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PodChats for FutureCIO: AI agents What you need to know (separate hype from reality)

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Manage episode 463509716 series 2912947
Content provided by CXOCIETY | FutureCIO FutureCFO FutureIoT. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by CXOCIETY | FutureCIO FutureCFO FutureIoT 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://ppacc.player.fm/legal.

A chatbot is an Artificial Intelligence program that chats with you. The 1960s saw the first chatbot. It was called ELIZA and was developed by MIT professor Joseph Weizenbaum. Six decades later, we have ChatGPT, Google Gemini and Microsoft Copilot joining the likes of Alexa and Siri.

While chatbots use pattern matching and natural language processing to interpret user inputs and choose the right responses from a set of pre-programmed options, AI agents engage in more complex, multi-step interactions that may span different platforms or services. AI agents take the next step from chatbots moving the needle of engagement between human and machines.

In this PodChats for FutureCIO, we are joined by David Irecki, chief technology officer for Asia Pacific and Japan at Boomi to walk us through the realities of AI agents – what you and I need to know, separating hype from reality.

1. Define AI agent as understood by most users in Asia (both tech and non-tech)?

2. What key factors differentiate AI agent hype from reality for organizations?

3. Since you brought it up, how can businesses ensure high data quality for effective AI deployment?

4. Scale out issues have been a recuring topic when RPAs came out and it may be part of the challenge with AI. From your experience, what common pitfalls should organizations avoid when adopting AI agents?

5. One of the promises of AI is improving productivity – at least this is the hope. In what ways can AI agents drive productivity and cost savings in specific industries? Any pitfalls to avoid?

6. How can AI agents enhance customer experiences across different sectors?

7. How can businesses maintain accountability and governance while leveraging AI agents effectively?

8. This 2025, what is your advice for lines of business, finance, IT and security work together to design or architect or transform processes so they can avail of the promise of AI agents without introducing unnecessary risks in the process?

  continue reading

429 episodes

Artwork
iconShare
 
Manage episode 463509716 series 2912947
Content provided by CXOCIETY | FutureCIO FutureCFO FutureIoT. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by CXOCIETY | FutureCIO FutureCFO FutureIoT 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://ppacc.player.fm/legal.

A chatbot is an Artificial Intelligence program that chats with you. The 1960s saw the first chatbot. It was called ELIZA and was developed by MIT professor Joseph Weizenbaum. Six decades later, we have ChatGPT, Google Gemini and Microsoft Copilot joining the likes of Alexa and Siri.

While chatbots use pattern matching and natural language processing to interpret user inputs and choose the right responses from a set of pre-programmed options, AI agents engage in more complex, multi-step interactions that may span different platforms or services. AI agents take the next step from chatbots moving the needle of engagement between human and machines.

In this PodChats for FutureCIO, we are joined by David Irecki, chief technology officer for Asia Pacific and Japan at Boomi to walk us through the realities of AI agents – what you and I need to know, separating hype from reality.

1. Define AI agent as understood by most users in Asia (both tech and non-tech)?

2. What key factors differentiate AI agent hype from reality for organizations?

3. Since you brought it up, how can businesses ensure high data quality for effective AI deployment?

4. Scale out issues have been a recuring topic when RPAs came out and it may be part of the challenge with AI. From your experience, what common pitfalls should organizations avoid when adopting AI agents?

5. One of the promises of AI is improving productivity – at least this is the hope. In what ways can AI agents drive productivity and cost savings in specific industries? Any pitfalls to avoid?

6. How can AI agents enhance customer experiences across different sectors?

7. How can businesses maintain accountability and governance while leveraging AI agents effectively?

8. This 2025, what is your advice for lines of business, finance, IT and security work together to design or architect or transform processes so they can avail of the promise of AI agents without introducing unnecessary risks in the process?

  continue reading

429 episodes

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