Solving the AI Productivity Paradox

Gemini 2.5 Pro gets coding update, Anthropic's AI models for U.S. Gov., Alphabet CEO pushes back on AI’s workforce threat and more!

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Everyday AI
June 05, 2025

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Sup y’all 👋

You ever feel like there’s certain projects that are too important for AI? Like…. Your financials? 

I just wrapped up a CRAZY insightful convo with the CTO of a global leader in financial AI. 

It’s dropping tomorrow – you don’t wanna miss it. 

✌️

Today in Everyday AI
7 minute read

🎙 Daily Podcast Episode: Why isn't generative AI boosting productivity as expected? We explore the challenges, solutions, and the future of AI in the workplace. Give it a listen.

🕵️‍♂️ Fresh Finds: Hugging Face boasts about robotics model, Runway CEO wants Hollywood to embrace AI video and the FDA’s AI tool isn’t working as expected. Read on for Fresh Finds.

🗞 Byte Sized Daily AI News: Google Gemini 2.5 Pro gets coding update, Anthropic unveils AI models for U.S. Gov. and Alphabet CEO pushes back on AI’s threat to the workforce. For that and more, read on for Byte Sized News.

🧠 Learn & Leveraging AI: How can we escape the AI paradox? We break down how you can boost your productivity with proper AI implementation. Keep reading for that!

↩️ Don’t miss out: Did you miss our last newsletter? We talked about ChatGPT for Business getting major updates, Meta's new AI glasses, Mistral AI unveiling a coding assistant and more. Check it here!

 Solving the AI Productivity Paradox đź’ˇ

AI makes us all more productive.... so why isn't revenue soaring?

That's the AI Productivity Paradox.

↳ Does that mean GenAI doesn't work?
↳ Or do we all collectively stink at measuring GenAI ROI?
↳ Or are employees just pocketing that time savings?

Faisal Masud is a tech veteran with answers. He's the President of HP Digital Services, and he's going to help us solve the AI Productivity Paradox.

Also on the pod today:

• Hybrid Work's AI Integration Challenges 🧑‍💻
• Generative AI Impact on Large Enterprises 🏢
• AI Tools vs. Traditional Employment Roles 🤔️

It’ll be worth your 30 minutes:

Listen on our site:

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Listen on:

Upcoming Everyday AI Livestreams

Friday, June 6th at 7:30 am CST ⬇️

Here’s our favorite AI finds from across the web:

New AI Tool Spotlight – TipTap brings AI to any editor, Solver is AI-powered, self-driving software, Effie is an AI writing productivity tool

Microsoft – Microsoft’s Chief Product Officer spoke on the AI shift.

AI Models – Hugging Face says its new robotics model is so efficient it can run on a MacBook.

Amazon – Amazon has launched a new R&D group focused on agentic AI and robotics.

AI Video – Runway’s CEO wants Hollywood to embrace AI video.

Big Tech - Tech giants’ indirect emissions rose 150% in the past 3 years as AI expands, according to a UN agency.

AI in Government – The FDA’s new AI tool for medical devices is currently struggling with simple tasks.

Future of Work – Vista’s CEO says AI will force 60% of finance professionals to seek work.

AI Startups – Thread AI has raised $20 million for a composable AI platform.

1. Google’s Gemini 2.5 Pro Gets Smarter at Coding 🧠

Google just rolled out an updated preview of its Gemini 2.5 Pro AI model, claiming it’s now sharper at tackling tough coding challenges and excelling in math, science, and reasoning tests. This upgrade, available today on AI Studio, Vertex AI, and the Gemini app, fine-tunes the model’s style and response formatting based on user feedback from last month’s release.

Google plans a wider launch within weeks, signaling growing competition in AI developer tools that could boost productivity for coders and tech professionals alike.

2. Anthropic Unveils Claude Gov AI Models for U.S. National Security 🇺🇸️

Anthropic has introduced a new set of AI models, Claude Gov, designed specifically for U.S. national security agencies, aiming to enhance strategic planning, operational support, and intelligence analysis. These models are already in use at the highest classified levels, offering improved handling of sensitive information, better language proficiency relevant to defense, and stronger cybersecurity data interpretation.

This move highlights the growing competition among top AI labs like OpenAI, Meta, and Google to secure defense contracts and integrate AI into government operations.

3. Alphabet CEO Pushes Back on AI Job-Cut Fears đź‘€

In a recent Bloomberg interview, Alphabet CEO Sundar Pichai dismissed worries that AI will slash half of the company’s workforce, emphasizing instead that AI boosts engineer productivity and fuels growth through new product innovation. While Alphabet has made targeted layoffs in 2025, these are far less severe than the massive cuts seen in 2023 and 2024.

Pichai highlighted ongoing advances in areas like Waymo, quantum computing, and YouTube’s booming presence in India as signs of continued expansion. He also acknowledged the legitimacy of job displacement concerns but remained cautiously optimistic about AI’s future, stopping short of guaranteeing a clear path to artificial general intelligence.

