Dr. Aditya Vikram Kashyap

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In an agentic era, the most effective PMs will be distinguished not just by what they can build, but by how they lead, communicate, and make decisions amid increasing complexity and automation. Skills like strategic judgment, cross-functional influence, adaptability, customer empathy, and ethical reasoning are becoming non-negotiable. To help product leaders, I ask members of the Product Management Group, a community that I lead through Forbes Technology Council, for skills that will define which PMs can align teams, inspire trust and guide products toward meaningful outcomes.

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A surge of bug reports and feature requests right after a new product or feature launch doesn’t always mean the release failed. But it can signal that the development team missed something important during planning, user acceptance testing or prelaunch validation. Before a product reaches users, dev teams need to understand not only whether it works but also whether it fits real customer needs, workflows and expectations. Below, members of Forbes Technology Council discuss some of the common reasons dev teams receive a steady stream of bug reports and feature requests shortly after a new product or feature release as well as tips to avoid these costly planning and testing missteps.

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Semiconductor sovereignty, as it is usually imagined, may be structurally unattainable.

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Last year, the FBI declared that older adults reported losses exceeding $7.5 billion due to fraud. As fraud and scam tactics grow more sophisticated, AgeTech leaders face an urgent mandate: Stay ahead of the innovations designed to protect older adults in real time. As illustrated in the movie The Beekeeper, the greatest challenge—and opportunity—lies in intervening at the very moment a scam unfolds. Emerging AI-powered solutions are making this possible, with tools that can detect suspicious behavior, alert caregivers or institutions, and even terminate harmful interactions before damage is done. One such example is Shield Seniors, an AI-powered app created by 17-year-old Tejasvi Manoj after her 85-year-old grandfather nearly fell victim to an online scam. By leveraging advanced analytics, machine learning, data privacy and security protocols, and AI-driven alerts, companies in this space help older adults and their families recognize and avoid threats. Such innovations underscore why proactive monitoring of the latest technologies and ever-evolving threats is no longer optional for leaders—it’s essential to safeguarding a vulnerable and growing population. To gain insights into leading approaches, I asked members of the Age Tech Group, a community that I lead through Forbes Technology Council, about specific actions that leaders can implement to help protect older adults from scams.

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In practice, retrieval is a system with its own failure modes, its own latency budget and its own quality requirements.

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What makes behavioral drift more dangerous than hallucinations is not just its invisibility but its self-concealing quality

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With constant disruption—from geopolitical shocks to AI-driven transformation—competitive advantage in supply chain is increasingly defined by the assets leaders choose to prioritize. No longer limited to physical infrastructure or cost efficiencies, today’s strategic assets span data visibility, digital capabilities, supplier ecosystems, and organizational agility. Those who stay attuned to which assets will matter most—not just today, but in the near future—are better positioned to adapt, invest wisely and outperform peers. I ask members of the Supply Chain Group, a community that I lead through Forbes Technology Council, how leaders can achieve resilience and long-term competitiveness in their field.

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From 4G to 5G and now 6G, the conversation around each new wireless generation usually centers around improved velocity and bandwidth. But most organizations aren’t simply seeking to download things faster; they’re trying to make decisions quicker, automate with more confidence, and support connected systems at greater scale. The bigger story behind 6G may be what happens above and beyond raw speed enhancement, ranging from more reliable operations and smarter systems to entirely new ways to connect people, devices and physical environments. As workforces, infrastructure and customer experiences become more distributed and data-driven, the real business value of 6G may come from capabilities that make connectivity more intelligent, dependable and adaptable. Below, members of Forbes Technology Council discuss some of the important capabilities 6G could bring to business and industry.

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The expensive part of AI is not building the model. It is every decision the model makes afterward.

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As organizations expand their use of cloud services, many are discovering that operating across multiple providers can quickly get complicated. While multicloud strategies can improve flexibility and resilience, they can also create friction around performance, cost management and interoperability. One proposed answer is “Sky Computing,” a model introduced by researchers at UC Berkeley that would let applications work more seamlessly across multiple cloud providers. Below, members of Forbes Technology Council discuss one real-world enterprise problem this kind of approach could realistically help solve today.

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If the only way to understand a system is to observe it, then your observability infrastructure is not operational overhead.

