Speaker 1: Welcome to AI assembled the top AI news for small business.
Speaker 1: I'm Chris daily and each week I bring you the
Speaker 1: most important AI developments that can transform your business. Let's
Speaker 1: dive into this week's top stories.
Speaker 2: Apple has sued open Ai and federal court in Northern California,
Speaker 2: accusing the AI lab of stealing trade secrets to build
Speaker 2: its own consumer hardware. This is a dramatic reversal for
Speaker 2: two companies that were high profile partners just two years
Speaker 2: ago when Chat GPT was baked into the iPhone's operating system.
Speaker 2: Apple's complaint pulls no punches. It alleges that at every level,
Speaker 2: from technical staff up to open AI's chief hardware officer,
Speaker 2: the company has been quote stealing Apple's trade secrets and
Speaker 2: confidential information end quote. That chief hardware officer, Tang Tan,
Speaker 2: is a former Apple vice president, and he is now
Speaker 2: personally named as a defendant. Apple says Tan directed job
Speaker 2: candidates still working at Apple to bring quote actual parts
Speaker 2: end quote from Apple to their interviews for what he
Speaker 2: called show and tell sessions so his team at open
Speaker 2: Ai could pull out more confidential information. Apple also alleges
Speaker 2: open Ai coached departing Apple employees on how to evade
Speaker 2: Apple's security processes on their way out the door, and
Speaker 2: that one former employee, Chang Liu, walked off with an
Speaker 2: Apple laptop. Liu is also named as a defendant, and
Speaker 2: Apple claims open ai has been asking outside hardware firms
Speaker 2: to use a metal finishing technique Apple invented, while misleading
Speaker 2: those partners into believing they had Apple's permission. The backdrop
Speaker 2: here is open AI's hardware push. Last year, open ai
Speaker 2: paid six point four billion dollar for former Apple designer
Speaker 2: Johnny Ives. Device startup and CEO Sam Altman has said
Speaker 2: the first prototypes are finished. Apple is asking the court
Speaker 2: for damages, injunctions, and an order forcing OpenAI to stop
Speaker 2: using its trade secrets. Why it matters for small businesses.
Speaker 2: If you build any part of your workflow on the
Speaker 2: assumption that Apple and open Ai would keep playing nicely together,
Speaker 2: that assumption is now shaky. The updated SERI coming this
Speaker 2: fall is already switching to Google's Gemini models instead of
Speaker 2: open Ai. Expect messier integrations between Apple devices and chat
Speaker 2: GPT going forward, and expect OpenAI's promised hardware to arrive
Speaker 2: under a legal cloud that could delay ship dates. If
Speaker 2: you are an SMB running on Apple Intelligence plus Chat GPT.
Speaker 2: Do not bet your Q four roadmap on that pairing,
Speaker 2: staying f frictionless. Now moving on, Microsoft has just made
Speaker 2: it a lot cheaper to skill up your team on
Speaker 2: the single hottest topic in enterprise AI right now, which
Speaker 2: is AI agents. Those are AI systems that take actions
Speaker 2: on your behalf, not just answer questions. Microsoft has released
Speaker 2: a completely free ten lesson course called AI Agents for
Speaker 2: beginners on Microsoft Learn and an expanded companion repository on
Speaker 2: GitHub with twenty one lessons that goes even deeper. The
Speaker 2: course walks you from concept to code. It covers what
Speaker 2: an agent actually is, the design patterns behind them, tool use, planning,
Speaker 2: multi agent systems, memory, and how to actually ship one
Speaker 2: to production. There is a hands on interactive version on
Speaker 2: LinkedIn Learning too, running about fifty minutes if you just
Speaker 2: want the fast pass, and crucially, it uses accessible real
Speaker 2: world tooling, not just Microsoft's own stack. Why this is
Speaker 2: a big deal for SMB owners Enterprise firms are spending
Speaker 2: tens of thousands of dollars per seat sending engineers to
Speaker 2: agent boot camps. This course covers the same foundational material
Speaker 2: from a company that runs the underlying infrastructure at a
Speaker 2: price point of zero. For a small business, that means
Speaker 2: your existing developer, or even a technically curious operations lead
Speaker 2: can learn enough in a weekend to prototype an agent
Speaker 2: that handles quoting, appointment reminders, invoice follow ups, or customer
Speaker 2: support triage. You do not need to hire a specialist.
