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Forbes
5 days ago
- Business
- Forbes
20 Expert Tips To Avoid Network Automation Pitfalls
Network automation offers the promise of greater efficiency, faster deployments and fewer manual errors—but it's not without its challenges. Many teams dive in with good intentions, only to encounter roadblocks that stall progress, introduce complexity or even create security gaps. The good news is that many common pitfalls are avoidable with the right planning, tools and processes. Below, members of Forbes Technology Council highlight mistakes they've seen in network automation efforts and share practical tips to help your team get it right from the start. A common network automation pitfall is automating without fully understanding existing network workflows. This can cause outages or security gaps. Teams can avoid these issues by documenting processes, validating configurations in a test environment, and involving network engineers early in automation planning. - Sai Shashank Rasamalla, American Express A common pitfall is automating without fully understanding the existing network architecture and dependencies. This can lead to unintended outages or security gaps that keep getting missed because there is no human intervention. - Venkata Thummala, Stanford Health Care Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify? A common network automation pitfall is failing to document configuration changes in real time. This can lead to misconfigurations and delays in troubleshooting. IT teams can avoid this by using tools that automatically track and update network changes, ensuring visibility and control as automation scales. - Douglas Murray, Auvik A common network automation pitfall is ad hoc scripting without standardization. Ad hoc scripts solve short-term problems but create long-term complexity and fragility. Adopting infrastructure as code avoids this by enforcing version control and modularity and ensuring only authorized, trackable changes are deployed, bringing stability, security and team alignment. - Karan Alang, Versa Networks Inc. A common network automation pitfall is relying on code-heavy solutions that only a few engineers can maintain, limiting scalability and resilience. Embracing no-code automation allows more team members to build and manage workflows, reduces reliance on novice coding skills, and ensures consistent, scalable network operations. - Song Pang, NetBrain Technologies A common network automation pitfall is inadequate testing of scripts before deployment, potentially causing outages. To avoid this, teams should create a testing environment that mimics production, use version control for scripts, conduct code reviews, automate testing processes and implement gradual rollouts, like canary releases. Additionally, proper documentation and training on automation tools are needed. - Raghvendra Tripathi Here's one I've seen recently: the use of weak or recycled security keys during automated deployments. These systems often don't generate strong randomness, making networks vulnerable. Teams can avoid this by using secure key generators or hardware-based tools that ensure fresh, strong encryption keys every time. - Erick Grau, Chibitek A frequent pitfall is automating overly complex or poorly understood manual processes—essentially, 'paving the cowpath.' Teams create brittle automation, which is a nightmare to maintain. Avoid this by first standardizing and simplifying the target process. Then, automate in small, incremental, well-tested steps. Focus on foundational elements before tackling intricate workflows. - Ashish Bhardwaj, Google Automating outdated legacy networks is like racing with a cracked engine. Without modern foundations, automation amplifies fragility and will lead to further complexities later on. Standardizing configurations and leveraging AI-driven workflows by upgrading ineffective systems will build resilient and intelligent networks. - Savinay Berry, OpenText One network automation pitfall is to simply automate a bad process; it just fails faster. Automation requires rethinking—not just for today, but for tomorrow—in a new, inventive way to anticipate technology growth and changes so that solutions stay relevant longer. - Pam Brodsack, Velera A common network automation pitfall is inadequate data backup verification. Many teams automate backups but don't periodically validate their integrity or restorability—until disaster strikes. Implement regular automated test restorations alongside your backup routines to verify that data can actually be recovered. This ensures your backups will work when really needed. - Chongwei Chen, DataNumen, Inc. A common network automation pitfall is alert overload from static, context-poor data. To avoid this, teams should integrate rich telemetry with AI-driven analysis to provide contextual, actionable alerts. This reduces noise and makes the process of identifying the root cause more streamlined, which ultimately supports more effective and efficient automation. - Judit Sharon, OnPage Corporation One common network automation pitfall is ignoring cross-team collaboration. When networking, security and operations teams work in silos, automation efforts often conflict or fail. To avoid this, build cross-functional workflows early on, ensuring alignment, shared goals and integrated