Episode 2  |  39 Min  |  February 05

Develop AI strategy for your organization with Dr. Kavita Ganesan

Share on

Engaging topics at a glance

  • 00:12:19
    Key messages in the book: The business case for AI
  • 00:12:58
    What should enterprise leaders look into when implementing AI
  • 00:15: 25
    What problems can be solved with AI?
  • 00:16:13
    Importance of data in AI
  • 00:19:30
    Things to consider when going with AI in production
  • 00:20:48
    What makes a problem AI suitable?
  • 00:24:35
    Success rate of AI projects
  • 00:25:37
    What causes failure of AI projects?
  • 00:28:14
    What is preventing AI success?
  • 00:30:20
    Data integration problem

“Develop AI strategy for your organization” with Dr. Kavita Ganesan, where she discusses things to consider when implementing AI.

Many programmes, specifically AI-based programmes, start with the right intentions but often fail when they go into production. And, to explore this topic, we had an insightful discussion with our guest in this episode to understand why this happens and how it can be solved.

One key problem is that they’re not solving the right problems with AI. People think of a cool idea, and then they come up with an AI solution, and once they’ve developed it, there isn’t a consumer for it.

– Kavita Ganesan

Most of the AI initiatives today fail to make it into production because people are not solving the right problems with AI, and there is a lack of understanding of what AI is at the leadership level.

The perception that Gen AI can solve every problem is inaccurate, and understanding this is crucial for enterprise leaders. There are many other AI techniques that can solve business problems and it’s important to have a general understanding of what AI is and what types of problems it can solve. As implementing AI is not only cost intensive, but it also comes with many risks.

Nowadays, many people think that because of Gen AI, we don’t need to collect data; we don’t need a data strategy; data is just gone. But that’s far from the truth.

– Kavita Ganesan

After the emergence of Gen AI, contrary to what many people think today, data collection is still a very integral part of AI initiatives in order to fine-tune the models for company-specific problems.

When deciding on the application of AI, it is advisable to use it for intricate issues that require numerous narrow prediction tasks. In such cases, a large amount of data points needs to be evaluated for making decisions, which could be challenging for human minds to process.

It’s important for companies to have a strategic approach while implementing AI. Instead of just focusing on the latest trends (like implementing Gen AI for all the problems), companies should identify the problems that need to be solved in their business in order to have a huge business impact.

Production Team
Arvind Ravishunkar, Ankit Pandey, Chandan Jha

Latest podcasts

Episode 13  |  57 Min  |  February 05

Responsible Al practices for business leaders with Dr. Rachel Adams, CEO, GCG

Responsible Al practices for business leaders with Dr. Rachel Adams, CEO, GCG

Share on

Engaging topics at a glance

  • 00:01:50
    About the topic i.e. Responsible AI
  • 00:12:20
    About the guest speaker – Dr. Rachel Adams
  • 00:14:20
    What is responsible AI
  • 00:16:00
    Why responsible AI
  • 00:19:55
    AI autonomy and policy
  • 00:22:10
    Beyond theoretical understanding of AI
  • 00:24:15
    How should business leaders approach responsible AI
  • 00:29:20
    Thoughts on AI regulation
  • 00:31:00
    Responsible AI framework for business leaders
  • 00:33:10
    Index for responsible AI
  • 00:36:20
    Staying educated on responsible AI and AI policy
  • 00:39:40
    EU AI regulations
  • 00:41:45
    Other emerging AI regulations
  • 00:45:10
    AI policy development on a specific area
  • 00:48:30
    Concluding thoughts on responsible AI

Gain valuable perspectives on integrating responsible AI into business strategies from Dr. Rachel Adams, CEO and founder of the Global Center on AI Governance.

In this insightful podcast, we embark on a journey to understand the intricate landscape of responsible AI practices, especially tailored for business leaders. Dr. Rachel Adams, one of the top global voices on responsible AI and the founder and CEO of the Global Center on AI Governance, serves as our guide through this complex terrain.

The conversation begins by framing the discussion around the concept of "thinking with care" when it comes to AI development and deployment. Dr. Adams emphasizes the importance of inclusivity and diversity in AI development, particularly in addressing the unique needs of different regions and communities worldwide. She stresses the significance of aligning technological advancements with the real needs of people, advocating for a user-centric approach driven by community engagement and feedback.