Speaker 2: You do not need to buy an enterprise agent platform.
Speaker 2: You need one motivated person, ten free lessons, and about
Speaker 2: a week. If AI agents have been on your maybe
Speaker 2: someday list, this is the week to move them onto
Speaker 2: the this quarter list.
Speaker 3: Meta has yanked a brand new Instagram AI feature off
Speaker 3: the platform just days after launching it after a wave
Speaker 3: of public backlash. On July seven, Meta rolled out something
Speaker 3: called muse Image. It was built into Meta Ai, Instagram,
Speaker 3: Stories and WhatsApp, and it let users generate and edit
Speaker 3: AI images, including by feeding it public Instagram photos and
Speaker 3: sketching changes on top of them. By July tenth, three
Speaker 3: days later, it was gone. Meta admitted in its own
Speaker 3: words that it had quote missed the mark end quote
Speaker 3: and said the feature was no longer available. The core
Speaker 3: problem was privacy. The tool made it very easy to
Speaker 3: grab images from public Instagram accounts, run them through generative
Speaker 3: AI and produce modified versions of real people, potentially without
Speaker 3: their knowledge. Regulators, creators, and every day users pushed back fast,
Speaker 3: and Meta blinked. Why this matters for s mbs Two
Speaker 3: lessons here. First, if your small business runs any part
Speaker 3: of its marketing through Instagram or Meta AI tools, understand
Speaker 3: that the feature set is unstable right now. Something you
Speaker 3: build a campaign around this week can quietly disappear next week.
Speaker 3: Do not become dependent on any single generative AI feature
Speaker 3: inside a social platform. Second, the backlash tells you where
Speaker 3: the line is with your own customers. If you are
Speaker 3: experimenting with AI generated images of clients, employees, or user
Speaker 3: submitted photos, get explicit consent and think hard about how
Speaker 3: it would look if a screen shot ended up in
Speaker 3: a local news story. The technology is running faster than
Speaker 3: the trust, and Meta just paid the reputational bill for
Speaker 3: finding that out in public. Now to the story, A
Speaker 3: lot of executives are quietly panicking about this week. Enterprises
Speaker 3: are getting hit with AI bills that are far far
Speaker 3: bigger than they expected, and in many cases, those bills
Speaker 3: are now higher than the salaries of the workers those
Speaker 3: companies laid off to pay for AI in the first place.
Speaker 3: A new kp MG survey of over two thousand senior
Speaker 3: executives across twenty countries found that twenty nine percent of them,
Speaker 3: nearly one in three, have no idea where their growing
Speaker 3: AI costs are actually coming from. Another third admitted their
Speaker 3: own confusion about AI economics is the main thing blocking
Speaker 3: them from deploying AI effectively. In plain English, the people
Speaker 3: signing the checks do not understand what they are paying for.
Speaker 3: The examples are watering. Uber's chief technology officer disclosed that
Speaker 3: Uber burned through its entire twenty twenty six AI coding
Speaker 3: budget in four months. By March, eighty four percent of
Speaker 3: Uber engineers had adopted the AI coding tool, and roughly
Speaker 3: seventy percent of committed code now comes from AI. Uber's
Speaker 3: own president admitted publicly that all that token usage did
Speaker 3: not clearly correlate with more useful features shipped to customers. Microsoft,
Speaker 3: which has invested about thirteen billion dollars in open AI,
Speaker 3: told engineers in one of its major divisions to stop
Speaker 3: using an AI coding assistant because the bill got out
Speaker 3: of control. One unnamed company, per reporting from Axios, racked
Speaker 3: up a five hundred million dollar claud bill in a
Speaker 3: single month after management forgot to set a usage cap.
