AI projects and Project Sponsorship

According to Randall L. Englund and Alfonso Bucero (co-authors of the book Project Sponsorship), project sponsorship plays a key role in the success of AI projects, ensuring that they receive the necessary resources, executive support, and alignment with organizational goals. We are in the AI era and we believe that sponsoring AI projects presents unique challenges and opportunities due to the complexity, ethical considerations, and evolving regulatory landscape of artificial intelligence.

We would like to share with you some key aspects of Sponsoring AI Projects:

1. Strategic Alignment

Project sponsors must ensure that AI projects align with the organization’s long-term vision and strategic objectives. AI initiatives need to be integrated with business goals to drive innovation and competitive advantage. Every project needs to have a project sponsor assigned who will work with the project sponsor. We believe they are an iseparable team.

2. Executive Support and Stakeholder Engagement

AI projects often require cross-functional collaboration between data scientists, IT teams, legal departments, and business leaders.  That means that project sponsors need to speak to different audiences, unsing the language every audience understand. Effective sponsors advocate for AI initiatives at the executive level and help navigate internal resistance to change.

3. Risk Management and Ethical Considerations

AI projects involve significant risks, including bias in algorithms, data privacy concerns, and regulatory compliance issues. Project sponsors must ensure ethical AI principles are understood, shared, followed, supporting transparency, fairness, and accountability in AI decision-making by all project stakeholders.

4. Resource Allocation and Funding

AI projects demand substantial investment in infrastructure (e.g., cloud computing, GPUs), talent (e.g., data scientists, machine learning engineers), and research. Project sponsors need to secure adequate funding and justify AI investments with clear ROI projections.

5. Managing Uncertainty and Innovation Risks

Unlike traditional IT projects, AI projects have inherent uncertainty due to data availability, model performance, and technological advancements. Project sponsors should adopt an agile approach, supporting iterative development and continuous learning.

6. Regulatory and Compliance Oversight

AI is subject to evolving regulations, such as the EU AI Act and industry-specific guidelines. Project sponsors must work with legal teams to ensure compliance with data protection laws and ethical AI standards. The interaction between the project sponsor and the Compliance responsible person is also a must.

7. Performance Metrics and Success Criteria

Defining clear KPIs (e.g., model accuracy, business impact, cost savings) is essential for measuring AI project success. Project sponsors need to set realistic expectations and track progress through pilot projects and phased deployments.

Some Challenges in AI Project Sponsorship

Based on some real case studies we have found some challenges in AI prpject sponsorship:

– Lack of AI Literacy: Many executives and project sponsors lack technical knowledge, they do not know how AI technology works, making it difficult to assess feasibility and risks.

– High Costs and Uncertain ROI: AI projects often require significant upfront investment without immediate returns.

– Cultural Resistance: Employees may fear AI replacing jobs, leading to resistance in adoption.

– Data Quality Issues: AI models rely on high-quality data, and sponsors must address data governance challenges.

Good practices for AI Project Sponsors

 Educate Leadership: Provide AI literacy training for executives to make informed decisions. Some good practices are as follows:

1. Start small, scale gradually: Fund pilot projects to validate AI solutions before full-scale implementation.
2. Ensure Ethical AI Practices: Support fairness, transparency, and explainability in AI applications.
3. Engage Cross-Functional Teams: Foster collaboration between business, technical, and regulatory teams.
4. Monitor AI Trends: Stay updated on AI advancements, regulations, and industry best practices.

Conclusion

Sponsoring AI projects requires a mix of strategic vision, technical awareness, and strong leadership. Successful AI sponsors champion innovation while managing risks, ensuring ethical AI adoption, and delivering tangible business value. By aligning AI initiatives with organizational priorities and fostering a culture of responsible AI, project sponsors can drive impactful AI transformation. Project sponsors need to be trained on sponsorship, and Englund and Bucero can facilitate that.