Techaisle Blog

IBM and Microsoft have an established and successful strategic partnership, marked by significant collaborations like ARO (Azure Red Hat OpenShift). In 2021, the general availability of Red Hat OpenShift on Azure evolved into Azure Managed OpenShift on Azure. In 2023, IBM achieved Partner of the Year recognition with over 13 accreditations across the Microsoft portfolio and seven in 2024.

ARO has been a cornerstone of this partnership, offering businesses a comprehensive hybrid cloud solution that seamlessly integrates Azure services with Red Hat OpenShift. This partnership has also driven IBM’s expansion on the Azure cloud marketplace, where IBM’s technology offerings have gained substantial traction.

In a significant initiative to enhance their long-standing relationship, IBM and Microsoft are expanding the partnership by bringing additional IBM solutions to businesses through the Azure Marketplace. This strategic move aims to provide businesses with a more streamlined and integrated experience, allowing them to access a broader range of IBM software and services directly within the Azure ecosystem.

Both IBM and Microsoft stand to benefit from this partnership, as Techaisle’s research indicates a growing momentum towards Azure Marketplace. 47% of businesses consider it to be secure, 45% find it well-understood, 44% utilize it due to its extensive footprint, and 41% perceive it as a mature platform. These positive perceptions highlight Azure Marketplace’s increasing appeal to businesses seeking reliable, comprehensive cloud solutions.

Expanding IBM's Offerings on Azure Marketplace: A Strategic Partnership

There are few absolute certainties in technology – but one subject that is beyond debate is that the cloud has permanently changed how technology is deployed and consumed within businesses, and AI is the latest disruptive technology. We know that AI is everywhere, but having arrived in a hurry, the changes made in response to its adoption will not leave abruptly.

Techaisle research shows that 72% of SMBs, 97% of midmarket firms, and 100% of enterprises believe technology is critical to business success. However, IT efficiency can be challenging to achieve. As the business pressures increase, the greater is the need for automation and orchestration. Business unit leaders seek inputs from IT to help achieve business goals. In straightforward terms, in 86% of firms, IT is expected to do more and is even seen as a source of innovation. In 79% of firms, IT is expected to deliver business outcomes faster. However, 80% of IT’s time is spent on support and maintenance; in 65% of organizations, IT is left with little time for innovation.

One of the key highlights of this expanded partnership is the introduction of Apptio Technology Business Management (TBM) software to the Azure Marketplace. Apptio, an IBM company, is recognized as a market leader in TBM and FinOps. It empowers organizations to make data-driven technology investment decisions and optimize costs across cloud and on-premise environments.

The roll-out of Apptio's product suite on Azure Marketplace will occur in phases, beginning with IBM Targetprocess on October 29^th, 2024. Targetprocess is an Enterprise Agile Planning (EAP) software that integrates with Azure DevOps, facilitating better budget planning and management across diverse technology environments. IBM also plans to bring its flagship IT financial management solution, IBM Apptio Costing and Planning, to the Azure Marketplace in the first quarter of 2025. These initiatives highlight a commitment from both IBM and Microsoft to provide businesses with a comprehensive suite of solutions to manage and optimize their technology investments within the Azure cloud platform.

Digital transformation remains a crucial driver of business success, enabling organizations to enhance customer experiences, optimize operations, drive innovation, adapt to disruption, and gain a competitive edge. AI maturity is a critical determinant for fully realizing the benefits of digital transformation. Organizations with higher AI maturity can leverage data insights, automate tasks, personalize experiences, innovate products and services, and mitigate risks, ultimately propelling their digital transformation efforts and securing long-term success.

Techaisle’s research of SMBs, midmarket, and upper midmarket firms shows that AI maturity, a crucial determinant of an industry's digital transformation success, is closely intertwined with IT maturity, cloud maturity, and innovation mindset. While many industries have embarked on their AI journeys, the level of maturity varies significantly.

