A recent discussion with our Digital Transformation Leaders community proved insightful, revealing ideas and real-world experiences in developing a winning AI strategy.
Here are the key takeaways:
Link AI Strategy to Business Strategy: Ensure that AI initiatives align directly with strategic goals, enhancing specific business and customer outcomes rather than serving as a standalone technology initiative.
Create Leadership Accountability: Assign a C-level sponsor to ensure the strategic importance of AI within your organisation. Interestingly, there was a mix of organisational approaches to where AI strategy and capability were placed, ranging from centralised under a specific C-suite leader to decentralised across multiple divisions.
Educate and Create a Compelling Narrative: Educate individuals at all levels on AI fundamentals and digital literacy to set the right expectations and foster ideas for leveraging the technology effectively. Given the uncertainties surrounding AI, a robust change and communications management plan is essential to ensure consistent messaging. It's crucial to convey that the technology is often there to augment rather than replace human roles. The group consensus highlighted a significant need for education in this area.
Build AI Delivery Capability and Consider Strategic Partners: Establish a robust AI development capability, which should include a mix of core roles such as data scientists, full-stack LLM developers, AI researchers, and other product roles. Some organisations have developed a blended model of internal resources supplemented by external experts, while others are still exploring the extent of capability needed internally versus externally.
Enhance Data Readiness and Technology Infrastructure:
Focus on enhancing data management and strengthening technology infrastructure to support AI applications. Effective data management is crucial, especially for generative AI, which requires less data than traditional machine learning models. Often, it is necessary to update and better organise knowledge bases with policies, procedures, and documentation that support digital assistants and enterprise solutions like Co-Pilot. The group's discussions highlighted significant variations in maturity and focus across organisations.
Choose the Right Tools and Platforms: Select AI tools and platforms that align with your business needs and technical capabilities. Consider both proprietary and open-source solutions, and evaluate them for scalability, support, and community strength.
Develop a Pipeline with a Blend of AI and Automation Capabilities: For members of the group whose organisations have started their journey, generative AI has opened up numerous new use cases, bringing renewed focus and enthusiasm to existing AI.
Create a Mechanism to Make Informed Make vs. Buy vs. Use Existing Decisions: Carefully evaluate the strategic value of developing AI solutions in-house compared to purchasing off-the-shelf products. Leaders discussed various approaches, noting that some AI applications are easier and more cost-effective to integrate through enterprise solutions like Microsoft's Co-Pilot, while others necessitate bespoke development. We all agreed robust governance to make these decisions is key.
Establish a Robust Delivery Model: Develop a structured delivery model, integrating with existing change processes. This includes governance for the identification, prioritisation and delivery of AI initiatives. Ideally, AI isn’t treated as a separate pipeline but integrated with other change initiatives to ensure adequate allocation of investment.
Begin with Manageable Projects: Initiate AI deployment with projects that are straightforward yet have the potential to provide high impact and quick wins. Many found that starting with low-hanging fruit helps to build momentum and set the right expectations, aiding broader organisational buy-in for more complex AI projects.
AI as a Source of Competitive Advantage: If possible, consider how AI applications can provide a unique competitive advantage to your organisation. A few participants highlighted that their organisations view AI not just as an operational tool but as a core component of their competitive strategy.
The insights shared during our roundtable showed the variation in where organisations are on their AI journey. Overall, it was clear there is still a long way to go to maximise the benefits. The fundamentals of what is required to ensure success, such as sponsorship, change management, etc., are no different from any other large-scale change.
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