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Productivity or Pink Slips? The Rise of Agentic AI

Ok, enough with the scaremongering – let’s thrash it out.

Is AI going to replace us any time soon?

One perspective’s look at the medium term future:

    “Cancer is cured, the economy grows at 10% a year… and 20% of people don’t have jobs.”

So said Dario Amodei, CEO of Anthropic, in one of the most jarring soundbites to emerge from the AI sector this year. It’s not a dystopian movie pitch — it’s a plausible trajectory.

The Brisbane Times recently spotlighted how Telstra is leaning hard into this future, and it starts with deploying so-called Agentic AI – discrete AI tools able to do a bunch of things with minimal oversight.  From automating customer service to writing code, the $54 billion telco is betting big that its next era won’t be driven just by fibre and frequency, but by “digital agents“: AI tools with autonomy to act, learn and optimise at scale.

While Telstra CEO Vicki Brady didn’t give hard numbers on expected job cuts, she did suggest the company’s workforce will likely be smaller by 2030. No bold claims — just quiet math. That’s the real face of the AI revolution: not mass firings, but jobs that never get hired in the first place.

Enter the Digital Employee

Nvidia’s Jensen Huang calls them “digital employees” — autonomous, specialised AI agents that handle roles from cybersecurity to network monitoring to legal summarisation. Unlike your flesh-and-blood team, they don’t sleep, unionise, or call in sick.

Tech giants like Microsoft, Canva, and Shopify are already eliminating roles that generative AI can perform faster, cheaper or more reliably. Shopify’s test for approving new hires? Prove the job can’t be done by AI.

Even highly paid software engineers and technical writers are now brushing up résumés — or joining unions. The shock isn’t just the job losses — it’s the redefinition of what work is.

The Illusion of Understanding

And yet — for all its prowess, there’s a lot that AI still doesn’t understand.

It doesn’t feel shame, pride, love, loyalty or regret. It doesn’t know the weight of a moral dilemma or the subtle ache of ambiguity. It doesn’t take responsibility. It hasn’t grown up anywhere. It’s very good at simulating humanity, but it hasn’t cracked what it means to be human.

Here are just a few areas where that matters:

• Moral Judgment & Empathy

AI doesn’t feel anything. It can mimic empathetic language, but it doesn’t understand suffering, joy, duty, shame, or dignity. That matters in:

  • law (e.g. sentencing, equitable remedies)

  • medicine (e.g. breaking bad news)

  • management (e.g. mentoring, handling conflict)

  • creative industries (e.g. stories that evoke genuine emotion)

• Contextual Wisdom and Ethical Trade-Offs

Humans weigh competing priorities in fluid, unquantifiable ways. A judge balancing public policy with individual hardship, or a parent navigating fairness between siblings — AI can model it, but not feel the stakes or bear the consequences.

• Lived Experience and Cultural Intuition

Even with perfect training data, AI lacks a body, a history, a community. It hasn’t known pain or formed personal relationships. It cannot speak authentically from or to a place of real cultural knowledge.

• Responsibility and Accountability

We trust humans with hard decisions because they can be held responsible. There’s no moral courage or ethical failure in the output of a large language model — only the illusion of one.

These aren’t just philosophical quibbles. They’re pressing questions for:

  • Law: Who bears blame when an AI agent misfires?

  • Healthcare: Who decides whether aggressive treatment is compassionate or cruel?

  • Leadership: Can you coach courage into someone via algorithm?

The Uncomfortable Part

AI already mimics a lot of that better than expected.  Consider:

• Empathy Simulation

GPT-4, Claude and others can write with stunning emotional acuity. They generate responses that feel empathetic, artistic or wise. It’s not authentic — but it’s increasingly indistinguishable, and often considered “good enough” by the humans receiving it.

• Decision-Making and Pattern Recognition at Scale

AI already outperforms humans at certain medical diagnoses, legal research, contract review and logistics. Its consistency and recall beat even expert practitioners — and that pushes decision-making downstream to human review of AI output.