feedback loops for smooth execution. - Rishi Kumar, MatchingFit One of the most frequent mistakes in network automation is rushing to automate processes without a structured plan. Teams often deploy automation tools haphazardly—scripting repetitive tasks or adopting orchestration platforms without evaluating long-term scalability, security or operational dependencies. - Pratik Badri, JPMorgan Chase & Co A common pitfall in network automation is a disconnect among processes, people and technology. Successful implementation requires these elements to work in harmony. Over-automation can alienate those who struggle to keep pace with rapid tech changes. Processes should be designed with adaptability and leverage technology when appropriate, not be dictated by it. - Hari Sonnenahalli, NTT Data Business Solutions Config drift is a major pitfall—manually applied changes bypass automation, causing inconsistencies. Modern teams avoid this by implementing strict automation-only policies, using tools like GitOps for infrastructure as code, and integrating validation checks that detect manual changes. Treating configs as immutable through CI/CD pipelines ensures all changes are tracked and reversible. - Anuj Tyagi One common pitfall is neglecting decommissioning. Automation excels at spinning up, but stale configs, orphaned services and zombie routes linger. Teams must automate clean-up, too—expiry policies, lifecycle hooks and teardown scripts ensure networks stay lean, secure and scalable. Don't just build—declutter. - Roman Vinogradov, Improvado Overlooking scalability is a frequent network automation pitfall; solutions that work for small environments may fail as networks grow. Teams can avoid this by designing automation with scalability in mind from the outset—using modular, reusable code and regularly reviewing automation tools to ensure they can handle increased complexity and volume as the organization expands. - Pradeep Kumar Muthukamatchi, Microsoft A common pitfall in network automation is treating it as tactical 'patchwork' rather than strategic orchestration. Many organizations automate isolated tasks without considering how those actions fit into the broader operational value chain, leading to fragmented solutions. To avoid this, step back and assess the entire operational workflow—identify dependencies, control points and outcomes. - Anil Pantangi, Capgemini America Inc. Skipping rigorous validation is a top network automation pitfall; a single typo or misconfiguration deployed at scale can cascade into massive outages. To prevent this, teams should embed pre- and post-change checks using network simulators, peer-reviewed scripts, automated verification tests and enforced rollback logic, ensuring errors are caught and reversed before they spread. - Sai Sandeep Ogety,
Forbes
5 days ago
- Business
- Forbes
Scaling A SaaS Business? Watch Out For These Costly Mistakes
getty Scaling a software as a service business isn't just about speed—it's about sustainability. Rapid growth can tempt teams into hasty hires, rushed rollouts or overextended infrastructure. Without a solid foundation, momentum can quickly turn into misalignment, technical debt or customer churn. Avoiding these missteps requires more than ambition—it takes discipline, foresight and the right systems to support scale. Below, members of Forbes Technology Council highlight common pitfalls SaaS teams face during growth and share practical advice on how to navigate them wisely. Early customers can and should inform product features as you are scaling a SaaS model—it can help you validate requirements and expectations of benefits. The art and science at this stage is balancing a single customer's requirements relative to what the broader market can benefit from. Many organizations go too deep into a single customer's needs, building something that will not benefit others. - Viraj Narayanan, Cornerstone AI The pitfall I see is equating adding team members with growth or capacity. Scaling efforts can run into a lot of friction when there are too many cooks in the kitchen and there's a constant need to keep everyone updated under the guise of collaboration. Having too many people at different hierarchy levels leads to silos and slowdowns instead of achieving true scale. I would be very careful about hiring too many new team members post-funding. - Asim Rizvi, RxSense Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify? SaaS teams often over-optimize for efficiency, centralizing systems and creating hidden risks. A better approach is distributed resilience: modular, redundant designs that meet diverse regulatory needs, paired with scaled governance and trust frameworks to sustain long-term growth. - Kevin Parikh, Avasant When scaling, SaaS companies often take their eye off customer service. It's important to guide customers and give them a clear understanding of the ROI and value that the platform will deliver throughout the contract term so that they can truly maximize its value. Touching base with customers just at the end of the year, when renewal is coming, is often too late. - Carlos Melendez, Maxar Intelligence Failing to architect a flexible, agile platform limits future growth. Start lean: Prioritize essential features, then track KPIs to learn where to invest, scale or evolve next. Let data, not assumptions, drive your