Should Amazon Compete in the War for AI Talent?

I don't see #Amazon as needing to compete with #OpenAI, #Meta, #Anthropic, etc. by developing their own #AI #LLM. The Amazon retail experience already has great usability, use of data, and recommendation / search algorithms.

I think they might be better off working agnostically with all model makers:

1. To offer the models in AWS for customers to use.

2. Getting all the model makers to embed APIs so that #chatbots can allow users to purchase products instantly that come up in query answers.

© 2025 Praveen Puri

I'm Increasingly Skeptical About AI Causing Mass Unemployment

I'm increasingly skeptical that #AI will put people out of work. History has shown that life becomes continually complex and new jobs are always created. I always write that the Information Age is gone, and we are now in the Attention Scarcity Age. Change is happening faster than ever, people are drowning in information, and attention / focus are the new scarce resources.

My prediction is that #LLMs and AI might take over basic, repetitive stuff, but human experts will be busy doing things, like evaluating #AIAgents. With all the change happening, to stay competitive, it will take full time people just to keep testing an evaluating which models and agents to use, how to deploy them, and help them cope with change.

We've been here before:

1. Historical - hundreds of thousands of jobs like blacksmiths, elevator operators, stenographers, and typesetters were eliminated, but new jobs were created.

2. McDonalds - They added ordering kiosks in stores and people thought it would eliminate jobs. Instead, the pandemic happened, and people switched to drive-through, and they added mobile ordering / curbside. That created jobs.

© 2025 Praveen Puri

How AI Companies Avoid Commodification

On LinkedIn, someone mentioned how they thought 99% of AI companies are building wrappers (UIs) for LLMs, and that they were just commodities.

I think the opportunity (to avoid being a commodity) for companies like this is that, while the price of tokens (unit pricing for LLMs) are dropping, costs for inquiries are going up because LLMs are doing more "deep thinking" (which burns tokens). 

Not every query needs deep thinking. So the unique value-add for AI wrappers/UI companies is to design for minimizing tokens without sacrificing accuracy.

© 2025 Praveen Puri

Future of AI?

© 2025 Praveen Puri

AI and the Strategic Simplicity® Framework

Businesses that struggle to come out with usage cases for #AI would do well to use my Strategic Simplicity® Framework for guidance.  I had created it in pre-AI times to guide executives and teams in areas like business #strategy, #projectmanagement, and #productmanagement.  But it's also good for AI strategy.

The components are CLOUD: Change simplicity, Language simplicity, Operational simplicity, User simplicity, and Decision simplicity.

Let's just take a look today at an example of Operational simplicity.  Part of Operational simplicity is treating your employees as "internal customers" and giving them the user simplicity to do their jobs well.  This could mean AI agents that converse with them and create things like requests, time sheets, etc. without requiring the employee to actually have to hunt around for links and actually filling out the forms.  A lot of info, such as the employee's manager, job code, dept #, etc. can be looked up and filled in by the agent.

© 2025 Praveen Puri

A Hidden Downside to AI

A hidden downside to #AI is that, with its apparent ease, companies will be tempted to do too much. Strategic Simplicity® will be needed by #leaders even more than ever. A good #consultant can help you focus, prioritize, and know which tempting projects to NOT do.

© 2025 Praveen Puri

About That MIT AI Report...

The recent report from MIT that 95% of AI pilot projects fail has caused some concern.

Contrary to what some may think, it's not because of the capabilities of the models themselves, but about the implementation.  

Here are some of the reasons for the poor performance:

1. Companies are trying to adapt AI to their current processes and procedures.  The problem with this bureaucratic approach is that AI does not care about office politics, and it is more important to adapt your processes to its strengths.

2. Build vs. buy.  Many companies are trying to build their own AI tools, rather than partner with an experienced vendor.  Most companies don't have AI expertise on staff, and the budget to do AI from scratch.  Also, any DIY attempts will probably involve open models, and these are not yet as powerful as proprietary LLMs.

3. Most of the current processes involve sales and marketing.  But AI can make some of its most productive gains if applied to back-end processes.

The ultimate key, just like any digital transformation, is to practice Strategic Simplicity®, and focus on a few, critical functions and bottlenecks.  Pick one at a time, as you first build your AI skills.  As the expert in Strategic Simplicity®, this is how I advise my clients.

© 2025 Praveen Puri