• Creative Collaboration

AI is co-authoring books, scoring music, designing buildings. The raw ideas remain human-led (for now), but AI increasingly does the scaffolding. The assistant as co-creator is here.

• Agentic AI and Task Autonomy

Agentic AI can take a task, plan it, execute it, and evaluate the results. That’s edging close to synthetic intentionality. In limited domains, it already feels like independent judgment.

The Upshot

What AI can do — increasingly well — is mimic language, logic and even tone. It can co-author your policy doc, diagnose your anomaly, draft your contract (although still terribly at present – which, frankly, makes the contracts lawyer in me feel safe for now), and script your empathy.

But ask it to weigh competing values in an evolving ethical context — or even just draft a nuanced commercial agreement, conduct accurate scientific or legal research, or develop a strategy based on historical fact — and you quickly meet its limits.

Those edge cases still belong to humans in the loop.

So Who Owns the Output?

As businesses delegate more high-order tasks to autonomous agents, legal questions are multiplying:

  • Who owns the IP generated by a self-directed AI agent?
    → At this stage, probably no one — though ordinary IP rules apply to any human-developed improvements.

  • Can AI-created processes be patented or protected as trade secrets?
    → Not patented without significant human input — at least not under current Australian (or global) standards. Trade secrets? Only if the process was generated in confidential circumstances, and even then, likely only protected contractually — or by a very sympathetic equity judge with a soft spot for machines and a broad view of what counts as confidence.

  • Will the law begin to treat AI output as a kind of quasi-employee contribution?
    → Hard to say. But this author’s view: yes — we’re likely to see forms of legal recognition for things created wholly or partly by generative AI, especially as its use becomes ubiquitous.

Telstra’s ambition to shift from “network provider” to “bespoke experience platform” only deepens the stakes. If AI manages your venue’s mobile traffic to prioritise EFTPOS over selfies, who owns that logic? What’s the IP — and who gets paid?

We’re very likely to find out soon.

We May Not Be Replaced, But We Are Being Rerouted

What’s unfolding isn’t the erasure of human work — but its redistribution.

Jobs once seen as safe — legal drafting, coding, customer care — are being sliced up and reassembled into workflows where humans supervise, train or rubber-stamp what AI proposes.

We’re becoming fewer creators, more editors. Fewer builders, more overseers.

This is the heart of the AI transition: it’s not about making us obsolete.  It’s about making us team players — not to say optional — in a landscape of role transformation, driven by the pursuit of results.

That’s why this isn’t just an IP question. It’s a human one.

So yes — cancer might be cured. The economy might boom.  But as the digital employee clocks in, we’ll need more than productivity gains.

We’ll need new answers — about ownership, ethics, responsibility and value.  Not just in law, but in how we define a fair and meaningful future.

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Maxim Forgets the Maxim, Chases Nuclear but Bombs

Maxim Media, the publishers behind the well-known men’s lifestyle magazine and brand MAXIM, had minimal success when in Maxim Media Inc. v Nuclear Enterprises Pty Ltd [2024] FCA 1443 they sought urgent Federal Court orders to shut down an Australian company allegedly riding on their name — through magazines, domain names, destination tours, and model management services.

Despite the explosive accusations, the Court delivered a much more subdued response.

Maxim had delayed for some time in coming to Court, but now applied for interlocutory relief, seeking immediate injunctions to restrain:

  • Use of the MAXIM name in any form in Australia;

  • Distribution of a competing Maxim Magazine;

  • Operation of maxim.com.au, destinationmaxim.com.au, and related social handles;

  • Any further unauthorised brand use.

The application relied on trade marks registered in 2020 and 2023 — and on allegations that the Australian respondents, including Nuclear Enterprises and Michael Downs, had no licence or authority to use the name.