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As breakthroughs in quantum computing, artificial intelligence and robotics begin to intersect, a new class of market-making technologies is emerging. Quantum systems promise unprecedented optimization and simulation capabilities, AI enables real-time learning and decision-making, and advanced robotics brings those insights into the physical world. To help business leaders and innovators understand how this convergence can unlock new markets and untapped growth, I ask members of the Quantum Computing Group, a community that I lead through Forbes Technology Council, for game-changing applications that are reshaping industries.

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Successful leaders stay in difficult rooms long enough to find out what they are made of.

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In data-driven organizations, the distance between upstream and downstream teams can quietly become a fault line. Data engineers, platform architects, and infrastructure leaders focus on pipelines, governance, and reliability, while analytics, product, and business teams push for speed, insights, and measurable outcomes. When these groups operate in silos, even the most sophisticated data investments stall—buried under misaligned priorities, unclear ownership, and competing definitions of success. From my experience leading tech teams, one effective way to bridge the gap between upstream and downstream teams is by aligning business and technical drivers from the start. Silos are the true enemy of progress. Every successful data initiative needs a common framework that clearly defines how data is propagated, governed and maintained across the landscape. When both business and technology teams share this unified view, collaboration extends across horizontal and vertical layers of the enterprise architecture and business value. To help tech leaders turn fragmented workflows into high-impact, insight-driven execution, I asked members of the Leveraging Data Group, a community that I lead through Forbes Technology Council, for game-changing ways to align upstream and downstream teams.

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Quantum computing isn’t mainstream yet, but the security implications are already on tech leaders’ radars. Today’s widely used public-key encryption standards were designed for classical computers, not the processing power quantum machines are expected to deliver. For organizations that store intellectual property, financial records or regulated data that must remain confidential for years, the concern isn’t just future breaches. It’s the possibility that encrypted data stolen today could be decrypted later once quantum capabilities mature. Forward-thinking leaders are taking steps to understand where long-lived sensitive data resides and how it’s protected, as well as to modernize cryptographic strategies to build long-term resilience. Below, members of Forbes Technology Council share practical steps organizations can take now to support a smoother shift toward quantum-safe security.

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Institutions need to stop treating transparency as a burden imposed by automation and start treating it as a debt owed from long before automation arrived.

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Across industries, employees are quietly building their own AI-powered micro-automations to streamline routine tasks, analyze data and speed up everyday workflows. This rise of “shadow AI” can raise legitimate concerns around security, compliance and data governance, but it also reflects a workforce that’s eager to experiment and solve problems in real time. Rather than trying to shut it down, many leaders are asking how to channel that energy into something secure and scalable. Below, members of Forbes Technology Council share constructive ways leaders can harness employee-driven AI innovation while maintaining oversight, alignment and trust.

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AI agents are quickly moving from behind-the-scenes automation to front-and-center decision-makers inside digital products. While they promise speed, personalization, and scale, they also introduce a new set of challenges for product managers and UX designers—ones that don’t fit neatly into traditional roadmaps or user flows. For example, as a digital project management leader, one challenge I see is that traditional event-based analytics, such as clicks, are becoming obsolete. PMs in 2026 now must rely on experience analytics and predictive metrics to track how effectively an agent is navigating the context of a user's journey. To help PMs prepare their teams as autonomy increases, I ask members of the Product Management Group, a community that I lead through Forbes Technology Council, to share emerging challenges that AI agents create for UX design.

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AI-powered coding assistants promise speed and creativity, but when Vals AI recently tested AI models to discover which performed best as a vibe coding partner, the top-performing model, GPT-5.2, accurately created features as requested less than half the time. While AI continues to improve, engineering teams can’t afford to treat it as a hands-off solution.  Instead, organizations must learn how to use AI tools to speed and smooth established development workflows, balancing experimentation with rigor, oversight and accountability. Below, members of Forbes Technology Council share smart development practices for safely and effectively partnering with AI for vibe coding.

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As populations age around the world, the question is no longer whether technology can support older adults—but how meaningfully it can extend independence, dignity, and quality of life. For example, robotics can provide real-time physical support to prevent or reduce the impact of falls. These breakthroughs in robotics are moving well beyond novelty, offering practical solutions that help seniors live longer, safer, and more self-directed lives. To highlight emerging age tech, I ask leaders in the Age Tech Group, a community that I lead through Forbes Technology Council, for breakthroughs that should be on our radar.

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The greatest risk in financial AI isn't that machines will make mistakes. It's that institutions will believe they understand those machines when they don't.