roadmap. - Raj Jhaveri, Greenlane™ Infrastructure SaaS teams often overlook the strategic importance of product integrations and build them ad hoc. This inevitably becomes a bottleneck to scaling, as engineers struggle to keep up with requests and deals are lost due to a lack of integrations. To avoid this, SaaS leaders should see integrations as a critical way to deliver value and plan for them in the product roadmap. - Michael Zuercher, Prismatic Too often, SaaS teams build around one use case or high-value client, over-customizing the product. It hinders wider adoption and stifles growth. Prevent this by basing your roadmap on scalable issues, iterating with numerous users, and modularizing custom features to address wider requirements without weakening the core product vision. - Prashant Kondle, Ivis Technologies Organizational structures and processes that work for small teams simply do not scale for large development organizations spread across multiple time zones and geographies. Coordination and transparency become even more important. DevOps automation is critical to ensure code consistency and compliance. Agile is great for small teams, but large teams need the Scaled Agile Framework. - Sanjay Gidwani, Copado A common pitfall is treating scaling as a second phase. To scale effectively, it must be part of your strategy from day one. For example, we wrote all documentation and internal docs in English from the start, even when selling locally, so when global sales began, we were ready. Scaling later is harder, slower and more expensive. - Darko Pavic, Fiscal Solutions One common pitfall is scaling before achieving true product-market fit. SaaS teams can avoid this by investing early in customer feedback loops, refining the core offering, and ensuring strong retention before pouring resources into growth. - Sven Oehme, DataDirect Networks Losing focus because you want to capture adjacent users and market segments before nailing what is enabling scale is a common misstep. Yes, SaaS teams have to expand, just like all businesses have to. However, it has to be thoughtful and carried out with the same care that allowed them to break into the first segment. - Aditya Lahiri, OpenFunnel During the pilot phase for SaaS products, the ROI case study usually tends to be high. However, when the product is rolled out in the post-pilot phase, the ROI rarely remains at the same level as the pilot phase. This is primarily because everyone uses products differently. Technology leaders should understand this and set realistic expectations during the wider rollout of SaaS products. - Manjot Pal, Resonate AI SaaS teams often prioritize requests from key clients, which can delay addressing technical debt and developing scalable features. Establishing a product council, where clients collectively influence the product roadmap, aligns individual needs with broader market demands. This collaborative approach fosters transparency, balances priorities and guides the product toward sustainable scalability. - Sandeep Shivam, Tavant Technical debt can be a silent killer during SaaS scaling. Teams frequently prioritize rapid feature development over code quality, creating a drag on future innovation. I think it is important to allocate resources to dedicated 'refactoring sprints' and enforce rigorous code reviews. Designing with scalability in mind from the outset is crucial to avoid this trap and maintain agility. - Neil Lampton, TIAG A common mistake SaaS teams make when scaling is getting too fixated on new features at the expense of refining the core product. It's easy to overlook the value of perfecting what's already working. Without a solid foundation, new features can feel disconnected or overwhelming to users, which can slow down growth. Ensure that the core product is rock-solid before scaling up with new features. - Alex Ford, Encompass Corporation The ideal customer profile that worked for early traction may not suit a scaling product. Teams often keep chasing the same persona, even when their product has evolved past them. To prevent this issue, it is essential to revisit your ICP every six to 12 months. Align product, pricing and go-to-market strategies with where your most profitable future growth lies, not just your historical wins. - Cristian Randieri, Intellisystem Technologies In a highly competitive SaaS market, failing to articulate what sets your product apart can lead to commoditization and destructive price competition. This in turn can lead to issues with attracting and retaining customers, which is a crucial need for SaaS business models that rely on recurring revenue. Having a unique value proposition and focusing on highlighting key differentiators is crucial. - Diganta Sengupta, Oracle Corp A common pitfall SaaS teams face when scaling is compromising on culture. In the urgency to grow, teams often prioritize speed over alignment, which leads to misalignment and long-term inefficiencies. The key is to be intentional—hire slowly, reinforce core values and scale your culture with the same discipline as you scale your product. - Mara Dimofte, Rilla Often, growing SaaS teams do not immediately realize the power of partnerships and are behind the curve on executing the platform strategy. Building strong partnerships with common applications that your customer uses and creating seamless experiences can be a strong differentiator for a SaaS product, leading to customer delight and stickiness and improving retention and customer acquisition. - Anshul Kumar, Paylocity Trying to retrofit a legacy product architecture and op-model into a new SaaS solution is a mistake. Not addressing fundamentals—such as multitenancy for management and security, clear separation of control and user planes, a revamped costing and accounting model that accurately manages shared costs, and so on—leads to big risks. Using shortcuts to bypass these issues can get you started on a SaaS solution, but scaling can be hard and expensive. - Mrutyunjay Mohapatra, Alix Partners