Justice Rofe refused the injunction — not because the claim was doomed, but because:

  • Ownership and licensing rights hadn’t been clearly established yet;

  • There were substantial factual disputes that needed a full trial;

  • There was no persuasive case for irreparable harm that couldn’t be remedied later;

  • The balance of convenience didn’t justify urgent intervention — particularly given Maxim’s delay in seeking relief (ironically, Maxim had ignored the equitable maxim regarding laches).

The proceeding will now be allocated to a docket judge for a full hearing.

The main takeaways here are:

  • Interlocutory relief isn’t automatic, even with a registered trade mark — the applicant still needs clean title, urgency, and evidence of irreparable harm.

  • Delays hurt. The longer you wait to challenge a rival’s use of your mark, the harder it is to convince a court that urgent action is needed.

The case could still blow Maxim’s way at a final hearing — but for now, Nuclear gets to keep exploding – and the fallout will be huge.

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Series Killers: When IP Australia Oversteps the (Descriptive) Mark

So you’ve filed a series trade mark in Australia. The marks are visually identical except for a single word that tweaks the service type — say, “BURST PLUMBING”, “BURST CLEANING”, “BURST GARDENING”.

All good, right?

Not if you ask IP Australia. According to the Office Manual, if your differentiating word describes only some of the services listed — even if it’s a totally non-distinctive, snore-worthy adjective — your series could be headed for rejection.

The rationale? That descriptive differences must apply to all of the goods/services claimed. Not some. Not most. All.

But is that legally correct?

Let’s unpack this.

The Law (Actually – and Not the Manual)

Section 51(1) of the Trade Marks Act 1995 (Cth) says you can register a series if:

“…the trade marks resemble each other in material particulars and differ only in respect of one or more of the following matters:
(a) statements or representations as to the goods or services  in relation to which the trade marks are used or are intended to be used;
(b) statements or representations as to number, price, quality or names of places; or
(c) the colour of any part of the trade mark.”

So there is a legal restriction — but it’s not about whether the descriptive term applies to all of the goods or services. It’s about whether the difference falls into one of the above three categories.

If your only point of difference is a generic descriptor like “PLUMBING” or “CLEANING” — that’s likely a “statement as to the services” under paragraph (a). ✅ Tick.

Whether that statement applies to all of the services? That’s not part of the statutory text. That’s IP Australia adding friction by policy — not by law.

The Practice (Not the Law)

IP Australia’s position is that if “CLEANING” only refers to a handful of the listed services — say, home cleaning and commercial premises — while your broader list also covers plumbing, garden maintenance, and pest control, then the marks in the series are no longer sufficiently aligned for a single registration.

Their concern: you’re using the series construct as a backdoor to bulk file a grab bag of marks that lack genuine commonality.

But here’s the catch: section 51(1) does not impose a requirement that the differing matter — like “CLEANING” — must describe all of the goods or services. The section simply requires that:

  1. The marks resemble each other in material particulars, and

  2. The differences fall only within one or more of the categories listed:

    • statements about the goods/services,

    • statements about number, price, quality or place, or

    • colour of part of the mark.

So, if “CLEANING” is a statement about services (and it is), and the marks still resemble each other in their key features (say, the word “BURST” in a bold red typeface with a splash logo), then the Act is satisfied.

The idea that every descriptive word must apply to all services is IP Australia policy, not law. It’s not in the Act. It’s not in the Explanatory Memorandum. It’s simply a convenient threshold applied to keep the register tidy — which may be operationally defensible, but not legally required.

What’s a Brand Owner To Do?

If you’re filing a series mark where the only difference is a descriptive word that applies to some — but not all — of the listed services, you’ve got two choices:

  1. Play nice: Redraft your specification to group services so that each descriptor applies across the board. That means breaking up the series and filing multiple applications.

  2. Push back: If the examiner raises an objection, go back to the legislation. Section 51(1) only requires that:

    • The marks resemble each other in material particulars, and

    • The differences fall only within the three specified categories.

