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Ep 770: What’s Coming Next: 5 AI Trends, Problems and Opportunities around the Corner
Big Tech is giving the U.S. early access to AI models, ChatGPT just upgraded to GPT-5.5 Instant, and Gemini Flash 3.2 is on the way, and more.
Everyday AI
May 05, 2026
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Today in Everyday AI
8 minute read
🎙 Daily Podcast Episode: AI is moving faster than companies can keep up—here are 5 trends, problems, and opportunities coming next. Give today’s show a watch/read/listen.
🕵️♂️ Fresh Finds: Anthropic is teasing a proactive AI assistant, Google AI Studio just added live editing tools, and OpenAI made voice AI feel nearly instant, and more. Read on for Fresh Finds.
🗞 Byte Sized Daily AI News: Big Tech is giving the U.S. early access to AI models, ChatGPT just upgraded to GPT-5.5 Instant, and Gemini Flash 3.2 is on the way, and more. Read on for Byte Sized News.
💪 Leverage AI: Employees are already running agents, testing tools, and learning AI after hours while most companies are still stuck on training plans and approvals. Keep reading for that!
↩️ Don’t miss out: Miss our last newsletter? We covered: Trump considers AI model oversight, OpenAI starts The Deployment Company, Treasury warns of AI-fueled cyber risk. Check it here!
Ep 770: What’s Coming Next: 5 AI Trends, Problems and Opportunities around the Corner
What's coming next in AI? 🤔
While no one knows, spending time in Silicon Valley and San Francisco recently helped give me a better idea of what's around the corner.
So what should you be paying attention to?
Tune in LIVE as we discuss.
What’s Coming Next: 5 AI Trends, Problems and Opportunities around the Corner -- An Everyday AI Chat with Jordan Wilson
Also on the pod today:
• AI generalists disappearing fast 🧠
• FOMAT: fear of missing agent time ⏰
• Enterprise AI training failing employees 🏢
Listen on our site:
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Here’s our favorite AI finds from across the web:
New AI Tool Spotlight – Flowstep Helps you Generate real UI in seconds, Intuned Agent builds production-ready Playwright code, deploys it, and fixes it when sites change, Airbyte connects to your tools and turns your business data into living context.
Anthropic Orbit — Anthropic is Teasing "Orbit," a proactive assistant that pulls insights from your favorite tools and lets you deploy custom apps.
AI Studio Edit Mode — AI Studio just dropped edit mode, letting you tweak UI components directly and swap images with Nano Banana.
TinyFish Free — TinyFish just made its Search and Fetch APIs free for all developers, no credit card needed
Gemma 4 Upgrades — Gemma 4 just got way faster thanks to Multi-Token Prediction drafters, letting you generate high-quality outputs up to 3x quicker with no quality loss.
Luma Arena — Luma’s UNI-1.1 models just stormed the Image Arena, outscoring rivals in both text-to-image and editing without agentic search.
OpenAI — OpenAI rebuilt its WebRTC stack to make voice AI feel instant, slashing lag and awkward pauses
Nano Banana AI Studio — Google AI Studio now uses NanoBanana to create custom images as you build, and the new edit tool lets you tweak everything visually.
Unity AI Beta — Unity AI is now in open beta, letting devs speed up game creation with smart tools built right into the editor.
Anthropic Finance — Claude just rolled out plug-and-play AI agents for finance, handling everything from pitchbooks to KYC in Excel, PowerPoint, Word, and more.
India Cybersecurity — India's PNB is boosting its cybersecurity budget as new AI models like Anthropic’s Mythos create new risks for banks.
Fortune 500 AI Monitoring — Nearly all Fortune 500 companies are monitoring AI use, which could impact how employees work and adapt. Curious about what this shift means for your job?
Pennsylvania taking Character.ai to court — Pennsylvania is taking Character.AI to court after one of its chatbots pretended to be a licensed doctor and offered medical advice.
1. Microsoft, Google, and xAI Grant U.S. Early Access to AI Models for Security Testing 🧠
In a timely move reflecting growing national security concerns, Microsoft, Google, and Elon Musk’s xAI have agreed to give the U.S. government a sneak peek at their cutting-edge artificial intelligence systems before public release, as reported by Reuters.
The Department of Commerce’s Center for AI Standards and Innovation will use this early access to test for security risks, a step prompted by rising alarm over the hacking capabilities of Anthropic’s new Mythos model. This collaboration aims to spot cyber and military threats before these AI tools hit the market, signifying a major shift in how Washington is handling AI oversight.
2. ChatGPT Gets Smarter with GPT-5.5 Instant 🤓
OpenAI just rolled out a major upgrade to ChatGPT, swapping its default model for the new GPT-5.5 Instant.
The update promises sharper, more accurate answers and a smoother conversational style, all while cutting down on mistakes in high-stakes topics like medicine, law, and finance. It’s now better at using your past chats, files, and even Gmail to personalize responses without making things cluttered or confusing.
3. Gemini Flash 3.2 Teases Big Leap Ahead of Google I/O ⚡️
With just weeks until Google I/O 2026, all signs point to a major upgrade for Gemini Flash, as hints of a 3.2 version briefly surfaced and deprecation notices for older models hit Vertex AI users.