Forbes
09-06-2025
- Business
- Forbes
20 Real-World Applications Of Quantum Computing To Watch
Quantum computing has long been the domain of theoretical physics and academic labs, but it's starting to move from concept to experimentation in the real world. Industries from logistics and energy to AI and cybersecurity are beginning to explore how quantum capabilities could solve—or cause—complex problems that classical computers struggle with. Early use cases suggest surprising applications for—and challenges from—quantum computing may arrive sooner than many people expect. Below, members of Forbes Technology Council detail some of the ways quantum may soon be making a real-world, widespread impact. Quantum computing is poised to rapidly transform cybersecurity, likely altering information exchange sooner than organizations expect. It is critical for organizations to explore quantum communication technologies, such as quantum key distribution and quantum networks, to defend against threats and level the playing field by integrating quantum computing defense strategies into defense frameworks. - Mandy Andress, Elastic Accelerated road testing demands simulating millions of scenarios related to weather, traffic and terrain to train and validate autonomous systems. This involves optimization of scenarios to ensure maximum coverage, risk modeling and detecting anomalies in high-dimensional data obtained from LiDAR, radar and cameras. Quantum computing will be instrumental in performing these simulations much faster. - Ajay Parihar, Fluid Codes Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify? Quantum computing promises to revolutionize data analysis—for example, helping scientists simulate molecules and gene pools and rapidly unlock life-saving cures. However, the same power that accelerates progress also breaks existing data-protection techniques, putting global digital security at risk. It's a double-edged future: Quantum is miraculous for analyzing data, but it's also dangerous for protecting data—unless we prepare now. - Srinivas Shekar, Pantherun Technologies One surprising area where quantum computing could help soon is drug discovery and designing new materials. Quantum computers can study molecules in ways normal computers can't. This can help scientists develop new medicines or better batteries faster. Big companies are already working on this, so real-world use may come sooner than people think. - Jay Krishnan, NAIB IT Consultancy Solutions WLL Logistics optimization represents an unexpected area of impact. Quantum computing shows promise for transforming complex routing problems that affect delivery networks and supply chains. The technology could optimize shipping and traffic routes in real time across the globe, which would reduce costs and emissions at a pace that's beyond current supercomputers. - Raju Dandigam, Navan Quantum computing could make a real-world impact sooner than expected in telecom network optimization. Quantum computing can revolutionize telecom networks by significantly enhancing their resilience and delivering richer user experiences. Additionally, with principles like superposition and entanglement, QNLP can address current natural language processing challenges, including nuanced understanding and bias. - Anil Pantangi, Capgemini America Inc. World hunger is one unique challenge where quantum could have an immediate impact. Roughly one-third of all food produced is lost across the entire supply chain, from farm to table. Quantum algorithms could be applied to optimize the food supply chain, improving demand forecasting, logistics and resource allocation. It can determine the best delivery path and ensure no food goes to waste. - Usman Javaid, Orange Business Entropy-based quantum computing using nanophotonics is optimized for solving very complex polynomial mathematics. This type of quantum computing can be performed at room temperature and could accelerate the development of low-energy protein configurations and synthetic amino acids. That, in turn, may give synthetic biology a boost in biochip and biosensor development. Products using biochips could elevate patient diagnostics, monitoring and drug delivery to a new level. - John Cho, Tria Federal Quantum computing will revolutionize energy systems by enabling real-time monitoring and modeling of electric grids. This will be critical as today's grids transition to match distributed sources of renewable energy, with growing demand from EVs, electric heating and data centers. I expect quantum will be a key technology to create smarter grids that deliver reliable, clean and affordable energy. - Steve Smith, National Grid Partners Attackers are now harvesting internet