountability as AI becomes embedded in everyday operations. The safest prediction is this – CIOs and CISOs who treat audits as forward-looking assurance mechanisms will govern AI more effectively, move faster with confidence, and earn greater trust from boards, users, and regulators. As AI becomes embedded across the enterprise, the greatest cybersecurity risks will come from normal business use, not malicious attacks. Safe, forward-looking audits are emerging as a critical tool for CIOs and CISOs to govern AI, manage…

With the rapid increase of volume, the e-commerce/ retail industry requires the high demand for rapid delivery. The traditional logistics and warehousing methods have become overwhelmed. In order to cope with the logistics pressure brought by events such as black Friday and double eleven festival, companies urgently need stable and reliable intelligent systems to release manpower. Hikrobot’s ecommerce solutions are designed to transform the way online retailers manage their logistics and supply chain operations. Their Autonomous Mobile Robots (AMRs) and intelligent logistics solutions address key challenges faced by ecommerce businesses, including: Some of the specific ecommerce solutions offered by Hikrobot include: Operational Challenges Solution overview: Aimed at unmanned handling, informatization of inventory management and high efficiency of picking, Hikrobot solution integrates robots, AI and the Internet of Things, facilitating goods inbound, sorting and collection with the help of RCS and IWMS, to improve operational efficiency and the level of automation. Solution Components Latent Mobile Robot (LMR) Hikrobot’s Latent Mobile Robot (LMR) is a game-changer for environments where space is limited. Its unique design allows it to slide underneath shelves, pallets, and other carriers, lift them, and transport them with ease. This eliminates the need for bulky lifting equipment and opens up valuable floor space. Hikrobot’s LMR is part of their comprehensive portfolio of Autonomous Mobile Robots (AMRs), designed to optimize operations, reduce costs, and improve safety. Key features: Forklift Mobile Robot (FMR) Hikrobot’s Forklift Mobile Robot (FMR) is very important component for warehouse automation! These robots are designed to handle standard bins and pallets with ease, using advanced laser SLAM navigation and vision technology for precise movement and obstacle avoidance. Key features: Popular models Hikrobot’s FMR series is designed to streamline your logistics and material handling processes, improving productivity and safety. Carton Transfer Unit (CTU) Hikrobot’s Carton Transfer Unit (CTU) is an automated, unmanned picking and handling robot designed to optimize warehouse operations. It can transfer multiple goods simultaneously, improving picking efficiency and storage capacity. Key features: The CTU is part of Hikrobot’s comprehensive portfolio of Autonomous Mobile Robots (AMRs), designed to streamline logistics and material handling processes in various industries, including e-commerce, manufacturing, and consumer electronics. iWMS1000 The iWMS1000 is a smart warehouse management system designed to optimize warehouse operations and logistics. It’s a comprehensive solution that integrates various technologies, including: By integrating with Hikrobot’s AMRs and other technologies, the iWMS1000 creates a smart, efficient, and agile warehouse ecosystem. Solution Advantages Rapid Fulfillment: Hikrobot’s AMRs enable fast and accurate order fulfillment, reducing delivery times and improving customer satisfaction Application Case Hikrobot’s solutions have been successfully implemented by various ecommerce businesses, including Superdry, which saw significant improvements in inventory accuracy, productivity, and order processing times. Background Superdry is an iconic, global fashion brand operating through 768 store locations in 65 countries. Maintaining product availability, keeping efficient fulfillment, and processing the returns rapidly are essential for ensuring the best customer experiences. To support future growth, deliver accurate and efficient picking, Superdry introduced Hikrobot intelligent mobile robots. Solution Superdry introduced 46 robots into the Burton-upon Trent DC and 20 robots in European DC for order picking and returns handling. Meanwhile, combination of PTL and indicator light ensured the accuracy of order fulfillment. Customer Benefit Read More

Learn how to deploy a successful RTCC in your citywith the right planning, technology, and partnerships Big and small, cities everywhere are trying to get a handle on crime and keep people safe. Much of this falls on the shoulders of law enforcement and public safety teams. These agencies are working around the clock, doing their best to quickly respond to emergencies and get offenders off the streets. And they’re doing it all despite ongoing staff shortages, increased violence toward officers, and rigid budget constraints. Using older, disconnected technologies makes their jobs even harder. Many inefficient manual processes and siloed communication between agencies cut into valuable time and resources. Add in the constant threat of cyberattacks and public mistrust over data governance; keeping cities safe can seem like an impossible task. For all these reasons, more city agencies are considering the benefits of real-time crime centers (RTCCs). In fact, according to The National Real Time Crime Center Association, there are over 150 RTCCs in the United States today. And that number keeps growing. RTCCs help cities and small