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Maximising the Impact of Your Data & AI Consulting Projects

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Manage episode 451901771 series 2954151
Content provided by Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In our latest episode of the Data Science Conversations Podcast, we spoke with Christoph Sporleder, Managing Partner at Rewire, about the evolving role of consulting in the data and AI space.

This conversation is a must listen for anyone dealing with the challenges of integrating AI into business processes or considering an AI project with an external consulting firm. Christoph draws from decades of experience, offering practical advice and actionable insights for organizations and practitioners alike.

Key Topics Discussed

1. Evolution of Data and Cloud Computing

The shift from local computing to cloud technologies, enabling broader data integration and advanced analytics, with the rise of IoT and machine data.

2. Data Management Challenges

Discussion on the evolution from data warehouses to data lakes and the emerging concept of data mesh for better governance and scalability.

3. Importance of Strategy in AI

Why a clear strategy is crucial for AI adoption, including aligning organizational leadership and identifying impactful use cases.

4. Sectoral Adoption of Data and AI

Differences in adoption across sectors, with early adopters in finance and insurance versus later adoption in manufacturing and infrastructure.

5. Consulting Models and Engagement

Insights into consulting engagement types, including strategy consulting, system integration, and body leasing, and their respective challenges and benefits.

6. Challenges in AI Implementation

Common pitfalls in AI projects, such as misalignment with business goals, inadequate infrastructure planning, and siloed lighthouse initiatives.

7. Leadership’s Role in AI Success

The critical need for senior leadership commitment to drive AI adoption, ensure process integration, and manage organizational change.

8. Effective Collaboration with Consultants

Best practices for successful partnerships with consultants, including aligning on objectives, managing personnel transitions, and setting clear engagement expectations.

9. Future Trends in Data and AI

Emerging trends like componentized AI architectures, Gen AI integration, and the growing focus on embedding AI within business processes.

10. Tips for Managing Long-Term Projects

Strategies for handling staff rotations and maintaining project continuity in consulting engagements, emphasizing planning and communication.

  continue reading

28 episodes

Artwork
iconShare
 
Manage episode 451901771 series 2954151
Content provided by Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In our latest episode of the Data Science Conversations Podcast, we spoke with Christoph Sporleder, Managing Partner at Rewire, about the evolving role of consulting in the data and AI space.

This conversation is a must listen for anyone dealing with the challenges of integrating AI into business processes or considering an AI project with an external consulting firm. Christoph draws from decades of experience, offering practical advice and actionable insights for organizations and practitioners alike.

Key Topics Discussed

1. Evolution of Data and Cloud Computing

The shift from local computing to cloud technologies, enabling broader data integration and advanced analytics, with the rise of IoT and machine data.

2. Data Management Challenges

Discussion on the evolution from data warehouses to data lakes and the emerging concept of data mesh for better governance and scalability.

3. Importance of Strategy in AI

Why a clear strategy is crucial for AI adoption, including aligning organizational leadership and identifying impactful use cases.

4. Sectoral Adoption of Data and AI

Differences in adoption across sectors, with early adopters in finance and insurance versus later adoption in manufacturing and infrastructure.

5. Consulting Models and Engagement

Insights into consulting engagement types, including strategy consulting, system integration, and body leasing, and their respective challenges and benefits.

6. Challenges in AI Implementation

Common pitfalls in AI projects, such as misalignment with business goals, inadequate infrastructure planning, and siloed lighthouse initiatives.

7. Leadership’s Role in AI Success

The critical need for senior leadership commitment to drive AI adoption, ensure process integration, and manage organizational change.

8. Effective Collaboration with Consultants

Best practices for successful partnerships with consultants, including aligning on objectives, managing personnel transitions, and setting clear engagement expectations.

9. Future Trends in Data and AI

Emerging trends like componentized AI architectures, Gen AI integration, and the growing focus on embedding AI within business processes.

10. Tips for Managing Long-Term Projects

Strategies for handling staff rotations and maintaining project continuity in consulting engagements, emphasizing planning and communication.

  continue reading

28 episodes

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