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  • Writer's pictureArka Roychowdhury

Before developing a GenAI Strategy

The advent of Artificial Intelligence (AI) marks a pivotal moment in history. BCG’s study revealed that consultants using AI completed 12.2% more tasks, 25.1% faster, and produced over 40% higher quality results compared to those not using AI1. This demonstrates AI’s potential to boost workplace productivity and efficiency. McKinsey estimates that AI technologies could potentially deliver up to $1 trillion of additional value each year for global banking2. AI can lead to higher automation and improve upon human decision making in terms of both speed and accuracy2. The potential benefits are immense and to reap them, organizations must act with urgency. This is a crucial time in history. The sooner your organization acts, the faster you will reach the potential benefits coming from generative AI. With limitless possibilities for what AI can do, it’s easy to get lost. Developing a strategy will help you focus on what is feasible and organize how to approach next steps. But some groundwork that needs to happen, before you can come up with this strategy. It is important to learn as you go, experiment and try out low hanging targets rather than lock yourself in a corporate silo, preparing a strategy that doesn’t play on your strength or provide you any long term competitive advantage.


Prepare, Educate and Fail Fast: Advancing organizational knowledge on AI will help you better navigate and understand what is possible for your organization. You need to build the right organic expertise and foster the right partnership in order to prepare the launchpad for success

Identify/prioritize High-Value Use Cases: Identify the highest value use case requiring AI in your organization as your starting point. This could be anything from improving customer service to optimizing operational efficiency. Ensure that you also evaluate the availability and quality of data required for each use case and ensure they align with your data strategy. Quality of data is a differentiator, and can make or break the value proposition of your AI model.

Invest in Innovation and Create a Culture of Experimentation: Don’t exclude your own people. Take a design thinking approach. It’s important that people feel they have the ability to try new things, make mistakes, and learn from them. This fosters a culture of innovation and continuous improvement.Ensure that your staff can effectively support AI initiatives by investing in their education. This may involve reskilling or upskilling employees to work effectively with AI.

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