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Top Dollar AI: What is value and how much is it worth paying? $1000 per user per month ? A user centric ‘AI Allyship ‘ Approach

Being Human for a Better Tomorrow in the Age of AI

  • September 13, 2024
  • 36th edition
top dollar ai 11zon scaled

“What would you make you pay $100/mo and $1000/mo for an AI subscription product? What should it do for you? “Aravind Srinivas CEO Perplexity AI, Sept 4th 2024, on X

This ‘X’ post triggered a new method of thinking about use cases and value.

There is a lot of literature from industry analysts and consulting firms on building ground-up use analysis of value vs. cost for prioritization. The previous edition of Mindvista newsletter, covered:

  • Employee-First Use Case Approach for Gen AI Implementation and Customer-First for More Established Machine Learning, Data Sciences
  • Bi-Modal Exploration (AI Enhanced and AI Driven)

A lot of the use case research can be abstracted into a generalized framework comprising the following:

  • Who is the user—internal employee or external customer?
  • What are the candidate tasks for automation and task chaining for process automation?
  • What is the outcome- enhancement or transformation?
  • What are the costs and short, medium, and long-term horizons?

This methodical bottom-up approach has worked well in technology adoption in the past and will continue to do help in AI adoption as well.

However, this post from Aravind Srinivas, got me thinking differently, to put a user (not a process or a task) at the center for a deeper understanding of what is real value and how much to pay or charge for this.

As an experiment, I tried to explore for myself as an AI user and enthusiast,

Here is the result of that thought experiment:

AI Allyship Thought Experiment

User: Creator – Content Research, Reason and Publishing

Job Analysis:

  1. Read and Research
  2. Reason and Articulate
  3. Write and Publish

1. Content Research and Consumption

Challenge: Multiple disaggregated content sources—AI news, expert research articles, LinkedIn, YouTube, X feeds, Podcasts, Reddit forums, Online learning materials, science fiction—books, movies, web series, history, philosophy and more.

AI-driven Value: Aggregate, index, cross-reference, suggest new content based on research interest and writing across platforms.

2. Reason and Articulation

Challenge: Solo iterative development—hunch, hypotheses, validation check, and synthesize framework.

AI-driven Value: Thought partner to reason, critique, and debate on hypotheses and build-outs; General conversation on demand.

3. Write and Publish

Challenge: Single format article publish.

AI-driven Value: Repurpose source with AI-generated multiple formats (Tweets, website, short podcasts, and Video Shorts), validate and auto-publish.

Value Hypotheses:

  1. Efficiency: >50% reduction in collating, validating content.
  2. Effectiveness: 4x increase in being able to process and critique hypotheses and make time for new.
  3. Outcomes: 2x reach—web, podcasts, and shorts.
  4. Overall throughput: 10x conservatively
  5. Worth: From $500 per month limited restricted usage to unlimited scaling for $1000 unlimited end to end AI Allyship- research, reason and publish.

AI Allyship is a new idea for a top-down user-centric value approach for an AI-driven enterprise..The users can be employees or customer users—CXOs, Power users (business functions, production support in IT) with high enterprise $$ value per hour.

It can complement the bottom-up process and task oriented approach to leapfrog what is today to what can be tomorrow and to change the game in what matters most every day with AI as an ally.

AI Allyship is also a deep subject and can grow in a virtuous cycle of LLM technology and business value. It is journey that could begin today to explore, share and collaborate in this forum. With Ariavista as a principle guide, we will also go down the rabbit hole of AI Allyship in future editions.

Hot off press: As I wrote this yesterday, ChatGPTo1 released a few hours ago is said to offer superior reasoning (more on that later). So tech is happening

Thank you for the read and explore.

If you found this of value, please like, follow, comment, feedback and share.

Cheers to Human AI Allyship for super-powered future,

Best wishes

Select Quotes

"You've got to start with the customer experience and work backwards to the technology."
– Steve Jobs
"People don't use a product because of the great design; great design helps them use the product."
– Viran Anuradha Dayaratne
"The future is already here—it's just not evenly distributed."
– William Gibson
"We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next ten."
– Bill Gates
"The factory of the future will have only two employees, a man and a dog. The man will be there to feed the dog. The dog will be there to keep the man from touching the equipment."
– Warren Bennis
"AI is whatever hasn't been done yet." - Adapted from Doug Hofstadter's quip about AI

II. Questioning / Asking

Good conversations flow from well‑sequenced questions—topical, simple, coherent, cohesive.
LLM Conversation Example 1
Q: What are empirical judgments?

A: Empirical judgments are based on observation, experience, or experimentation.
Q: What are moral judgments?

A: Moral judgments are based on ethical principles and values.

Thank you for the read and explore.

If you found this of value, please like, follow, comment, feedback and share.

Cheers to Human AI Allyship for super-powered future,

Mindvista Newsletter (for the next gen, professionals, aspiring leaders, and executives)

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