data for the time when quantum computers are ready to break today's identity and encryption systems. CEOs and boards are asking, 'What's our risk? How do we defend ourselves?' It's a reason why lifetimes for TLS certificates—the identity system for the internet—will drop to 47 days as demanded by Google, Apple and Microsoft. - Kevin Bocek, Venafi, a CyberArk Company Quantum computing could soon transform large language model training by accelerating matrix operations and optimization, potentially breaking today's cost barrier. With skyrocketing demand for AI and breakthroughs like DeepSeek, quantum-accelerated AI may arrive faster than expected, as the extremely well-funded AI industry considers this its most urgent problem. - Reuven Aronashvili, CYE Municipal and industrial water systems lose an estimated 20% to 30 % of the water they pump through undetected leaks, pressure miscalibration and energy-hungry pumps. Finding the optimal combination of where to place sensors, how to set valve pressures and when to run pumps is a classic combinatorial-optimization headache; the search space explodes as a network expands. It's a perfect use case for quantum. - Jon Latshaw, Advizex Quantum computers could impact AI by generating high-fidelity training data for domains like pharmaceuticals, chemistry and materials design, where real-world training data is scarce. They can accurately simulate the complex molecular structures needed for training generative AI algorithms. The synergy of quantum computing and AI is poised to be more transformative than either technology alone. - Stephanie Simmons, Photonic Inc. Most of us focus on the risks of quantum in relation to breaking public key cryptography. Quantum will also have a positive impact by preventing and detecting attacks early through its ability to solve complex problems related to pattern recognition and anomaly detection (especially in complex ecosystems). As cybersecurity becomes a priority, investments in quantum are expected sooner rather than later. - Chris Dimitriadis, ISACA By combining AI with quantum computing, we could see quantum-enhanced 401(k) plans that deliver hyper-personalized portfolios. These plans would offer real-time rebalancing based on quantum simulations analyzing millions of combinations. The result is a shield against unexpected market turmoil, providing workers with consistent retirement plans that adapt throughout their careers. - Chris Willis, Domo Quantum algorithms enhance financial simulations—such as Monte Carlo methods, used for risk evaluation and scenario building—by reducing the number of qubits required and lowering associated costs. Key applications include improving efficiency, calculating value at risk and modeling market dynamics for traders. Managing these advancements will be essential to prevent unfair monopolization of data and to ensure equitable access to the benefits of quantum computing. - Jeff Schmidt, ECI One unexpected application of quantum is optimizing supply chains in agriculture. Based on my experience with AI in agri-tech, quantum computing could transform how we model weather, predict yields and optimize commodity logistics, performing much faster than traditional systems. This could bring real-world impact—sooner than most anticipate—in terms of food security and sustainability. - Suri Nuthalapati, Cloudera Quantum computers have a significant advantage over classical computing in terms of simulating complex molecular interactions. This can lead to accelerated research in the area of sustainable and renewable energy development. This is especially critical given the proliferation of EVs and high-energy AI applications. - Arun Kumar, Material Quantum computing could accelerate value-based care by solving optimization problems that current AI and cloud systems can only approximate. Even with today's technology, care plan design across thousands of patients requires extensive manual work. Quantum systems can evaluate all possible interventions and constraints in parallel, enabling faster, more precise and globally optimized care strategies. - David Snow, Jr., Cedar Gate Technologies Quantum computing could significantly impact cloud solutions by transforming how providers optimize resource scheduling, load balancing and traffic routing. Today's cloud systems rely on classical algorithms that struggle with the complexity of real-time global workloads. Quantum algorithms could dramatically improve efficiency and data center energy use, ensuring greener cloud operations. - Rahul Bhatia, HCL Tech
Business Recorder
06-06-2025
- Business
- Business Recorder
US fund taps Pakistani tech duo with $10mn to lead startup investment initiative