4. X Tightens AI Training Rules Amid Industry Scramble đźš«

X, formerly Twitter, has updated its developer agreement to block the use of its posts and API for training AI models, signaling a shift towards controlling its data’s role in AI development. This move aligns X with platforms like Reddit, which recently sued an AI company for unauthorized data scraping, highlighting growing tensions over AI training access.

Despite the stricter terms, X’s privacy policy still allows selected third parties to use data for AI training unless users opt out, and X itself uses user data to train its Grok AI.

5. Amazon Drops $10 Billion on North Carolina AI Hub đź’°

Amazon is making a huge bet on North Carolina with a $10 billion investment to build a sprawling AI and cloud computing campus in Richmond County, promising at least 500 new tech jobs and extensive upgrades to local infrastructure. This move not only signals Amazon’s commitment to expanding its AI capabilities but also aims to revive a region hit hard by the decline of textile jobs, offering fresh career paths in engineering, network security, and more.

The project includes partnerships with educational institutions to train the next generation of tech talent, potentially reshaping the local workforce for decades.

🦾How You Can Leverage:

Reddit is full of stories about people juggling seven gigs simultaneously.

All excelling.

All getting "exceeds expectations" on their reviews.

And their secret weapon? AI that's automating 70% of their workload while bosses measure productivity using decade-old metrics.

Faisal Masud joined Everyday AI today to get us the ACTUAL tea on this paradox. As in, if AI is making us all more proactive, why aren’t revenues soaring? 

Faisal is the President of HP Digital Services and he just revealed why your company isn't printing money despite having access to AI that can compress 60-second tasks into 2-second wins. 

It's everything else you're doing wrong.

1 – Your Performance Metrics are Measuring The Wrong Century 📊

Customer service used to take 60 seconds per ticket. Now AI handles it in 2 seconds.

But you're still celebrating teams that hit the old 60-second benchmark.

Faisal watched this exact scenario play out across multiple enterprise companies. While startups are seeing 40% productivity gains, massive corporations are barely moving the needle. Why? They're measuring industrial-age outputs in an AI-powered world.

The goalposts moved. You didn't notice.

When Amazon started with 7-8 day shipping, that was revolutionary. Now it's next-day everything. The bar keeps rising, but most companies are still using last decade's standards to evaluate this decade's AI-enhanced work.

Try this:

Open your team's current KPIs spreadsheet right now. Find any metric based on time-to-completion for tasks your team uses AI for. Replace those time-based measurements with quality and outcome metrics instead. If your customer service team resolves tickets faster with AI, measure customer satisfaction scores and first-contact resolution rates rather than response time.

2 – The Great AI Policy Illusion 🪄

Trillion-dollar companies building AI technology don't have proper AI policies.

Let that sink in.

Faisal worked at these places. He saw the chaos firsthand. Companies scrambling to control what employees use while those same employees have ChatGPT bookmarked on their personal laptops at home.

You can't police remote workers using external AI tools.

You shouldn't want to.

The smarter play? Make your internal AI offerings so incredible that employees stop looking elsewhere. Most companies do the opposite. They provide mediocre internal tools then wonder why their team goes rogue with external platforms.

Faisal's insight cuts deep. Employees will use whatever works best for them. Your job isn't to restrict their toolkit. It's to compete with the external options by offering something better internally.

Try this:

Send an anonymous survey to your team asking what AI tools they're actually using for work tasks. Not what they're supposed to use. What they really use. Then audit your internal AI capabilities against their preferred external tools. Either upgrade your internal offerings to match or officially adopt the tools they're already finding valuable.

3 – The Death of Traditional Job Descriptions 💼

Stop hiring humans for human roles.

Start hiring humans for AI-augmented roles.

Faisal shared something wild from his Staples days. Back in 2016, his team launched an AI-powered easy button handling a thousand different customer commands. It was powered by IBM Watson and ahead of its time. Today, that level of automation is table stakes.

Yet most job descriptions read like they were written in 2014.

When someone leaves your team, you can't just copy-paste their old responsibilities. The role fundamentally changed the moment AI entered the picture. Companies like Shopify are evaluating every potential hire against one question: could AI do this instead?

The future belongs to smaller teams with AI superpowers. Not larger teams doing industrial-age work.

Faisal's experience running teams at Amazon and Alphabet taught him that hiring more people usually creates more problems. More handshakes. More bureaucracy. More complexity. The magic happens when you enable small teams with incredible tools.

Try this:

Before posting your next job opening, spend 20 minutes listing every task the previous person did. Mark each task as either "uniquely human" or "AI-augmentable." Rewrite the job description focusing entirely on the uniquely human responsibilities. Add "AI proficiency" as a hard requirement, not a nice-to-have. Include specific examples of how they'll work alongside AI tools to amplify their impact.

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