Software Development

Unleashing the potential of Generative AI: a strategic approach

15 September 2023 • 2 min read

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Generative AI presents both opportunities and challenges for organisations. Chief Experience Officers (CXOs) must navigate carefully to maximise the benefits and achieve their organisational goals, delivering a remarkable customer experience in the process. In this blog post, we'll explore a strategic approach to harnessing the power of Generative AI.

 

Laying the strategic foundations for AI success

 

Before diving into Generative AI, it's crucial to gain a deep understanding of your organisation's processes. Many businesses operate without a clear grasp of their workflows, which can hinder effective decision-making. Conducting a service mapping exercise can reveal bottlenecks and inefficiencies within your system, paving the way for optimisation. Once you’ve done this, there are a number of steps you can take to drive success:

 

Dealing with historic constraints

 

Historic constraints, often termed Zero Value Historic Constraints (ZVHCs), can impede progress. These are legacy processes that no longer add value but persist due to historical reasons. Identifying and removing these roadblocks should be a priority, as doing so can significantly enhance efficiency, quality, and risk management.

 

Working incrementally

 

Adopting Generative AI is best done through an incremental and iterative process. This approach allows your team to learn, adapt, and maintain high levels of quality. As the technology is relatively new, working in small increments provides valuable insights into its capabilities and the potential impacts on your existing environment.

 

Adapting your organisation’s skills

 

In a rapidly evolving technological landscape, the ability to adapt is crucial. Prioritise skills that enable your team to identify problems, collaborate effectively, and tackle challenges incrementally. The focus should be on problem-solving abilities rather than specific tools, as technology continues to evolve.

 

Making your data accessible

 

Generative AI relies heavily on high-quality, accessible data. Establish a robust data management strategy that encompasses efficient collection, storage, cleanliness, accuracy, and security. Breaking down data silos and encouraging cross-departmental data sharing and integration is essential for the success of Generative AI applications.

 

Fostering collaboration

 

Generative AI has the potential to benefit various departments within your organisation. Encourage cross-functional collaboration among teams like marketing, sales, research and development, and customer service. This collaboration can lead to enhanced processes and optimised customer experiences.

 

Implementing continuous monitoring and assessment

 

As Generative AI becomes integrated into your operations, establish a feedback loop for continuous monitoring and assessment. Regularly evaluate AI-generated outputs for alignment with business goals and gather feedback from internal stakeholders and customers. This iterative process allows you to fine-tune AI models, adapt to changing business needs, and effectively address unexpected challenges.

 

The importance of strategic leadership in the age of Generative AI

 

Whilst Gen AI advances are setting expectations high, budgets are still tight - meaning CXOs have to be well-informed and strategic in their response. Generative AI offers an evolving range of possibilities to enhance efficiency, innovation, and customer engagement, but it requires thoughtful planning and execution.

By laying the strategic foundations for AI success that we’ve outlined above, you can position your organisation to fully leverage the potential of Generative AI. This journey is not static; it demands ongoing vigilance and adaptation. The true value of Generative AI lies not only in its technology but in the strategic decisions and leadership that guide its integration, shaping a more productive and innovative company that delivers greater value for its customers.

Software Development

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