You may not win every time, but you’ll be on solid legal ground — and might just push the boundaries of a policy that’s grown a little too rigid for its boots.

There’s no additional legal requirement that the differing statement about services must relate to all of them. That’s a policy position, not a statutory one.

So if “BURST PLUMBING” and “BURST CLEANING” share all core branding elements and differ only by a word that is a statement about services — you’ve met the test under the Act.

Bottom Line

IP Australia’s insistence on descriptive uniformity across the entire class spec is not supported by s 51(1) of the Act. The only legal requirement is that the marks:

  • Resemble each other in material particulars, and

  • Differ only in respect of statements as to goods/services, price, quality, place, or colour.

Everything else? That’s Office convenience, not legislative command.

So don’t be afraid to push back.

And if that fails… well, split the applications, swallow the extra fee, and tell your accountant it was a “protest expense” … the cost of resisting bureaucratic overreach.

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Paul Bender’s music has been sampled by Beyoncé and Kendrick. His band, Hiatus Kaiyote, has three Grammy nominations. His side project, The Sweet Enoughs, racks up millions of streams. So it came as a shock when fans started hearing tracks on his Spotify profile that he didn’t recognise — or approve.

Tracks that sounded like they’d been composed by an AI trapped in an elevator.

“It was probably the worst attempt at music I’ve ever heard,” Bender told Brisbane Times. “Just absolutely cooked.” His reaction soon gave way to a grim realisation: someone was uploading fake music — apparently AI-generated — directly to his artist profile. And it wasn’t just Spotify. Apple Music, Tidal, YouTube Music and Deezer all carried the same fakes.

No passwords were stolen. No logins compromised. Just a ticking time bomb in the music distribution supply chain.

The Loophole That Became a Business Model

The scam works like this: a grifter uploads garbage tracks via a digital music distributor, assigns them to a known artist name, and — voila — the platform “maps” it to the artist’s official profile. Instant legitimacy, with algorithmic discovery to match.

No ID check. No consent. No authentication.

This isn’t just a quirk of one platform’s back end. It’s systemic. And it’s being exploited on an industrial scale. One vlogger, TankTheTech, showed how anyone can assign AI music to an artist profile in under ten minutes.

And the numbers are staggering:

  • Deezer reports that 18% of its daily uploads in 2025 are AI-generated.

  • Mubert, an AI music tool, claims over 100 million tracks were made on its platform in just the first half of 2023.

  • The Music Fights Fraud Alliance estimates 10% of all global music streams are fraudulent, with some distributors seeing fraud rates as high as 50%.

That’s not fringe — it’s a revenue model. And it’s bleeding real artists.

Legal Implications: Between Passing Off and Platform Apathy

Let’s be clear: uploading fake music under someone else’s name looks a lot like impersonation, if not passing off, especially where artist reputation and income are at stake. There may also be:

  • Copyright infringement if elements of an artist’s work were used in training or replication.

  • Moral rights violations under the Copyright Act 1968 (Cth), especially the right of integrity where a fake work is falsely attributed.

  • Misleading or deceptive conduct under section 18 of the Australian Consumer Law.

Yet despite the legal exposure, platforms and distributors are playing hot potato with responsibility. Spotify calls it a “mapping issue.” Artists call it what it is: a scam that platforms are structurally enabling.

Why This Matters — Beyond Music

This isn’t just a niche concern for indie musicians. It’s a case study in what happens when:

  • AI-generated content floods creative ecosystems,

  • platforms prioritise volume over verification,

  • and IP rights become an afterthought to scale.

In short, it’s the algorithm’s world — and creatives are just living in it.

But not quietly. Artists like Bender and Michael League (of Snarky Puppy) are now speaking out and pushing for industry action. With growing numbers of testimonials and escalating complaints, the music world may be the canary in the coal mine for a broader wave of AI impersonation and platform indifference.

