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Get your Company AI Ready: Why Cloud Comes Before AI in your Strategy

By BreakFree Solutions


Generative AI is making waves in the tech world. The excitement around it is undeniable – the internet won’t stop buzzing. However, it’s vital for business leaders to ignore the noise and lay a solid foundation with cloud infrastructure and agile processes before starting to embrace AI.


It is crucial to separate the noise from practical considerations. Implementing AI solutions is a complex engineering feat that demands careful planning, significant resources, and a holistic transformation of the underlying platform. Instead of getting distracted by the hype, organizations should focus on having a solid cloud foundation before implementing AI into their platforms to create a lasting impact. True transformation comes from building a robust foundation and investing in the necessary skills and capabilities.



Focus on Cloud First Before Diving Into AI

It’s essential to have your cloud infrastructure in order before implementing generative AI. This means being able to access and manage cloud services efficiently and securely. For instance, ensuring that the right people have the appropriate access to cloud resources can be likened to giving out keys to your company’s storage rooms – you don’t want just anyone to have access. Tools that manage this “key allocation” can be automated, saving time and increasing security.


Embrace Cloud-Native Platforms


With your cloud infrastructure set, the next step is adopting cloud-native platforms. This will provide the agility and scalability your systems need. Think of it like building with LEGO; using cloud-native platforms means you have a vast array of building blocks and the flexibility to rebuild as needed. Ensuring these platforms can accommodate automated testing and deployment is like having a quality check and a delivery service for every new product you build with LEGO, without lifting a finger.


Align Your People and Processes


Successful AI implementation relies on cross-functional collaboration, agility, and DevOps. Adopting agile methodologies and fostering a DevOps culture allows organizations to align their people and processes, enabling seamless collaboration between data scientists, developers, and operations teams. By breaking down silos and embracing iterative development, businesses can accelerate AI initiatives, streamline workflows, and adapt quickly to evolving business requirements.



Optimize Operational Processes


Operational efficiency is key to keeping pace with AI. Imagine your company as a well-oiled machine – every part should move smoothly and in sync. This means implementing modern workflows that promote quick decision-making, and ensuring teams from different departments can easily collaborate. It’s like having a skilled pit crew in a race; not only are the cars (the technology) important, but also having a team that can efficiently change tires and makes repairs on the fly.


Build AI on a Solid Foundation


Now with a stable cloud infrastructure and streamlined processes, you're ready to delve into AI. But remember, AI systems are complex and should address specific business needs. For example, building AI agents can be thought of as training specialized employees – they can handle customer queries or help users find the perfect product. These “employees” can work around the clock, learn and improve over time.


Investing in AI Enablement and Engineering Resources


To fully capitalize on generative AI business cases, organizations need to invest in AI enablement and engineering resources. Developing AI models, implementing machine learning algorithms, and extracting actionable insights require specialized skills and expertise. By allocating resources to AI enablement, companies can empower their teams with the necessary knowledge and tools to leverage AI effectively, paving the way for innovation and competitive advantages.


While AI is exciting, it's important not to get ahead of yourself. To successfully utilize AI’s potential, companies must establish a solid cloud foundation and leverage cloud-native capabilities, invest in engineering resources, and adopt agile methodologies. Your organization can meet the demands of generative AI by embracing these principles and can unlock the full potential of AI, driving innovation, growth, and competitive advantage in the digital age.


If you want to learn more or are ready to tackle your AI initiatives, we can help:



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