As the dialogue progresses, the focus shifts towards the role of business leaders in navigating the multifaceted dimensions of responsible AI. Dr. Adams elucidates the critical considerations that business leaders must keep in mind during both the development and deployment phases of AI initiatives. From addressing inherent biases in AI models to safeguarding user privacy and data protection, she outlines a comprehensive framework for ethical AI governance within organizations.

Moreover, Dr. Adams sheds light on emerging policy developments in the field of AI regulation, highlighting the European AI Act as a pioneering effort in this space. She underscores the need for nuanced, sector-specific regulations tailored to the diverse contexts and challenges faced by different industries and regions.

Throughout the conversation, Dr. Adams emphasizes the importance of collaboration and cross-disciplinary dialogue in advancing responsible AI practices. She underscores the need for closer collaboration between technologists, policymakers, and communities to navigate the evolving landscape of AI governance effectively.

As the podcast draws to a close, we reflect on the fundamental principles of responsible AI adoption, emphasizing the imperative of "thinking with care" in every aspect of AI development and deployment. Dr. Adams reiterates the need for a collective effort to ensure that AI technologies are developed and deployed in a manner that prioritizes human values, equity, and societal well-being.

In summary, this podcast provides invaluable insights into the complex challenges and opportunities presented by AI technology for business leaders. Through engaging dialogue and expert analysis, Dr. Rachel Adams offers a roadmap for ethical AI adoption, empowering business leaders to navigate the ethical complexities of AI with confidence and integrity.

Production Team
Arvind Ravishunkar, Ankit Pandey, Chandan Jha

Top trending insights

Episode 11  |  55 Min  |  February 05

How to deploy AI sustainably with Dr. Eng Lim Goh, SVP at HPE

How to deploy AI sustainably with Dr. Eng Lim Goh, SVP at HPE

Share on

Engaging topics at a glance

  • 00:16:45
    Why is sustainable AI important?
  • 00:20:48
    Apart from power, what else matters for sustainable AI?
  • 00:26:12
    What about e-waste and recycling?
  • 00:29:15
    Why is AI so power hungry?
  • 00:32:19
    What model should business leaders adopt for AI deployment?
  • 00:36:47
    More on energy use by AI
  • 00:39:56
    Choosing the right hardware for AI
  • 00:45:08
    Organizational effort for sustainable AI
  • 00:48:56
    Considerations when deploying AI

Explore the vital link between AI and sustainability as we discuss strategies for eco-conscious AI deployment with Dr. Eng Lim Goh, Senior vice president of Data & AI at Hewlett Packard Enterprise

In this episode of Unpacked, Arvind introduces Dr. Eng Lim Goh, SVP of Data and AI at Hewlett Packard Enterprises, to discuss the topic of sustainable AI. They agree on the importance of being conscious of the planet's well-being while charting business growth and profitability. 

Dr. Goh explains the need for corporations to consider sustainability due to their net-zero goals, the conscious younger generation of employees, and the economic implications of power consumption in supercomputing. He shares his experience of working on the International Space Station and how he realized the importance of a sustainable approach to technology. 

Similarly, he suggests that businesses should consider long-term goals while investing in AI and related technologies, adding that it is important to measure the impact of such efforts quantitatively. He also talks about the importance of collaboration between businesses, governments, and academia to achieve sustainable progress. The conversation then moves on to the topic of energy consumption in AI, and Dr. Goh explains how the power consumption of large models has been a challenge in the supercomputing industry. He suggests that businesses should consider using more efficient hardware and software to reduce energy consumption and how they can approach this. He also mentions the importance of using renewable energy sources to power data centers. 

The conversation concludes with Dr. Goh’s vision for the future of AI and sustainability. Dr. Goh emphasizes the need for businesses to consider the long-term impact of their actions and to invest in sustainable technologies. He believes that AI can play a crucial role in achieving sustainability goals and that it is important for businesses to collaborate and share knowledge to achieve sustainable progress. 

Overall, the conversation highlights the need for businesses to consider sustainability while investing in AI and related technologies. It emphasizes the importance of transparency, collaboration, and measurement in achieving sustainable progress.

Production Team
Arvind Ravishunkar, Ankit Pandey, Chandan Jha

Co-create for collective wisdom

This is your invitation to become an integral part of our Think Tank community. Co-create with us to bring diverse perspectives and enrich our pool of collective wisdom. Your insights could be the spark that ignites transformative conversations.

Learn More