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How to Bring Your Generative AI Strategy to Life

In our discussion earlier this week, we delved into How to Build A Generative AI Strategy that aligns perfectly with your unique business objectives. Now, it's time to roll up our sleeves and bring that strategy to life!




Bridging the Gap Between Strategy and Execution


Did you know that a staggering 92% of strategies never see the light of day, according to McKinsey? It's crucial to remember that strategy and implementation are two sides of the same coin. Your AI initiatives should be the stepping stones that lead you towards your strategic goals around:


  • Boosting Revenue

  • Cutting Costs

  • Enhancing Customer satisfaction


To ensure this, appoint dedicated project leads who can keep the implementation aligned with your overarching strategy.


Zeroing in on Actions That Matter


Start by identifying the one to three AI applications that will have the most significant impact on your strategic goals. Which ones will create a lasting difference in your revenue and cost over time?

For example:


  • Could using Gen AI slash your customer response time by 50%?

  • Will employing Gen AI to optimize supply chain efficiency be your game changer?


Focus on use cases with biggest payoff.


Answer the Three Fundamental Questions

For each AI initiative, you need to have crystal clear answers to three fundamental questions:

  • Who is the target audience?

  • What product/service will we provide them?

  • How will we profitably deliver this?

Bottlenecks Are Your Friend


Identify the bottlenecks in your implementation - the hurdles standing in your way to Gen AI success. Choose bottlenecks that:

  • Directly impact value creation

  • Require recurrent decisions

  • Arise from resource constraints

For example, you might be facing data accessibility issues that prevent model training. Make it your mission to overcome these bottlenecks and drive results.


User-Generated "Rules of the Road"


Top-down rule creation is a no-go. Instead, gather the users of each AI application to collaboratively establish guidelines for successful integration into their workflows.

Their hands-on insights will provide practical "rules of the road" that optimize adoption. For example, customer service agents using a new AI chatbot could jointly create usage guardrails.


Iterate, Learn, Repeat


View implementation as an iterative process. Continuously:

  • Test

  • Gather user feedback

  • Update approaches

Remember, AI projects require ongoing adaptation as models evolve.


Strategy Lives in Simple Rules


Your strategy isn't a hefty document gathering dust on a shelf - it lives in the simple rules that guide everyday decisions around AI usage and integration. Create just enough structure to empower your employees without stifling their creativity.


Invest Time Upfront


Spend time early on to deeply analyze where AI can drive maximum strategic value. Resist the urge to rush into execution across too many fragmented use cases.

With these guiding principles, you're well on your way to transforming your AI strategy into actions that deliver real, tangible results. Ready to capture the value of AI across your organization? Let's connect and discuss how to drive execution and make your AI vision a reality.





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