Techaisle Blog

The cybersecurity landscape is constantly evolving, presenting significant challenges and driving changes in security adoption trends across Small and Medium-sized Businesses (SMBs) and midmarket firms. Insights from the Techaisle SMB and Midmarket Security Adoption Trends Report reveal a complex picture of preparedness, perceived risks, emerging priorities, and strategic shifts in security spending and solution adoption. This analysis will delve into these trends, highlighting the distinct realities faced by small businesses (1-99 employees), Core Midmarket (100-999 employees), and Upper Midmarket (1000-4999 employees) firms.

Current State of Cyberattack Readiness: A Landscape of Vulnerability

The report underscores a concerning level of unpreparedness among SMBs and midmarket firms, despite the rising threat landscape. A significant portion of SMBs lack fundamental security measures: 46% have no security protocol in case of an incident, 51% lack formal risk frameworks, and a striking 83% have no formal security awareness training for their employees. This translates into a feeling of being under-prepared, with 68% of SMBs believing they are less prepared than their peers. Furthermore, 61% of SMBs feel that native cloud security is insufficient, and 43% have experienced a security incident, with most small business attacks going undetected. The average financial loss for SMBs due to security incidents is reported to be $1.6 million, and 62% are not very confident in their ability to recover from such an incident.

Midmarket firms, while slightly better equipped, still face significant gaps. 34% of midmarket firms have no security protocol, 35% lack formal risk frameworks, and 72% have no formal security awareness training. 49% feel under-prepared compared to peers, and 60% believe native cloud security is insufficient. Midmarket firms experienced security incidents at a higher rate of 57%, and the average financial loss due to these incidents was substantially higher at $11 million. Only 36% are not very confident of recovering from a security incident, indicating a slightly higher, yet still concerning, level of confidence compared to SMBs.

Executive Vice President and Chief Customer Experience Officer, Liz Centoni's vision for Cisco's Customer Experience (CX) organization is bold, future-ready, transformative, and complete. This vision is fundamentally reshaping how customers interact with and derive value from their technology investments. Cisco's CX strategy centers on leveraging Generative AI and Agentic AI to move beyond reactive support towards proactive, predictive, and personalized assistance throughout the entire customer lifecycle—from initial planning and deployment to ongoing operation and renewals.

Cisco is achieving this by digitizing decades of historical knowledge, establishing standardized workflows, and developing AI-powered tools, such as intelligent agents, delivered through unified platforms. These innovations provide actionable insights, tailored recommendations, and automated actions. The overarching goal is to revolutionize customer experience by simplifying operations, enhancing customer value, and accelerating time to value for both customers and partners, all while carefully maintaining the critical elements of human expertise and trust. I firmly believe that this forward-thinking strategy positions Cisco CX to enhance resilience and simplify complexity in an increasingly intricate technological landscape.

As an industry analyst at Techaisle, my analysis of Cisco's CX strategy reveals several critical insights. Here, I will delve into the competitive differentiation these developments offer Cisco, their tangible benefits for customers, and the fresh opportunities they unlock for channel partners:

AWS Marketplace, a platform synonymous with accelerating procurement and fostering innovation, is undergoing a significant transformation, propelled by the strategic integration of Artificial Intelligence (AI). A recent briefing offered deep insights into how AWS is leveraging AI, not just as a new product category, but as a core engine to enhance the experience for both customers and partners, particularly Independent Software Vendors (ISVs). The briefing highlighted a comprehensive approach, applying AI across the entire AWS Marketplace lifecycle – from discovery and procurement to partner operations, support, and co-selling motions. This isn't merely a superficial application of AI; it's a fundamental shift aimed at increasing speed, efficiency, visibility, and ultimately, mutual success for AWS and its vast partner community.

The Vice President for AWS Marketplace and Partner Services, Matt Yanchyshyn, shared that the excitement within their engineering teams over the past three to six months has been palpable, directly correlating with the meaningful improvements realized through AI. While AI has been used internally for years, recent advancements, particularly in areas such as prompt-driven development and what some refer to as agents, have led to a "step change" in engineering velocity and the features exposed to users. The focus is on specific, realized time and cost savings, both internally and externally.

AWS Marketplace itself has evolved dramatically since its inception as a self-service software marketplace. It now encompasses software as a service (SaaS), containers, large language models (LLMs), professional services (including consulting and managed services), and data. This breadth positions AWS well to serve emerging trends, such as the increasingly fast-evolving drift of combining private and third-party data sources with AI in the form of agents or foundation models. The core value proposition of the marketplace remains speed in the procurement journey, which is deemed paramount, especially in the context of AI, where rapid experimentation and access to technologies like LLMs or vector databases are crucial for innovation. Slow procurement kills innovation.

The strategic underpinning for this AI-driven transformation is the concept of "Marketplace Everywhere". This four-part strategy involves using AWS Marketplace to power partner experiences across AWS service consoles, including Amazon Bedrock, Amazon SageMaker, and Amazon Elastic Kubernetes Service (EKS). It involves integrating AWS Marketplace into every sales motion, making it a core component of co-selling. It means bringing AWS Marketplace to every country where customers do business with AWS. Crucially, it also involves exposing the same APIs used internally to power experiences across AWS service consoles publicly. This "Buy with AWS" capability enables third parties, such as ISV websites or distribution partners, to embed AWS Marketplace listings directly into their own experiences. This distributed approach ensures that AI buyers, who may be scientists, developers, or future line-of-business users, can discover and buy AI capabilities within the tools and platforms they already use, democratizing access and meeting customers where they are.

Now, let's delve into the key takeaways regarding AI's impact on AWS Marketplace and the significant advantages it offers partners and ISVs.

Dell Technologies World 2025 (DTW) recently provided a comprehensive look into Dell's strategy and vision, with a particular focus on the transformative power of Artificial Intelligence (AI) for businesses of all sizes. Keynotes from Michael Dell and Jeff Clarke, alongside detailed briefings on Client Solutions Group (CSG) and Infrastructure Solutions Group (ISG), painted a picture of a company positioning itself as the end-to-end partner for the AI journey. While much attention often focuses on hyperscalers and large enterprises, Dell offers significant opportunities and tailored strategies for the midmarket as well as the vital channel partners who serve them.

Here are my seven key takeaways:

1. The Dell AI Factory is an End-to-End AI Framework, Not Just Hardware

Dell introduced and expanded upon the concept of the Dell AI Factory, describing it as an unmatched set of capabilities in the industry designed to help businesses get started with Generative AI and scale it. It is presented as an open, modular infrastructure with a rich ecosystem, delivering powerful GPUs, scalable storage, high-throughput networking, curated tooling, and integrated cutting-edge models, supported by deployment services. This framework covers the entire computing architecture for modern AI workloads, from PCs to data centers and the edge. Dell has helped over 3,000 businesses build their factories and launched over 200 new features since its inception a year ago. The vision is for customers to bring their own company data to the AI Factory, driving unique business outcomes.

Why this is important for Midmarket and Channel Partners: This framework provides a structured approach to AI adoption. For midmarket, it demystifies the complex landscape of AI infrastructure by offering a seemingly integrated and supported stack. They don't need to piece together disparate components or become AI experts overnight. For channel partners, the AI Factory is a complete solution portfolio to take to customers. Dell is making it easier to consume and deploy through reference architectures and packaged software. This enables partners to concentrate on delivering value and outcomes, rather than merely selling individual pieces of hardware. The concept of bringing "your own company data" to drive outcomes resonates strongly with businesses of all sizes, emphasizing that AI value is tied to their unique operations and data, which partners are often intimately familiar with.