Embarking on the journey to build an AI strategy can be both exciting and challenging. Here we’ll walk you through the essential steps and considerations for crafting a robust AI strategy that aligns with your unique goals and aspirations. The goal of this post is to empower you to harness the potential of AI, and we’re excited to share our expertise to make this journey as supportive and successful as possible.
AI strategy simplified
Kavita Ganesan defined an AI strategy as a vision or high-level plan for integrating AI into the organisation in a way that aligns with your broader business and automation goals. The plan can either be a Product-level AI strategy, Business-unit-level AI strategy, Organisational-level AI strategy, or an AI startup strategy. The caveat within all these plans is that the bigger the vision, the broader the objectives until each objective is broken down into a roadmap for implementation.
Creating An AI Strategy
Regardless of what we say the reality of things cannot be ignored and that reality is that there are no shortcuts. Amazon, Google, Apple, and Facebook all used very different business strategies to gain their current market dominance and global influence, but their common success is arguably due to their foresight in understanding the value of data and positioning themselves early. This doesn’t mean there is no hope as Sebastian Heinz stated that there are 6 key elements of an AI strategy: Data, Use Cases, Team and Skills, Infrastructure, Organisation and Governance. Focusing and carrying along these elements will make it much easier for any organisation to implement their AI Strategy.
Steps in making an AI strategy
Creating a successful AI strategy is a journey, one that requires careful planning and consideration of several key steps:
- Establish a Clear Vision and Objectives: Begin with a well-defined corporate vision and set of objectives that align with your organisation’s AI goals. This vision will guide your AI strategy.
- Define Specific Use Cases: Identify the particular areas where AI can bring value to your business. Work closely with stakeholders to understand the opportunities AI presents.
- Data and Infrastructure: Determine the data sources and technical infrastructure required to support your use cases. You can choose to build in-house, opt for cloud solutions, or combine both for flexibility.
- Build the Right Team: Assemble a skilled team, including data engineers, systems engineers, modelling experts, and data scientists. Consider partnerships with academic institutions to access specialised expertise.
- Governance and Risk Management: Implement governance structures, such as an Executive Steering Committee, to ensure alignment with AI vision, principles, and guidelines. Assess your risk appetite, including legal, model, reputational, and operational risks.
- Create an Incremental Roadmap: Develop a practical roadmap that spans immediate, medium-term, and long-term goals. Prioritise your initiatives, building upon past successes.
In conclusion, building an AI strategy is not just about technology; it’s about your vision, your goals, and your future. We hope this post has illuminated the path to success in your AI journey. At Eden AI we’re here to be your trusted partner every step of the way. Our caring team is always ready to listen, advise, and guide you, ensuring that your AI strategy not only meets your needs but exceeds your expectations. Reach out to us at email@example.com and we will help you in your AI journey.
This post was enhanced using information from:
Kavita Ganesan What Is An AI Strategy And Why Every Business Needs One Opinosis Analysis
Sebastian Heinz (2021) The 6 Key Elements of an AI Strategy
Munich Re Creating an AI Strategy from the Ground Up