Until then, don’t be surprised if the next time you hit play on a favourite artist’s profile… what comes out is 100% algorithm, 0% soul.

Here’s a thought: 2FA authentication before allowing uploads? Verify before you amplify!

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Crunch Time for CRUNCHIEZ: Cadbury Blocks Rival Chocolate Mark

In a sweet victory for brand owners, Cadbury UK Limited has successfully opposed the registration of the trade mark CRUNCHIEZ SURPRIZE in Australia, convincing the Trade Marks Office that the name was too close for comfort to its iconic CRUNCHIE mark.

Greek confectionery importer Relkon Hellas applied to extend international protection for its mark CRUNCHIEZ SURPRIZE (featuring stylised graphics) for use in relation to chocolate and confectionery in Class 30. Cadbury, relying on decades of use of the CRUNCHIE mark in Australia, opposed the application on several grounds — but ultimately succeeded on one: section 60 of the Trade Marks Act 1995 (Cth).

Under s 60, a trade mark may be refused if another mark had acquired a reputation in Australia before the relevant date, and the use of the new mark would be likely to deceive or cause confusion.

Here’s how the Delegate broke it down:

Reputation:
Cadbury’s CRUNCHIE has been sold in Australia since the 1950s and enjoys widespread recognition. Sales figures, advertising spend, historical ads, and retail presence all pointed to a strong reputation in Australia, particularly for chocolate and confectionery.

Similarity of Marks:
While not identical, CRUNCHIE and CRUNCHIEZ SURPRIZE share key elements:

  • The word CRUNCHIEZ was viewed as a near-plural of CRUNCHIE, differing by just one letter.

  • The additional term SURPRIZE was considered descriptive and did little to distinguish the overall impression.

  • Stylisation differences weren’t enough to avoid confusion.

Likely Confusion:
The Delegate found that ordinary consumers could reasonably wonder whether CRUNCHIEZ SURPRIZE products were from the same source as Cadbury’s CRUNCHIE line — especially when both appeared in close proximity in stores like Kmart and The Reject Shop.

Interesting side note – the evidence of where the competing brands sat in places like K-mart and The Reject Shop was adduced not by Cadbury, but by Relkon Hallas, whose lawyers used that evidence to submit that because the brands were not literally side-by-side, this supported a conclusion that there would be no confusion.

That turned out to be a bit of a strategic fail as the Delegate thought this evidence supported a finding of confusion because it was clear evidence that the relatively new CRUNCHIEZ SURPRIZE mark was being advertised in close proximity to the long-standing and very famous CRUNCHIE mark.

Oops.

The Outcome
Protection for CRUNCHIEZ SURPRIZE was refused in full. Cadbury was awarded costs, and Relkon Hellas left with a lesson in brand proximity.

Key Takeaways for IP Owners

  • Reputation is a powerful shield. Long-standing brand presence, even on basic goods like chocolate bars, can stop later marks in their tracks.

  • Adding a “z” won’t save you. Minor spelling tweaks and descriptive add-ons (like “Surprize”) rarely neutralise the risk of confusion.

  • Stylisation matters — but not enough. Graphic flourishes won’t rescue a mark if the words dominate and invite association with a famous brand.

  • Proximate promotions can pummel you. If your goods end up shelved near a well-known competitor, that visual proximity will weigh heavily in the analysis.

IP Mojo Takeaway:
If you’re naming a new chocolate product and your trade mark sounds like a Cadbury classic… you’re probably skating on thin nougat.

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Whose Work Is It Anyway? The Remix War, AI, Coffee Plungers and Swimsuits

From Elton John to anonymous meme-makers, a battle is raging over what it means to be “creative” — and whether it starts with permission.

Two stories made waves in copyright circles last week:

  • In the UK, Sir Elton John, Sir Paul McCartney and other musical heavyweights called for stronger rules to stop AI from “scraping” their songs without a licence.

