After decades in the background, high-speed aviation is drawing renewed attention from investors, manufacturers, and regulators. The convergence of global economic pressures, advanced materials science, and digital engineering is reshaping what’s possible for commercial and cargo at high flight speeds. While Concorde proved the allure of supersonic travel, it also revealed the technical,  operational and economic constraints that grounded the aircraft in 2003. Now, the next generation of aerospace innovators is targeting more sustainable, economically viable, and mission-flexible platforms.

After decades of false starts, high-speed aviation is moving closer to a commercially viable comeback — this time driven not by prestige or Cold War competition, but by structural shifts in global commerce, advances in propulsion and materials, and new approaches to financing large-scale aerospace programs.

The distributed denial-of-service (DDoS) threat landscape is undergoing a radical transformation. No longer the domain of high-cost, high-complexity adversaries, the ability to launch sophisticated and disruptive DDoS campaigns has been democratized by artificial intelligence (AI). These capabilities are no longer limited to nation-states or cybercrime syndicates.

The rise of artificial intelligence is transforming the nature of distributed denial‑of‑service (DDoS) attacks, creating a new level of urgency for mid‑market manufacturers and industrial operators to strengthen their cyber defenses. According to Michael Honeycutt, who leads product marketing at Corero Network Security, the latest wave of AI‑assisted DDoS activity is faster, more adaptive, and more accessible to would-be attackers than ever before.

Healthcare organizations are grappling with an intensifying cybersecurity crisis. Sophisticated ransomware groups, vulnerable legacy systems, expanding digital footprints, and limited security resources have combined to create what some experts call a “perfect storm” of risk exposure. To explore how providers can better protect themselves, BizTechReports spoke with Vince Crisler, Chief Strategy Officer of Celerium, a cybersecurity firm focused on automated detection and surgical containment of cyber threats.

As digital transformation strategies mature across industrial sectors, the limitations of centralized cloud architectures are becoming harder to ignore. For critical applications in manufacturing, energy, finance, and healthcare, the need for real-time decision-making has propelled edge AI from a futuristic concept to a present-day operational requirement. Below are key takeaways from the webinar “Establishing a Framework for Transforming Industrial Operations with Real-Time Edge AI,” in which Penguin Solutions' John Chaves shared his perspectives on the emerging trajectory of innovation in industrial environments.

The life insurance industry is steadily overcoming long-standing friction to digital transformation as consumer expectations, regulatory demands, and operational inefficiencies converge with emerging technologies and viable AI-enabled business strategies. While historically slow to modernize—due in part to legacy systems, complex stakeholder relationships, and a risk-averse culture—the sector is now reaching a tipping point. Accelerated by the pandemic and reinforced by changing demographics, insurers are embracing tools that promise both efficiency and enhanced customer engagement. 

As AI workloads move closer to the data source, organizations are being forced to reassess how they structure infrastructure, coordinate operations, allocate investment, and govern change. This shift was explored in depth during a webinar hosted by Penguin Solutions (formerly Stratus Technologies) titled “Establishing a Framework for Transforming Industrial Operations with Real-Time Edge AI,”.

In this Q&A, Krauthamer explains the strategic context of the quantum threat, operational readiness challenges, cost dynamics, and how crypto-agility can serve as both a security enabler and a source of long-term risk reduction. Her insights are grounded in both national defense experience and enterprise adoption, making this conversation essential for cybersecurity and IT leaders navigating the quantum era in both private and public sectors.

As artificial intelligence (AI) transforms nearly every industry, the property technology sector—PropTech—is seeing a surge in innovation across leasing, operations, asset management, and portfolio strategy. To better understand how AI is being deployed within commercial and residential property ecosystems, BizTechReports spoke with Carla Hinson, Vice President of Solution and Innovation at MRI Software. With nearly three decades of experience in real estate technology, Hinson offers grounded insight into how AI is moving from pilot to practice in a traditionally risk-averse industry.

“People talk about Q-Day like it’s a future event,” said Rebecca Krauthamer, Co-Founder and CEO of QuSecure, a cybersecurity company that provides post-quantum cryptography (PQC) solutions, in a recent executive conversation. “But from a risk management perspective, we’re already there. Data that’s being stolen now could be exposed later by quantum technology. This is worrisome for data that has a long shelf life, like medical records, intellectual property, or classified communications.”

The property technology sector—PropTech—has entered a phase of accelerated disruption, driven by the convergence of artificial intelligence, legacy system modernization, and shifting economic pressures across residential, commercial, and industrial segments. What began as a fragmented landscape of point solutions is rapidly evolving into an interconnected ecosystem where strategic data access, automation, and predictive analytics define competitive advantage.

Autonomous delivery is poised to become a standard feature of logistics—but a key element of that ecosystem has long gone unaddressed: where do drones, robots, and unmanned vehicles actually deliver their payloads? According to Dan O’Toole, CEO of Arrive AI, the answer lies not in the sky, but at the curb.

The lack of intelligent, secure, and universally accessible delivery endpoints has emerged as a critical gap in the autonomous delivery ecosystem. Long overshadowed by the spectacle of unmanned aerial vehicles and sidewalk rovers, these “last-inch” infrastructure platforms may be the linchpin in the transition to autonomous delivery at scale.

The growing reach of AI across business operations is reshaping the demands placed on data centers in every industry. This BizTechReports briefing synthesizes insights from four recent reports to explore how data centers are evolving—consolidating platforms, securing new power sources, adopting more flexible investment models, and redesigning infrastructure to support AI at scale.

As generative AI reshapes the automation landscape, mid-market enterprises are under pressure to modernize—without the disruption or cost traditionally associated with large-scale transformation. In this exclusive BizTechReports interview, Mahesh Vinayagam, CEO and Founder of qBotica, explains how combining generative AI with robotic process automation (RPA) is changing the game.

The U.S. mortgage sector is at a crossroads. For decades, the process of getting a home loan has been synonymous with paperwork, stress, and a lack of transparency. But the convergence of artificial intelligence, rising consumer expectations, and housing market volatility is forcing the industry to evolve. With affordability challenges mounting and younger, tech-savvy buyers entering the market, lenders are being pushed to rethink not just how they operate—but why.

As artificial intelligence (AI) reshapes the enterprise technology landscape, industry leaders are rethinking modernization strategies to balance agility, security, and compliance. That was the key takeaway from a recent CIO Magazine roundtable, co-hosted by Skyla Loomis, Vice President of IBM Z Software, and John Currie, Partner, Mainframe Application Modernization at IBM.

Chris Miller, Vice President of Sales and Marketing at ATB Technologies, brings firsthand perspective on how SMBs are navigating this transformation. As a managed services provider (MSP) with deep roots in manufacturing, engineering, and nonprofit sectors, ATB is working on the front lines to help organizations adopt AI in ways that are responsible, practical, and tailored to their specific needs.

The AI revolution is no longer confined to the Fortune 500. With copilots, chatbots, and machine learning tools becoming increasingly accessible through mainstream productivity suites and cloud platforms, small and midsize businesses (SMBs) are confronting a new set of strategic, operational, and technological decisions—many without the internal expertise typically found in enterprise environments.