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AI/ML

L'IA au service des valeurs agiles

January 22, 2025 | 4 Lecture minute

Dans le paysage technologique en évolution rapide, l'intelligence artificielle (IA) s'impose comme une force significative, remodelant divers domaines, y compris les pratiques agiles.

L'IA, souvent entourée du mythe des robots qui envahissent le monde, est un ensemble de technologies qui permettent aux machines d'effectuer des tâches traditionnellement associées à l'intelligence humaine, telles que le traitement des données, le raisonnement, la synthèse et la résolution de problèmes.

L'IA étant encore en cours de développement, sa meilleure application à l'heure actuelle est d'enrichir les tâches qui vous sont déjà familières. Des tâches simples pour résumer, catégoriser ou analyser des quantités importantes de données. L'IA peut contribuer à générer des idées novatrices ou à combler des lacunes. L'IA s'appuie sur des points de données et des règles connus et peut produire des résultats lorsqu'on lui donne des instructions claires. Toutefois, il est important de vérifier les résultats pour s'assurer qu'ils sont éthiques, impartiaux et exacts.

Leveraging AI in Agile Practices 

AI can significantly enhance Agile values by developing clear and compelling product visions, creating detailed and accurate personas, and generating comprehensive Product Backlog Items (PBIs). This is achieved through well-crafted prompts that guide AI to produce valuable outputs.  

What is in a prompt? 

  • The goal of what you are trying to accomplish leveraging AI. 

  • The role the AI model should assume.  For example, a Business Analyst, Product Owner, Market Researcher, Customer, etc. For even better results, include details about the role. 

  • The aspects or context around the ask.  For example, information about your topic, website(s), company goals, product information, current and target customers, customer needs and problems, how success is measured, etc. 

  • The task you are asking AI to complete. This primary action should be clear and concise, and action words should be used. 

  • Lastly, the format of the response you are expecting. Are you looking for a paragraph, a bulleted list, how many items? 

  • The quality of your output hinges on the quality of the aspects, context, and prompt made to AI. 

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Some examples in Agile where AI can help a Product Owner and Scrum Team: 

Product Vision 

The AI-generated vision reflects the company's goals, customer needs, and strategic direction, demonstrating how AI can help align business objectives with customer expectations. 

Customer Personas  

AI can also create detailed personas for target customers. A persona highlights the customer's goals, challenges, and needs, which in turn informs the development of relevant features and services. 

Product Backlog Items 

Based on the product vision and persona, AI can generate a list of features to be included in the product backlog. These features ensure that the product meets the customer's needs and aligns with their lifestyle, thereby enhancing the overall user experience. 

Sprint Goal  

Once the team has identified the items for the Sprint during Sprint Planning, your team can enter these into the AI tool to aid in coming up with a singular focused Sprint Goal. 

Inform Priorities 

Using product reviews, usage logs, survey results, purchase history, social media interactions, and support tickets after release, we can validate we are achieving the desired outcomes.  Based on the frequency and severity of pain points, this information can help inform priorities to directly address customer problems. 

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How Does AI Enable the Agile Values? 

By using AI to summarize, define, and create first drafts of things like the product vision and personas once we bring this draft to the stakeholders and Scrum Team we are having better conversations around the product and our customers.  We can collaborate together to refine and improve the Product Vision and Personas which gives us a shared understanding of the current and future product and customers.   

Using AI for Product Backlog Items, first and foremost can result in huge time savings to identify the work and priorities.  Our refinement sessions are improved with a better starting point for the Scrum Team to discuss product backlog items.  AI can also identify items that were not previously thought of which can result in additional innovative ideas coming from the team. One spark can start a ripple effect of ideas! 

Ensuring Continuous Improvement through AI 

When leveraging AI, it is important to iterate through validation and feedback loops. By continuously refining AI outputs and incorporating feedback, teams can improve the accuracy and relevance of their products. Reviewing and adjusting AI-generated outputs ensures that the final product resonates with customers and meets their evolving needs.

Conclusion 

The integration of AI into Agile practices offers a promising avenue for enhancing efficiency, collaboration, and customer satisfaction. By leveraging AI to develop product visions, create customer personas, generate product backlog items, and ensure continuous improvement, organizations can stay ahead in a competitive landscape.

As AI continues to evolve, its role in Agile practices will likely grow, providing even more opportunities for innovation and growth. The key lies in understanding AI's capabilities, addressing its misconceptions, and maintaining a human-centric approach to ensure ethical and effective use. Contact us at Improving to learn more about how we can help you leverage AI.

AI/ML
Agile

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AI/ML

L'IA au service des valeurs agiles

L'IA améliore les pratiques Agile en créant des visions claires, des personas détaillés et des backlogs complets.