  • In India, news agency ANI drew criticism for aggressively issuing YouTube copyright claims — even for sub-10 second clips — triggering takedown threats against creators.

At first glance, these might seem worlds apart. But they highlight the same question:

At what point does using someone else’s work become exploitation, not inspiration?

And who decides?

Creators vs Reusers: Two Sides of the Copyright Culture Clash

On one side: Creators — musicians, writers, filmmakers, photographers — frustrated by tech platforms and algorithms ingesting their work without permission. Whether it’s AI training data or news footage embedded in political commentary, their message is the same:
“You’re building on our backs. Pay up.”

On the other side: Remixers, meme-makers, educators, and critics argue that strict copyright regimes chill creativity. “How can we critique culture,” they ask, “if we’re not allowed to reference it?”

This isn’t new — hip hop, collage art, satire, and even pop music are full of samples and nods. But AI has industrialised the scale of reuse. It doesn’t borrow one beat or a single shot. It eats the entire catalogue — then spits out something “new.”

So what counts as originality anymore?

Australian Lens: Seafolly, Bodum, and the Meaning of “Original”

Seafolly v Madden [2012] FCA 1346

In this high-profile swimwear spat, designer Leah Madden accused Seafolly of copying her designs. She posted comparison images on social media implying that Seafolly had engaged in plagiarism. Seafolly sued for misleading and deceptive conduct under ss 52 and 53 of the Trade Practices Act 1974 (predecessors to s18 of the Australian Consumer Law – which had by then commenced but the relevant conduct being sued for took place before it had commenced).

The Federal Court found that Madden’s claims were not only misleading but also unsubstantiated, because the design similarities were not the result of actual copying. The case reinforced that:

  • Independent creation is a valid defence, even if the resulting works are similar

  • Superficial resemblance isn’t enough — there must be a causal connection

It’s a reminder that derivation must be substantial and material, not speculative or assumed.

Bodum v DKSH [2011] FCAFC 98

This case involved Bodum’s iconic French press coffee plunger — the Chambord — and whether a rival product sold by DKSH under the “Euroline” brand misled consumers or passed off Bodum’s get-up as its own.

Bodum alleged misleading or deceptive conduct and passing off, based not on name or logo, but on the visual appearance of the product: a clear glass beaker, metal band, and distinctive handles, which had come to be strongly associated with Bodum.

At trial, the Federal Court rejected Bodum’s claims. But on appeal, the Full Federal Court reversed that decision, holding that:

  • Bodum had a substantial reputation in the get-up alone;

  • The Euroline plunger was highly similar in appearance; and

  • DKSH’s failure to adequately differentiate its product through branding or design gave rise to a misleading impression.

Both passing off and misleading/deceptive conduct (also under the old s52) were found. The Court emphasised that reputation in shape and design can be enough — and differentiation must be meaningful, not tokenistic.

The AI Angle: Who Trains Whom?

AI tools like ChatGPT, Midjourney, and Suno don’t just copy works. They learn patterns from thousands of inputs. But in doing so, they arguably absorb creative expression — chord progressions, phrasing, brushstroke styles — and then make new outputs in that same vein.

AI developers claim this is fair use or transformative. Artists argue it’s a form of invisible appropriation — no different from copying and tweaking a painting, but with zero attribution or compensation.

It’s the Seafolly and Bodum problem, scaled up: if AI’s “original” work was trained on 10,000 human ones, is it really original? Or just a remix with plausible deniability?

The Bottom Line

Copyright law is meant to balance:

  • Encouraging creativity

  • Rewarding labour

  • Allowing critique and cultural dialogue

But that balance is breaking under the weight of machine learning models and automated copyright bots. As Seafolly and Bodum show, the law still values intention, process, and context — not just resemblance.

Yet in a world of remix and AI, intention is opaque, and process is synthetic.

So where do we draw the line?