Steven Forth is a Partner in Ibbaka, a strategic pricing advisory firm. He was CEO of LeveragePoint Innovations Inc., a SaaS business designed to help companies create and capture value. Steven is what I consider one of the great pricing thinkers in our industry.

In this episode, Steven talks about AI and how it is impacting the world of pricing. He also shares some of the improvements we could expect from AI infrastructures in the near future.

 

Why you have to check out today’s podcast:

• Find out how the emergence of AI improves and disrupts the pricing profession and the trade as a whole
• Learn how to extract the best and most comprehensive solutions from AI tools
• Get an idea on how the “big 3” of cloud services might price for their AI services in considering their current pricing models

 

“Many billions of dollars being invested in AI last year, next year, this year. The overall investment is going to be probably in the neighborhood of $300 billion in 2023. So, if we were investing that much money, we better get some value back. And the companies investing that money need to be able to price that value they're creating.”

– Steven Forth

 

Topics Covered:

02:10 – The questions that need to be answered about the impacts of AI in pricing

04:06 – Examples of existing value proposition that AI is improving

07:10 – Examples of existing value proposition that AI is disrupting

10:44 – Is the emergence of AI a challenge to the pricing profession?

12:08 – Can open AI soon generate value models that are better than experts create?

15:58 – Why and how large language models such as Chat GPT are taking over

18:06 – How to guide an AI in giving you comprehensive answers

19:34 – What the pricing of major AI infrastructures looks like

21:02 – How Amazon, Google and Microsoft would possibly price for AI considering their present pricing models

23:28 – Will there be different strengths in the AI of infrastructures Amazon, Google and Microsoft?

24:55 – Differences in AIs: Would different Ais give out different answers to the same questions?

26:19 – Could AI effectively learn pricing from human pricing experts?

28:02 – How Ais could start making outcome-based pricing more practical

32:03 – Connect with Steven Forth

 

Key Takeaways:

“People who are skilled in the art [of trade] understand how to come up with pricing for disruptive innovation.” – Steven Forth

“Understanding the limitations of these large language models, which GPT is an example of, is also important. And we can come to that. But let's not forget that the limitations today are not the limitations in six months.” – Steven Forth

“That, I think, is actually one of the emerging skills: To be able to structure a sequence of questions that will guide an AI in giving you meaningful answers.” – Steven Forth

 

People / Resources Mentioned:

• Ibbaka – https://www.ibbaka.com/
• DALL·E 2 – https://openai.com/dall-e-2/
• Chat GPT – https://openai.com/blog/chatgpt/
• Amazon Web Services – https://aws.amazon.com/
• Google Cloud Services – https://cloud.google.com/
• Microsoft Azure – https://azure.microsoft.com/en-us
• NVIDIA – https://www.nvidia.com/en-us/deep-learning-ai/products/solutions/

 

Connect with Steven Forth:

• LinkedIn: https://www.linkedin.com/in/stevenforth/
• Email: [email protected]

 

Connect with Mark Stiving:

• LinkedIn: https://www.linkedin.com/in/stiving/
• Email: mailto:[email protected]