Techaisle Blog

Techaisle has released its annual infographics detailing the Top 10 IT Priorities, Challenges, and Business Issues for SMBs, Core Midmarket, and Upper Midmarket firms. In its 15th year of global tracking, Techaisle surveyed over 5000 businesses across various employee segments to provide a comprehensive overview of the IT market. The survey reveals key business goals, technology priorities, and IT challenges for the upcoming year, offering invaluable insights to IT vendors, channel partners, and media.

Business Issues

In 2025, Small and Medium-sized Businesses (SMBs) will encounter several significant challenges. Attracting and retaining top talent will be crucial, necessitating adaptation to technological advancements. This effort extends beyond recruitment, encompassing the attraction of skilled workers in a competitive market that demands remote work options, flexibility, and competitive benefits. It is not merely about reducing IT costs but strategically integrating new technologies such as AI and automation to enhance efficiency, customer service, and potentially product or service offerings.

Financial resilience will require meticulous financial management and risk mitigation strategies. With increasing reliance on digital tools and data, robust security measures and compliance with evolving regulations will be essential to address data security and privacy concerns. Protecting sensitive information from cyber threats will be paramount.

Meeting customer expectations will demand a focus on personalized experiences and omnichannel engagement, where customers anticipate seamless interactions both online and offline. Additionally, there will be an expectation for more sustainable and ethical business practices. Innovation and differentiation will be imperative to remain competitive, necessitating a culture of experimentation and unique offerings.

Reaching target audiences in a fragmented digital landscape will require sophisticated marketing and sales strategies. Digital marketing and sales optimization will be critical for engaging customers effectively. Building resilient supply chains will help mitigate disruptions and ensure business continuity. Compliance with regulatory requirements will be necessary to avoid penalties and maintain a positive reputation. Finally, integrating sustainability and social impact into business practices will be important for attracting and retaining both customers and investors.

Technology Priorities

Technology will be essential in overcoming the challenges facing SMBs. Advanced AI and automation will streamline operations and enhance efficiency. Beyond basic AI assessment, SMBs will explore more sophisticated applications, such as automating complex business processes using AI and machine learning. They will leverage AI to deliver personalized customer experiences and recommendations. Furthermore, predictive analytics will empower SMBs to forecast trends and make data-driven decisions.

Conventional wisdom suggests that large enterprises spearhead technological adoption, with smaller businesses lagging. However, small and medium-sized businesses (SMBs) leverage their agility and propensity for experimentation to overcome challenges that often hinder larger organizations. As generative AI becomes more accessible, SMBs will likely emerge as innovators rather than passive followers in the technological arena.

Despite enduring challenges such as limited capital and technical expertise, the decreasing cost of AI tools and cloud services presents new opportunities. These developments enable smaller firms to compete more effectively in areas traditionally dominated by larger corporations.

As analysts, we are keen to explore these trends and assist businesses in anticipating future developments. This article outlines key predictions for 2025, highlighting the opportunities and challenges that await SMBs and midmarket firms.

Rodney Clark, SVP of Partnerships and Small & Medium Business, Cisco, and Elisabeth De Dobbeleer, SVP of Cisco Partner Program, Cisco are on a mission. At the recently concluded Cisco Partner Summit 2024, Cisco unveiled its new partner program, the Cisco 360 Partner Program, which aims to redefine how partner value is recognized and rewarded. This program fosters shared success, enhances partner profitability, and simplifies the partner experience. Cisco is streamlining its partner structure by transitioning from four roles (Integrator, Provider, Advisor, and Developer) to two main tiers: Cisco Partner and Cisco Preferred Partner. This change is not due to a lack of recognition of partners' diverse roles or a disregard for the ecosystem. On the contrary, Cisco is enhancing its focus on the ecosystem, acknowledging that partners can fulfill multiple roles. This simplified structure allows partners to achieve the Preferred Partner status through a value index that recognizes metrics spanning various business models.

Cisco currently boasts a best-in-industry partner program, recognized for its strong market presence, trust, and reliability. However, the program's complexity and operational challenges are hindering its effectiveness. The multifaceted benefits, while encouraging partner adoption, can take time to manage and track. As Cisco looks to evolve its partner program, it focuses on simplifying the process and shifting towards outcome-based metrics. By focusing on profitability and operational efficiency, Cisco aims to ease the transition for partners and ensure a smooth evolution of the program.