Behind the scenes, insiders are buzzing about a new Gemini Flash candidate that rivals the much pricier Pro tier, suggesting Google's about to blend flagship reasoning with lightning-fast, budget-friendly models. For developers and everyday users, this means faster, smarter AI by default and a smoother transition off outgoing versions.
4. Perplexity Launches Computer for Finance Teams 💸
Perplexity has just released its Computer platform tailored for finance professionals, giving teams instant access to licensed data from industry leaders like Morningstar and PitchBook.
Alongside, the company rolled out 35 dedicated finance workflows designed to automate analysts’ weekly routines and boost productivity. New features include instant company briefs, annotated stock charts, and smarter screening tools for research-heavy tasks.
5. OpenAI and Anthropic Ramp Up AI Deployment Arms 💪
OpenAI and Anthropic are making headlines as they race to acquire engineering and consulting firms, aiming to supercharge enterprise AI deployment, Reuters reports.
Both companies are raising billions through joint ventures with major private equity players, signaling a shift from building AI models to helping businesses actually put them to work. This marks a new phase in the AI competition, as skilled talent and hands-on services become the hottest commodity for scaling artificial intelligence.
6. Microsoft: AI at Work Is a System Shock, and Most Companies Aren’t Ready 💻
A fresh 2026 Work Trend Index report from Microsoft reveals that while employees are quickly embracing AI and using it to tackle higher-value work, the real holdup is old-school organizational systems that can’t keep up.
The research found that workers using AI are more productive and creative, but only 19% of organizations are truly enabling both their people and their tech to work hand-in-hand. The study warns that companies failing to redesign how they operate risk falling behind, as “Frontier Firms” are already creating smarter, self-improving workplaces by capturing and learning from every AI-driven workflow.
The uncomfortable truth from the AI frontier is simple: the workers pushing AI hardest aren’t waiting for better enterprise plans. They’re experimenting faster than their companies can train, govern, budget, or redesign work.
That’s a problem.
Because when AI specialists multiply, agents run in the background, autonomous systems move into the real world, and employees are doing “AI homework” after hours, the real gap isn’t tool access.
It’s whether your company can turn all of that chaos into operating advantage before it turns into risk.
That’s what we tackled on today’s episode of Everyday AI: five AI trends, problems, and opportunities leaders need to understand now, from autonomous vehicles and disappearing AI generalists to FOMAT, AI homework, and the acceleration gap coming for every org chart.
1. Watch embodied AI closely 🚗
Autonomous vehicles might feel like a random consumer tech story.
They’re not.
The transcript frames Waymo as a signal that AI is moving from screens into the physical economy, and that shift matters way beyond rides. Delivery robots, drone delivery, autonomous transport, and real-world robotics are all part of the same bigger pattern.
AI isn’t just helping people type faster.
It’s starting to act in the world.
Try This
Pick one physical workflow in your business and ask where autonomy could remove delay, risk, or human inconsistency.
Start boring: deliveries, site inspections, inventory checks, facilities monitoring, handoffs, routing, or anything with repeated movement through the real world.
2. Fund the translator layer ⚡
AI generalists are getting rarer right when companies need them most.
That’s a problem because AI has split into too many working languages: text, agents, audio, video, image, vibe coding, agentic QA, orchestration, trust, observability, and local models.
Specialists are mandatory.
But without adaptive generalists, your technical teams talk past your business teams, your business teams misunderstand what’s possible, and your AI ROI quietly wanders into a ditch.
Try This
Assign one AI translator per function.
Their job is to map tools, workflows, risks, duplicated experiments, and opportunities across teams so leaders can see what’s actually happening instead of guessing from vendor demos.
3. Stop normalizing AI homework 🔥
The transcript’s biggest management problem is painfully simple.
People are learning AI after work because their actual workday is already full.
That creates shadow AI, uneven skill development, personal-subscription chaos, security risk, and burnout with a fun little innovation sticker slapped on top.
If your best people need nights and weekends to understand tools your company expects them to use, that’s not ambition.
Try This
Create a weekly AI sandbox block.
Give one team four hours, a safe environment, clear rules, and one Friday debrief: what worked, what failed, what could move into production, and what needs governance first.
4. Treat agents like labor 🧠
FOMAT sounds goofy.
It’s actually a warning.
Fear of missing agent time means high performers are starting to think of idle machines as wasted productivity. Codex, Claude Code, local models, and desktop agents aren’t just tools sitting there waiting for clicks.
That changes productivity, meetings, workflows, and how leaders should think about “headcount” without immediately turning into the worst person in the room.
Try This
Identify one workflow where an agent could run while a human does higher-judgment work.
Then define the handoff: what the agent can do, what it can’t touch, when a human reviews it, and what proof is needed before the work moves forward.
5. Close the acceleration gap 🚀
The scary part isn’t that AI is moving fast.
Everyone knows that. Congrats, we all own calendars.
The scary part is that capabilities, spending, agent adoption, and model behavior are moving faster than training, governance, job design, and executive understanding.
The transcript cites Gartner projecting worldwide AI spending will hit 2,500,000,000,000 in 2026, up 44%, and Microsoft saying active Microsoft 365 agents grew 15x year over year.
That gap is where advantage lives.
It’s also where things break.
Try This
Rewrite one AI-exposed job description before Friday.
Define what the human stops doing, what agents handle, what requires approval, what new judgment skills matter, and what guardrails need to exist before anyone celebrates the productivity gains.
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