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In 2025, “security misconfiguration” jumped to the No. 2 spot on the “OWASP Top Ten” list, underscoring how frequently basic setup mistakes weaken critical digital systems. Quick decisions made during deployment or “temporary” exceptions that are allowed to linger can significantly expand cyber risk across an organization.  Often, breaches don’t stem from sophisticated hacking techniques; instead, they are the byproducts of speed, increasing complexity and missing human oversight in modern IT environments. Below, members of Forbes Technology Council share the misconfiguration mistakes they see most often in the wild and offer practical guidance on how teams can reduce exposure.

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Consumers are increasingly aware that their personal information fuels everything from targeted advertising to AI development, yet they rarely see direct financial returns from that value. And specialized businesses are often sitting on a goldmine of valuable data but don’t have straightforward pathways to share or benefit from it. As concerns around privacy, consent, and data value and ownership grow, so does startups’ interest in changing how data is collected, governed and monetized. A growing number of business models aim to help organizations share and profit from their data resources—and give users more control over their data and a stake in the upsides it creates. Below, members of Forbes Technology Council share their perspectives on data monetization strategies they believe could realistically work at scale.

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A growing number of leaders have driven unexpected product-led growth by running bold experiments that challenged assumptions, reimagined customer experiences, and reshaped how value is delivered. From unconventional partnerships to radically simplified onboarding and delight-driven features, product managers have seen that risk-taking inside the product itself can unlock surprising momentum. To help others learn from these experiments, I asked members of the Product Management Group, a community that I lead through Forbes Technology Council, for examples of bold bets that paid off.

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As synthetic data requires discipline, there are key processes to make sure this approach is anchored.

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Event-driven architectures let software react to events in real time, with services publishing signals like “order placed” or “payment completed” that other services can subscribe to and act on. The approach can improve responsiveness and scalability and reduce tight coupling between teams and systems. But the trade-off is complexity that grows as events, producers and consumers multiply, making it harder to trace what happened, where something broke and who owns the fix—especially when events arrive late, out of order or more than once. Below, members of Forbes Technology Council share challenges teams should anticipate when shifting to event-driven applications and how to mitigate them before the architecture turns into a black box.

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When AI-driven advantage depends on moving fast and scaling globally, organizations hit a familiar wall: data sovereignty. As countries tighten rules around how and where data can be stored and processed, leaders face a growing tension between protecting sensitive information and unleashing the full power of hyperscale innovation. The challenge isn’t choosing one or the other—it’s reconciling both. To stay competitive, I ask members of Cloud Computing Group, a community that I lead through Forbes Technology Council, for ways that organizations can build architectures that honor local compliance while preserving interoperability.

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The battle for trust will be determined by the authenticity of machines that increasingly make decisions on our behalf.

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Decentralized physical infrastructure networks, or DePIN, could represent the next step in how society builds and maintains essential systems. In these models, members of the public contribute to running real-world networks—such as wireless coverage, energy grids or sensor deployments—by supplying hardware or resources, creating infrastructure powered by community participation instead of large corporations. It’s an ambitious idea, and it comes with significant challenges—DePIN projects will need to match the stability, reliability and ease of use people expect from traditional providers if they hope to scale beyond early adopters. Below, members of Forbes Technology Council share the biggest hurdles DePIN networks must overcome to move past experimentation and earn mainstream confidence.

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Older adults represent one of the most powerful yet overlooked consumer segments in today’s economy. With more than $7 trillion in buying power, according to AARP research, this demographic is redefining what it means to age — embracing technology, wellness, travel, and lifestyle experiences at unprecedented rates. Yet many brands still underestimate or misunderstand their influence. Tapping into this market isn’t just a matter of inclusion; it’s a strategic advantage for businesses ready to innovate around the needs and aspirations of a rapidly growing population. From the same research, 77% of older adults want to age in place at home. An unaddressed market opportunity is to take the senior living community concept into one's home. This can look like a package of services and support to promote independence, community living and active engagement without the need to move from one's home or the capital investment of building, staffing and managing a campus. To help business leaders tap into this market, I ask members of the Age Tech Group, a community that I lead through Forbes Technology Council, for one opportunity they see to scale age tech.