The JR Dallas Tech Fund has announced $10 million investment to Pakistani technology leaders Mehwish Salman Ali and Malik Mudassir, entrusting them to inject the fund into exclusive US-focused startup investment initiatives, Business Recorder learnt on Friday. 'Under this landmark agreement, Ali and Mudassir will receive $10 million in dedicated capital to identify, evaluate, and invest in high-potential startups planning to scale operations in the United States. The duo will serve as lead investment partners with full authority to deploy capital across artificial intelligence (AI), cloud computing, digital health, and frontier technology ventures,' a press statement read. 'We are entrusting $10 million to two of the most visionary technology leaders of our generation,' said Jehangir A. Raja, Managing Partner at JR Dallas Tech Fund, which is the premier private investment arm of the US-based JR Dallas Wealth Management. Forbes Technology Council: Pakistani-origin Mehwish selected as member The two Pakistani technology leaders are running their offices in Karachi and Lahore. They represent 'perfect combination of technical expertise, entrepreneurial success, and strategic vision needed to identify the next generation of game-changing startups ready to conquer the American market,' Raja added. Mehwish Ali is a founding CEO of Data Vault that is claimed to be Pakistan's first solar-powered and quantum-encrypted AI data center. She is a co-founder of Zahanat AI, the country's first indigenous GPT model, and COO of AppsGenii Technologies. She is a TEDx speaker and Forbes Technology Council member. Mudassir is founding CEO of AppsGenii Technologies, operating across the US, UK, and Pakistan. He is a co-founder of ventures including GharPar, BoxesGen, and Dental Connect. He is also a member of the Central Executive Committee at P@SHA (Pakistan Software Houses Association). According to the statement, the $10 million fund operates under a rigorous investment framework designed to maximise both financial returns and economic impact. Startup Neem enters logistics space with Leopards Courier Services partnership The investment is targeted to be in the range of $250,000 to $1.5 million per startup. The investment should be focused in the sectors like AI/machine learning, cloud infrastructure, digital health, quantum computing and cybersecurity. The investor is aimed at investing the entire fund into 15-20 select companies over a period of two-year in the US-focused projects. The funding is projected to enable portfolio companies to create direct jobs, generating 300-500 high-skilled technology positions within 24 months. Strengthening Texas as a hub for international tech talent entering the US market. Accelerating breakthrough technologies in AI, healthcare, and cloud infrastructure. 'Portfolio companies (are) projected to contribute $50-100 million in US economic activity within three years,' the statement read.
Forbes
23-05-2025
- Business
- Forbes
20 Modern Tech Tools That Are Advancing Public Safety
From drones and digital twins to AI-assisted emergency response systems, technology is transforming how communities prevent, detect and respond to threats. Whether it's faster 911 dispatch, safer infrastructure or smarter surveillance, these innovations are quietly reshaping public safety at every level—even saving lives. Below, Forbes Technology Council members discuss modern tech tools that have positively impacted public safety in recent years. Here's how they believe the capabilities and influence of these technologies might evolve in the near future. Tech is reshaping public safety by helping schools detect early signs of crisis, whether it's mental health, cyberbullying or potential threats. In the future, these systems may shift from alert-based tools to proactive support networks, connecting students with help before issues grow into emergencies. Prevention, not just response, will define the next chapter of school safety. - Saby Waraich, Clackamas Community College Technologies using biological data significantly enhance public safety, preventively and investigatively. For example, biometric systems like facial recognition aid prevention by identifying suspects or wanted individuals. Post-incident forensic biotechnology, such as DNA analysis, is key to accurately identifying suspects or linking them to scenes. - Sourabh Kukar, Salesforce Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify? When people talk about public safety, they often forget that highly dense areas will have more issues, and they will also often have a higher percentage of low-income constituents. Public offerings like cameras, shot detection and Wi-Fi provide the ability for residents to share information in real time and receive help faster, and they are provided at no cost to the public. - Tara Duke, As a frequent traveler, this feels personal. AI-based predictive maintenance and anomaly detection for commercial aircraft is one of the biggest safety advancements, detecting issues before they become risks and solving them before they escalate into emergencies. The advancements will continue, and in the future, AI will predict failures even earlier, making air travel even safer and smarter. - Gundeep Singh, EY Railway safety systems—like Positive Train Control (PTC), developed in the U.S., and Kavach, developed in India—have significantly improved public safety. These systems use GPS and sensors to monitor train movements and automatically apply brakes to prevent collisions, derailments and accidents. - Manikandarajan Shanmugavel, S&P Global Telemedicine platforms have made healthcare more accessible, improving safety by enabling quicker, remote consultations between patients and healthcare providers. As adoption of telemedicine grows, so will its potential to prevent medical errors. - Hui Sang Yun, Endo Health Fall detection, which is now a feature of many mobile phones and smartwatches, has significantly accelerated first-aid provisioning to the injured since its inception. Fall