IT Maturity as a Foundation: A strong foundation in IT maturity is essential for successful AI adoption. Industries with higher IT maturity levels, such as Financial Services, are better positioned to leverage AI effectively. However, sectors like Healthcare and Hospitality, which are lagging in IT maturity, may face challenges in implementing AI solutions. Bridging this digital divide requires significant investments and targeted development efforts to enhance IT capabilities. For partners and IT suppliers, identifying specific IT areas for improvement within each industry could drive targeted development efforts.

Cloud Maturity as an Accelerator: Cloud adoption plays a pivotal role in accelerating AI initiatives. Industries with higher cloud maturity levels are more advanced in digital transformation and AI adoption journeys. Organizations in sectors with lower cloud maturity can gain a competitive edge by prioritizing cloud adoption and implementing robust cloud governance and security measures.

Innovation Mindset as a Catalyst: A culture of innovation is crucial for driving AI adoption. Industries with a higher propensity for innovation, such as Technology-driven sectors, are leading in AI advancements. While recognizing the potential of AI, sectors like healthcare may need to foster a more innovative mindset to fully capitalize on its benefits. On the other hand, Financial Services presents a mixed picture, with a significant number of very innovative companies alongside a substantial portion of somewhat innovative organizations.

As AI continues to evolve, industries must strive to improve their AI maturity by addressing the underlying factors of IT maturity, cloud maturity, and an innovation mindset. By doing so, they can unlock AI's full potential and drive sustainable growth and competitive advantage.

Techaisle research shows that the Financial Services, Manufacturing, Healthcare, and Retail verticals are prime AI and cloud services targets due to their shared characteristics. These industries aim to modernize operations, leverage vast amounts of data, and comply with stringent regulations. Additionally, they prioritize customer experience, operational efficiency, and scalability. By integrating AI and cloud solutions with existing systems, these industries can unlock the full potential of their technological investments, drive innovation, and maintain a competitive edge.

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.

On 24^th September 2024, Google Cloud unveiled several significant updates to its AI offerings. These updates include enhancements to the Gemini model, including the general availability of a two million token context window for Gemini 1.5 Pro, improvements in provisioned throughput, advancements in grounding capabilities, and the general availability of the Imagen 3 text-to-image generation model. These new product announcements from Google Cloud highlight its commitment to advancing AI technologies and providing businesses with the tools they need to drive innovation and growth. With these new features, Google Cloud further solidifies its position as a leader in AI development.

Google also discussed the evolution of its agents, highlighting how they have become increasingly sophisticated and capable over time. As AI technology has advanced, Google's agents have evolved from simple chatbots to intelligent assistants that can perform complex tasks and provide valuable insights. Cloud agents are intelligent software applications that can perform tasks autonomously or in collaboration with humans. They leverage artificial intelligence and machine learning to automate processes, analyze data, and provide insights. Google Cloud has released a variety of agents, including customer agents, employee agents, data agents, security agents, and creative agents. These agents offer numerous benefits, such as increased efficiency, improved decision-making, enhanced customer satisfaction, and reduced operational costs. Google Cloud agents differentiate themselves by integrating with Google's AI platform, Vertex AI, which simplifies development and deployment. Additionally, Google Cloud's agents are designed to be scalable, reliable, and secure, ensuring that businesses can leverage AI to meet their evolving needs.

Gemini Updates and Expanded Capabilities

Updates to the Gemini Model: One of the event's key highlights was the announcement of updates to the Gemini model. The Gemini model, known for its powerful generative AI capabilities, has been further enhanced to provide even more robust performance. The updates to the Gemini Model, specifically the introduction of the Gemini 002 version, bring several advantages for customers. The new version is available in both Flash and Pro versions. The Flash version is designed for speed and versatility, making it suitable for a wide range of applications. On the other hand, the Pro version offers incremental reasoning capabilities, which can be particularly beneficial for more complex tasks that require deeper analysis and understanding. The context window for Gemini 1.5 Pro has also been expanded to 2 million tokens. This significant increase allows for analyzing larger amounts of data in a single prompt, such as two hours of video or 1500 pages of text. This capability enables customers to process and analyze extensive datasets more efficiently, leading to more comprehensive insights and better decision-making.