Techaisle Analyst Insights

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.

Pandemic has changed how businesses operate, employees work, customers purchase and goods/services get delivered. This has also changed how small and midmarket firms are evaluating their core, cloud and edge technology needs to address their accelerated digital transformation objectives of cost efficiencies, operational excellence, innovation, business growth, organizational empowerment and customer intimacy. Clearly, core infrastructure has evolved to meet future digital transformation demands, but the question is how are small businesses and midmarket firms planning to adopt forward-facing solutions, like Artificial Intelligence, 5G, AR/VR, IoT, analytics and several others. There is a general sense within the SMBs that these advanced solutions will increase insight into and control over key aspects of their business operations and deliver benefits in different ways and to different ends.

Remaining true to the core belief of tracking the future of SMBs and channel partners, Techaisle studied global SMBs to determine future, planned and likely adoption patterns of several technology areas. The study of SMB and Midmarket digital transformation trends identified top 15 technology categories where the adoption growth rates will likely be highest in the next six months to a year. There are some surprises, for example, chatbots (for customer responsiveness), 5G (for enhanced mobility), open source (for cloud management, modernization and lower TCO), AI (for customer experience, security, operations) and several expected, for example, SD-WAN, HCI, WVD/VDI/DaaS and UCaaS.

They are here - Techaisle's annual SMB and Midmarket Top 10 IT Priorities, IT Challenges and Business Issues infographics. This is the 7th year of Techaisle tracking at a WW level and is much sought after by IT vendors, channels and media. There is an ongoing trend – in both the buy-side and supplier communities – towards positioning IT initiatives and expenditures in a business context.

To help readers connect positioning with core market drivers, Techaisle research provides insight into the most pressing business issues, IT priorities and IT challenges faced by small (1-99 employees) and midmarket (100-999 employees) businesses in 2018.

For 2018, Techaisle investigated 21 different technology areas, each with several sub-technology categories, 24 different IT challenges and 24 different business issues. At the request of our clients, this year, not only are we releasing data & infographics (shown below) as usual for SMBs (1-999 employee segment), Midmarket (100-999 employee segment) but also for Small businesses (1-99 employee segment).

In 2018, the new and upcoming IT Priorities within SMBs are Virtual Reality (VR)/Augmented Reality (AR) and Hyperconverged infrastructure (HCI). Within midmarket firms, Artificial Intelligence (AI) appears for the first time for 2018. Workplace transformation is one of the new top IT challenges for SMBs – number 1 on the list for midmarket firms and overall at number six across all SMBs. This obviously points to a need for unified workspace experience. In addition, Cloud orchestration and integration are among the top five key IT challenges for both SMBs and midmarket firms.