detection has also recently been added to some Internet-of-Things-enabled smart home devices, enhancing safety and care for the elderly. While this technology is more prevalent in Western countries, as costs fall, it will expand globally. - Bihag Karnani, Google Mass notification systems have significantly enhanced public safety by enabling authorities and emergency responders to rapidly share critical alerts with the public across multiple channels—text, voice, email and so on. Whether it's severe weather, active shooter incidents or hazardous material spills, these tools play a vital role in improving situational awareness and facilitating timely responses. - Judit Sharon, OnPage Corporation Autonomous 'drone as first responder' (or DFR) fleets are quietly reshaping emergency response. Launched from a rooftop dock when a 911 call is received, a drone can reach the scene in minutes and stream live video and thermal data, allowing dispatch teams to cancel false alarms or tailor resources. As Beyond Visual Line of Sight (BVLOS) rules mature and 5G edge computing spreads, citywide drone swarms could respond to every major incident before ground units roll. - Rohit Anabheri, Sakesh Solutions LLC Gunshot detection systems have improved public safety by enabling faster responses to shooting incidents. These acoustic sensors automatically alert police with a precise location within seconds of gunfire, reducing response times from four to five minutes to under 60 seconds. Future integration with surveillance cameras, emergency services and AI/ML will further enhance these systems' life-saving capabilities. - Ambika Saklani Bhardwaj, Walmart Inc. Next generation 911 (NG911) has improved public safety by allowing text, images, videos and real-time location data to reach emergency services. The impact will only grow as AI wearables and smart devices are integrated, enabling faster, more precise responses—even, potentially, predictive dispatch—and better assistance in critical situations. - Rahul Wankhede, Humana Advanced data recovery systems have dramatically improved public safety by enabling the rapid restoration of critical information during disasters and cyberattacks. When emergency services lose access to vital records during crises, these technologies ensure continuity of operations while minimizing downtime. - Chongwei Chen, DataNumen, Inc. Digital twin technology is an emerging force in public safety. Cities are now creating real-time virtual replicas of infrastructure—like bridges, tunnels and power grids—to simulate disasters, predict failure points and coordinate emergency response. As sensor coverage grows, these digital twins will evolve into live command centers, enabling safer, faster decisions during crises. - Pawan Anand, Ascendion AI-powered transcription and analysis tools are transforming public safety by making police body camera footage and court proceedings searchable and transparent. These tools help surface patterns of misconduct, reduce case backlogs and ensure greater accountability. As adoption spreads, they could become foundational for equitable and data-driven criminal justice reform. - Alessa Cross, Ventrilo AI One impactful technology is the security robot dog, or 'robodog.' Equipped with cameras, sensors and AI, it helps patrol public areas, detect threats and relay real-time data to authorities. As AI advances, its role could expand into crowd control, disaster response and autonomous emergency alerts, further enhancing public safety. - Nikhil Jain, SmartThings, Inc. Earthquake early warning systems—like ShakeAlert, used on the U.S. West Coast—provide advance warning seconds or even minutes before the shaking starts. These systems allow people to take shelter and critical systems to automatically engage safety protocols. Further, these systems could be integrated into existing apps and services to widen their reach and impact. - Ishaan Agarwal, Square Crowd-sourced traffic apps have quietly improved public safety. By letting users share real-time alerts about accidents, hazards or blocked routes, they help others avoid danger and reduce the risk of follow-up crashes. As these platforms integrate with smart city systems and emergency responders, they could evolve into real-time, community-powered safety networks. - Umesh Kumar Sharma License plate recognition is an underrated force in public safety, automatically sending alerts for stolen vehicles as well as AMBER Alerts. As it scales and syncs with smart city infrastructure, LPR can help forecast and disrupt crimes before they unfold. - Joseph Olorunyomi, Accomplishr Advanced Driver Assistance Systems have transformed road safety by using AI, sensors and real-time data to prevent accidents. Features like automatic braking, lane-keeping and blind-spot detection help reduce human error, the leading cause of crashes. As technologies like vehicle-to-everything communication advance, ADAS has the potential to save even more lives and make roads safer. - Udit Mehrotra, Amazon AI-driven emergency dispatch systems are quietly reshaping public safety. By analyzing incoming calls, location data and historical patterns in real time, they can prioritize the most urgent cases faster and route help more efficiently. As these systems evolve, we'll see lifesaving responses become even faster and more precise. - Zohar Bronfman, Pecan AI