Generative AI is revolutionizing how businesses operate, offering unprecedented opportunities for innovation and efficiency. As per Techaisle’s research of 2400 businesses, 94% are expected to use GenAI within the next 12 months. Amazon Web Services (AWS) is at the forefront of this transformation, guiding business leaders through the adoption and implementation of generative AI technologies. AWS emphasizes the importance of understanding the potential of generative AI and identifying relevant use cases that can drive significant business value. By leveraging tools such as Amazon Bedrock, AWS Trainium, and AWS Inferentia, businesses can build and scale generative AI applications tailored to their specific needs. These tools provide the necessary infrastructure and performance to handle large-scale AI workloads, ensuring businesses can achieve their goals effectively. Moreover, AWS highlights the critical role of high-quality data in the success of generative AI projects. A robust data strategy, encompassing data versioning, lineage, and governance, is essential for maintaining data quality and consistency, enhancing model performance and accuracy. Additionally, AWS advocates responsible AI development, emphasizing the need for ethical considerations and risk management. Businesses can establish clear guidelines and safeguards to ensure their AI initiatives are innovative and responsible. Real-world success stories, such as those of Adidas and Merck, demonstrate the tangible benefits of generative AI, from personalized customer experiences to improved manufacturing processes. As businesses continue to explore and implement generative AI, they must prioritize adaptability, continuous learning, and a commitment to ethical practices to fully harness this technology's transformative power. AWS is taking a pivotal role in guiding businesses through the adoption and implementation of generative AI by encouraging business leaders to consider the possibilities if limitations were removed.

AWS’ Roadmap for Generative AI Success

Despite widespread GenAI adoption plans, Techaisle found that 50% of businesses struggle to define an AI-first strategy. Most businesses, from small to large corporations, struggle to define specific GenAI implementation strategies. This is particularly evident among small businesses (81%), midmarket firms (45%), and enterprises (41%). As Tom Godden, AWS Enterprise Strategist, said, “The question on every CEO’s mind is ‘What is our generative AI strategy?” To facilitate this journey, AWS outlines a clear roadmap encompassing several key stages: Learn, Build, Establish, Lead, and Act.

In the Learn phase, AWS recommends understanding the possibilities of generative AI and identifying relevant use cases. They offer resources like the AI Use Case Explorer, which provides practical guidance and real-world examples of successful implementations. Moving to the Build stage, AWS stresses the importance of effectively choosing the right tools and scaling. They provide a range of infrastructure and tools, including Amazon Bedrock, AWS Trainium and AWS Inferentia, Amazon EC2 UltraClusters, and SageMaker. These tools help businesses balance accuracy, performance, and cost while developing and scaling generative AI applications.

The Establish phase centers around data, a crucial component for successful generative AI implementation. AWS highlights the need for a robust data strategy that includes data versioning, documentation, lineage, cleaning, collection, annotation, and ontology. This ensures data quality and consistency, which is essential for optimal model training. In the Lead stage, AWS emphasizes the importance of humanizing work and using generative AI to empower employees rather than replace them. They recommend redesigning workflows to leverage AI effectively, adopting successful AI governance models, and preparing the workforce for new roles through upskilling and reskilling.

Finally, the Act phase focuses on building and implementing a responsible AI program to ensure generative AI's ethical and safe use. AWS advises proactively addressing potential risks and challenges, establishing clear risk assessment frameworks, and implementing controls and safeguards to prevent misuse. They also emphasize the importance of providing training and resources to ensure security and compliance teams are confident in the organization's AI practices.

AWS provides a comprehensive approach to guiding businesses through the adoption and implementation of generative AI. AWS helps leaders navigate this transformative technology and unlock its immense potential by offering a clear framework, practical tools, and real-world examples.

Amazon Bedrock: A Comprehensive Platform for Generative AI

Building upon this foundation, Amazon Bedrock emerges as a pivotal tool for businesses seeking to harness the transformative power of generative AI. By providing a curated selection of foundation models and simplifying their implementation, Bedrock empowers organizations to experiment, iterate, and scale their AI initiatives rapidly.