AI in Delivery Excellence : Transforming Governance, Customer Experience, Product Management and Collaboration

With the rapid advancement in digital technology, organizations across the globe are leveraging Artificial Intelligence (AI) to enhance delivery excellence.

AI is without doubt playing a key role in streamlining governance, elevating customer experience, optimising product management, and fostering collaboration. The image below depicts how AI and Delivery function together for better results.

Delivery Excellence and AI – Key Areas

Role of AI in Governance

• AI algorithms in strategic decision-making
  – Informed Decisions: GenAI provides comprehensive data analysis and predictive insights, thereby enabling more informed and strategic decisions.
  – Scenario Planning: AI models can simulate various project scenarios, helping anticipate potential challenges and plan accordingly. As an example – For an IT infrastructure migration project, AI models could simulate risks like downtime, security lapses, data transfer delays, etc.
• Efficiency Boost for PM’s
  – GenAI automates routine tasks such as resource allocation, scheduling, and progress monitoring, freeing up time to focus on high-priority issues.
• Automated Task Creation
  – Automated processes reduce human error and ensure consistency in project execution and documentation.
• Predictive analytics for risk management
  – Proactive Risk Identification: AI algorithms identify potential risks early by analyzing historical data and current project parameters.
  – Mitigation Strategies: AI provides recommendations & actionable insights for risk mitigation, helping managers/leads to act swiftly and effectively

Examples of how AI has brought in aspects of Governance like transparency –

A global supply chain company used AI to enhance governance by monitoring supplier compliance with ethical sourcing standards. The AI system analyzed procurement data, supplier reviews, and shipment records to identify deviations from sustainability guidelines, ensuring transparency and accountability across the supply chain.

Enhancing Customer Experience with AI

• Using AI for personalized customer interactions
  – AI based delivery systems can help analyze customer data and identify specific user preferences, allowing personalised services customised to each customer.
• AI-powered chatbots and virtual assistants
• Customer Feedback Analysis / Sentiment Analysis
  – Using AI-powered delivery management solutions to analyze customer feedback and identify areas of improvement.
• Consistency and Accuracy
  – By analysing the customer data like purchase history, browsing behavior, and demographics, and applying advanced machine learning techniques to provide hyper-personalized recommendations
• Leveraging machine learning for market research and trend analysis

Examples of how AI has shaped the Customer Experience

I was reading an article about an e-commerce company that deployed an AI chatbot for customer support. The chatbot used natural language processing (NLP) to resolve 80% of customer queries without human intervention, significantly reducing response time and enhancing customer satisfaction.

• AI in Personalised Content: Netflix uses AI to optimize the streaming experience. For instance, it uses machine learning algorithms to predict what content will be delivered to which servers to reduce latency, ensuring high-quality, seamless streaming for users across the globe.
• Predictive Analytics for Infrastructure: Netflix’s AI-driven predictive models help determine server capacity and network load, predicting traffic surges during peak times (e.g., weekends or after new releases), allowing for smoother delivery even during high demand.

Impact of AI on Product Management

• Market Analysis
  – Predictive analytics, anticipating user needs, market trends, and competitor analysis.
• Building Strategic Product Roadmaps
  – AI could support Product Owners / Managers in creating data-driven, dynamic roadmaps, and based on real-time feedback, AI tools could update roadmaps.
• Automated Product Backlog
  – With AI, it is now very much possible to have intelligent prioritization where the ranking of backlog items is done based on user feedback and business goals.
• Automating Product Surveys and Predictive Analysis
  – Key insights can be derived from user responses/surveys, summarizing user sentiments and pain areas.
• Effective Story Writing and Task Management

Let us take an example of how the use of AI in Jira can help in automated task creation. In the video shown below, we have used the AI Assistant plugin in Jira.
https://drive.google.com/file/d/12-UAL6KqK0QpGVseJ6Esl6BF1aJkAxGJ/view?usp=sharing

Netflix Case Study – Leveraging AI in Enhancing Customer Experience and Product Improvement

Let us take one more example on how Netflix has used AI to enhance Product Management and Customer Experience.

AI in Product Management and Customer Experience – Netflix Case Study

AI in Product Management and Customer Experience – Netflix Case Study. Netflix continues to grow strong after so many years, even in the face of fierce competition from the likes of HBO Max, Disney Plus, Hulu, and Amazon Prime.

Much of the reason for its success is the constant striving for product improvement. To put it differently, Netflix is focused on improving its user experience and upgrading its service. The Netflix AI recommendation engine is the platform’s most important product feature.

Facilitating Collaboration through AI

• Real-Time Communication
  – AI-driven tools support instant communication and collaboration across dispersed teams, ensuring everyone stays aligned and informed.
• Enhanced Coordination
  – GenAI helps in coordinating tasks, assigning responsibilities, and tracking team performance, fostering a more cohesive work environment.
• Increasing engagement and inspiring innovation
  – Promotes unconventional approaches by offering fresh perspectives and questioning the status quo
• Helping generate new ideas
  – Promotes unconventional approaches by offering fresh perspectives and questioning the status quo
• Powering Automation
  – Usage of smart collaboration tools can help with collaboration. Examples – Automated reminders, Smart suggestions.

Tools for AI in Collaboration

• Microsoft Teams with Copilot AI – AI-powered meeting transcriptions and task automation.
• Zoom, Google Meet, and all communicators now provide built-in AI tools for capturing transcripts.

Conclusion

AI is no longer just a concept of the future —it is growing as a game changer in how organizations deliver projects. By enhancing governance, improving customer experience, optimizing product management, and enabling seamless collaboration, AI is helping organizations become more efficient and customer-centric. Be it automating compliance checks, providing personalized customer interactions, predicting market trends, or making teamwork more effective, AI is making a tangible impact.

Organizations that embrace AI-driven tools today will be better positioned to innovate, reduce risks, and create more meaningful experiences for their customers.