communities harness the power of existing technology investments, real-time data, and advanced analytics to skyrocket public safety initiatives. They unify data streams and operations across city departments, which often leads to the following results: As law enforcement and public safety agencies start investigating or planning for an RTCC, knowing where to begin and what to look for and prioritize in the decision-making is critical. On the planning side, agencies must consider initial technology and space assessments, various funding strategies, and the vested interests of all city stakeholders. When assessing core RTCC platforms, data integration and unification, adaptability and growth, community connections, inter-agency collaboration, cybersecurity, and privacy should always top wish lists. Finally, working with an experienced and trusted partner can often help ease the entire RTCC journey and generate the most successful long-term outcomes. Why You Need an RTCC Challenges in public safety today Disconnected systems, data, and people Public safety and police agencies use various technologies to keep their communities safe. Yet, all these systems and devices are often running independently. Having to retrieve data from different sources and piece together information is not only cumbersome, but it slows emergency response and investigations. These siloed systems and data further limit inter-agency communication and collaboration, leading to huge efficiency losses. Growing cyber threats and privacy concerns From Internet of Things (IoT) devices to new crime-fighting solutions, the use of technology is expanding across cities. With that, so are data security and privacy concerns. Despite continually improving cybersecurity practices, cities can’t always keep up with the sophistication of today’s cybercriminals. Citizens also want greater transparency around how cities use, collect, and manage data. Building public trust and strengthening cybersecurity and privacy efforts remain top of mind. Inefficient evidence management When a crime occurs, investigators often spend a lot of time gathering evidence to build cases. They go from place to place, collecting everything from video footage and 911 call recordings to text messages and audio recordings. If cases go to court, they must also burn DVDs and deliver them to attorneys. The entire process saps resources and slows investigations. Storing and sharing physical copies of evidence also makes it difficult to ensure the evidentiary authenticity and chain of custody. Ongoing personnel shortages Police departments everywhere are struggling to hire and keep officers. According to a recent survey, only 10% of respondents confirmed their police department was fully staffed. As crime evolves and demand for effective policing remains constant, existing officers and public safety teams are trying their best to keep up. However, the pressure on people to do more is heightening stress and burnout in an already demanding line of work. Increased violence toward officers In recent times, violent crime and antipolice rhetoric have been running high. This has caused a rise in aggression towards law enforcement. Though the very nature of police work exposes officers to physical altercations and risks, officer safety remains paramount across agencies. Yet, there’s still a significant opportunity to leverage existing technologies to enhance information sharing, improve officer readiness, and drive safer outcomes. Rigid budget constraints Public safety and law enforcement agencies don’t always have extra room in their budget to make technological enhancements. Even when decisionmakers recognize the benefits of new solutions, long-standing budget rigidity and red-tape approval processes hold them back. Yet these public safety innovations can drive ripple effects in time and cost savings across departments, offering substantial returns on investments over time. What is a real-time crime center? Real-time crime centers (RTCCs) take public safety initiatives to the next level. They act as crime-fighting nerve centers, unifying data streams and operations across city departments. Within these state-of-the-art tech hubs, public safety and law enforcement teams can tap into a central source of real-time information and trending data. Everything from 911 calls and dispatch information to live video, various sensor data can stream onto video walls and monitors for all operators and investigators to see. During an emergency, they can then quickly understand what’s happening and effectively deploy resources to mitigate the situation. During investigations, detectives can dive deep and collect evidence with all relevant data at their fingertips. What’s the outcome? A unified front of public safety technology and resources that help reduce incident response times, improve officer safety, speed up investigations, and enhance data collection across the city landscape. The core of an RTCC and the value of true ‘real-time’ At its core, an RTCC is built on a foundational, frontend solution that offers operators a single interface pane of glass. This is what brings all data from various systems and sensors together and provides public safety teams with real-time situational awareness and support. It does this by analyzing and correlating all incoming information and then pointing officers to the most pressing situations. All relevant video and data is displayed on an interactive city map, allowing for added situational context to make faster, more informed decisions. Here’s an important caveat: not all…