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Ambient Internet of Things systems represent a promising step forward in connectivity and sustainability. They comprise connected devices that gather and transmit data, but these devices aren’t powered by batteries; instead, they harvest energy from the surrounding environment in the form of light, radio waves or motion. However, between spectrum congestion, security and identity challenges, and sensors that behave differently depending on location, there are plenty of challenges that must be addressed before ambient IoT can achieve its full potential. Below, members of Forbes Technology Council detail the biggest technical and regulatory barriers that must be overcome for ambient IoT to become a global difference-maker.

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So how can ordinary people resist a war fought with invisible weapons? The answer isn’t paranoia. It’s discipline.

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For organizations modernizing legacy stacks, shifting from a monolithic architecture to MACH (Microservices, API-first, Cloud-native, Headless) promises modular systems that foster easier maintenance and agile innovation. Yet success takes far more than a technical rewrite—the transition often exposes flaws in architecture design, governance and team topology that must be rethought and refined. From “mini monoliths” that replicate legacy dependencies to fragmented ownership models that erode scalability, the real pitfalls of MACH adoption usually stem less from technology than from organizational inertia. Below, members of Forbes Technology Council share the most common failure points they’ve seen in a MACH transition—and the technical and cultural strategies that can help prevent them.

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Emerging technologies—particularly AI—are reshaping industries. Seeking to boost productivity and remain competitive, C-level leaders are often eager to adopt the tools they’re reading about. But enthusiasm at the top doesn’t always translate into clear-eyed risk assessment or well-considered usage plans, leaving organizations vulnerable to operational, compliance and security challenges. Tech experts say bridging the divide between impatient enthusiasm and smart implementation requires more than just new tools—it calls for cultural alignment, shared language between technical and executive teams, and governance frameworks that translate technical risks into business terms. Below, members of Forbes Technology Council share strategies to bring leadership vision and frontline realities into sync.

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Stop fetishizing “the new system.” Success is when people stop calling it new.

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Quantum computing is often framed as the next technological arms race, with nations and corporations vying for breakthroughs that could reshape industries from finance to medicine. But as with any transformative innovation, the question isn’t just who gets there first. It’s who gets to benefit from it. Without intentional design, access to quantum tools and discoveries could be concentrated in the hands of a few, deepening existing inequities. To explore how leaders can prevent that outcome, I asked members of Quantum Computing Group, a community that I lead through Forbes Technology Council, to share actionable steps that ensure quantum computing delivers value for humanity as a whole, not just a privileged minority.

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When a new product is in development, it can be tempting to pack in features to impress investors, potential users or even the internal team. However, an overloaded MVP can dilute the core vision, stall progress and make it harder to see what really works (or doesn’t).  A well-designed MVP solves one painful problem clearly and quickly, without distraction. Below, members of Forbes Technology Council share strategies to help teams stay focused, deliver value without unnecessary complexity, and move efficiently from concept to market.

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AI and intelligent design can be transformative in finance. However, the line between support and manipulation is not fixed.

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Emerging technologies like artificial intelligence and quantum computing have the potential to reshape nearly every industry—but only if global infrastructure evolves fast enough to support them. From intelligent energy systems and ultra-fast connectivity to new governance models and quantum-safe security, foundational upgrades are essential.  The approaching tech revolution requires more than just faster chips or bigger data centers; business and government leaders must rethink how they manage power, information, regulations and talent. Below, members of Forbes Technology Council highlight the most critical infrastructure shifts needed to unlock the full potential of next-generation innovation.

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Self-healing networks—systems that automatically detect, diagnose and fix network issues without human intervention—promise a future of near-zero downtime, automated fault recovery and more resilient digital infrastructure. But for all their upsides, they’re far from a plug-and-play solution. Companies exploring this technology should take the time to understand the complexity, investment and cultural shifts required to do it right. Below, members of Forbes Technology Council share their top advice for businesses evaluating self-healing networks. Their insights highlight not only how to unlock the technology’s full potential, but also what pitfalls to avoid when implementing and managing these systems at scale.

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AI governance is not a legal formality; it's a matter of trust, reputation and long-term business resilience.

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Rolling out self-service analytics isn’t just a tech upgrade—it’s a shift in how people work. To truly empower teams across the business to make data-informed decisions, leaders need not only the right tools, but also a commitment to ongoing training and support. Many companies underestimate the learning curve, particularly for nontechnical users. Below, members of Forbes Technology Council share practical strategies to help turn access to data into real, positive impact on operations and decisions. From role-specific guidance to on-demand help and long-term reinforcement, the right support approach can make all the difference.