Technology Adoption Follows a Natural Cycle of Excitement, Disillusionment, and Renewal.
The Hype Cycle: Understanding the Stages of AI Adoption
The Gartner hype cycle is a well-established framework for understanding the stages of technology adoption. It describes the natural progression of technology adoption, from initial excitement and optimism to eventual disillusionment and decline. The cycle consists of five stages: peak, trough, slope of enlightenment, slope of disillusionment, and the post-peak state.
The Five Stages of the Hype Cycle
The council had to pay a significant amount of money to SAP to migrate the customisations, which was a major concern for the council.
The Challenges of Migrating to Cloud Services
Migrating to cloud services can be a complex and costly process, especially when it comes to customising existing systems. Birmingham City Council’s experience highlights the challenges that organisations face when trying to migrate their ERP systems to the cloud. The cost of migrating customisations can be prohibitively expensive, with some estimates suggesting that it can cost up to 50% of the total project cost.
The Benefits of Third-Party Support Providers
Reducing Downtime and Data Loss
Third-party support providers can help IT departments keep older enterprise software platforms running for longer.
This is because many SaaS products are designed to be highly scalable and offer flexible pricing models that can be easily adjusted as a company grows.
The Hidden Dangers of Corporate Credit Cards
Understanding the Risks
When a company uses a corporate credit card to purchase a SaaS product, the risks associated with the purchase are often overlooked. However, these risks can have severe consequences, including data leakage and financial losses.
Key Risks to Consider
The Impact of SaaS Pricing Models
Flexible Pricing Models
SaaS products often offer flexible pricing models that can be easily adjusted as a company grows. While this can be beneficial for companies, it can also lead to runaway costs and data leakage risks.
How Flexible Pricing Models Can Go Wrong
AI Readiness: The Marathon of Upgrades
Upgrading to AI readiness is a long-term process that requires careful planning, strategic execution, and continuous improvement. It’s not a sprint, but a marathon, as SAP User Group chair aptly puts it. The journey to AI readiness involves several key elements, processes, and steps that need to be addressed to ensure a successful implementation of AI systems.
Understanding the AI Landscape
Before embarking on the journey to AI readiness, it’s essential to understand the current AI landscape. This involves identifying the various AI technologies, tools, and platforms available, as well as their potential applications and use cases. Some of the key AI technologies include:
Assessing Current Capabilities
The next step is to assess the current capabilities of the organization in terms of AI adoption. This involves evaluating the existing AI infrastructure, identifying areas of strength and weakness, and determining the potential for AI-driven innovation. Some key questions to ask include:
The Need for AI Assurance
The UK government has launched an AI assurance platform designed to help enterprises navigate the complexities of artificial intelligence. This move comes as the UK’s AI sector continues to grow, with the government recognizing the need for greater assurance and trust in AI systems.
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