Speaker 3: Nvidia's own VP of a fplied deep learning has said
Speaker 3: on the record that the cost of compute for his
Speaker 3: team now exceeds what Nvidia pays the humans using it. Meanwhile,
Speaker 3: more than one hundred and fifteen thousand tech workers have
Speaker 3: been laid off in twenty twenty six alone, across more
Speaker 3: than one hundred and fifty companies, with the stated reason
Speaker 3: being reallocation toward AI. Meta cut eight thousand rolls. Wis
Speaker 3: cut a fifth of its workforce, Block halved headcount, Atlasian
Speaker 3: shed sixteen hundred jobs. And here is the punchline. An
Speaker 3: MIT study found AI automation is economically viable in only
Speaker 3: about twenty three percent of roles. For the other seventy
Speaker 3: seven percent, humans are still cheaper. Companies fired the humans
Speaker 3: then found out the machines cost more.
Speaker 2: So what does the enterprise AI bill shock mean for
Speaker 2: you running a small or mid size business. Honestly, this
Speaker 2: is one of the rare weeks where being small is
Speaker 2: a genuine advantage. Big companies are stuck. They've locked in
Speaker 2: enterprise contracts, laid off staff, and now they're on the
Speaker 2: hook for usage based AI pricing that is climbing every quarter.
Speaker 2: Analysts project that when AI pricing fully normalizes to reflect
Speaker 2: real infrastructure costs, enterprise AI bills will rise another thirty
Speaker 2: to fifty percent above where they are today. Anthropic already
Speaker 2: moved enterprise customers from flat rate plans to usage based
Speaker 2: billing tied to actual compute in April. Get Hub copilot
Speaker 2: followed weeks later. The era of flat rate all you
Speaker 2: can eat AI is ending. You as a small business,
Speaker 2: still have time to be smart. Three things to do
Speaker 2: this week. Number One, before you sign any AI tool contract,
Speaker 2: ask specifically whether the pricing is flo at rate or
Speaker 2: usage based, and ask for a hard monthly cap. That
Speaker 2: five hundred million dollar claud bill happened because someone forgot
Speaker 2: to set a cap. Do not be that someone. Number two,
Speaker 2: Do not use frontier models for tasks that do not
Speaker 2: need them. Roughly ninety five percent of enterprise AI usage
Speaker 2: still runs on the most expensive frontier models, even for
Speaker 2: work that does not require that horse power. If you
Speaker 2: are using a top tier model to reformat spreadsheets or
Speaker 2: answer basic FAQ emails, you are lighting money on fire.
Speaker 2: Match the model to the job number three. Before you
Speaker 2: replace a person with AI, do the actual math on
Speaker 2: total cost of ownership over twelve months, including tokens, integration, monitoring,
Speaker 2: error correction, and the human hours to supervise it. In
Speaker 2: roughly three quarters of roles, the human is still the
Speaker 2: cheaper option. Zooming out on the whole week Apple versus
Speaker 2: Open AI tells you the AI platform wars are entering
Speaker 2: a new, more legal phase and your integrations may get bumpy.
Speaker 2: Microsoft's Free Agent course tells you the skills gap is
Speaker 2: closing fast, and it is closing in your favor if
Speaker 2: you move now. Meta's Muse Image Retreat tells you generative
Speaker 2: AI features inside social platforms are volatile and consumer trust
Speaker 2: is fragile. And the enterprise cost story tells you the
Speaker 2: biggest companies in the world do not actually understand their
Speaker 2: own AI spending, which means the playbook is still wide
Speaker 2: open for a nimble SMB that picks the right models,
Speaker 2: sets the right caps, trains one person on agents, and
Speaker 2: does not lay off staff to chase a bill it
Speaker 2: cannot forecast. This is genuinely a moment of advantage. The
Speaker 2: advantage will not last forever, but it is here, right now,
Speaker 2: this week. Use it.
Speaker 1: That's it for this week's AI assembled the top AI
Speaker 1: news for small business. If you found this valuable, share
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Speaker 1: Slash aiready until next week, keep innovating and keep it real.