The marketing technology industry has spent the past two years promising that artificial intelligence would do more than suggest a catchier subject line, and vendors are now racing to prove it. The latest example comes from Zoho, the privately held software company with a sprawling product suite and a sizeable Australian customer base, which has added AI agent workflows to its Campaigns platform. The shift matters because it moves AI from the role of a helpful assistant that drafts copy into the role of an operator that can carry out multi-step marketing tasks with far less human prompting.
Zoho Campaigns is the email and audience marketing tool inside the broader Zoho ecosystem, used by small and mid-sized businesses to build mailing lists, design newsletters, run drip sequences and track who opened what. Until recently, the AI layered on top of platforms like this was largely generative, meaning it helped write and summarise. The move to agent workflows signals something different: software that can be handed a goal, then plan and execute the sequence of steps needed to reach it, from segmenting an audience to scheduling sends and adjusting follow-ups based on how recipients behave.
What has actually changed
The core idea behind an AI agent is autonomy within limits. Rather than a marketer clicking through each stage of a campaign, an agent can be given an instruction such as re-engaging lapsed subscribers, then work out which contacts qualify, craft the messaging, choose timing and report back on results. Zoho’s decision to embed this capability directly into Campaigns reflects a wider industry bet that the next phase of marketing automation will be defined by agents rather than by the rules-based triggers that have powered email platforms for the better part of a decade.
It is a meaningful distinction for the people who actually run these tools. Traditional automation is rigid, following an if-this-then-that logic that breaks the moment reality does not match the pre-set path. Agentic systems promise to handle ambiguity, making judgement calls that previously required a human in the chair. Whether they deliver on that promise consistently, and safely, is the open question hanging over the entire category.
Two ways to read the move
For optimists, this is the democratisation of sophisticated marketing. A two-person startup in Geelong or a regional retailer in Toowoomba rarely has the budget for a dedicated marketing operations specialist. An agent that can quietly manage segmentation, timing and testing could hand those smaller players capabilities that were once the preserve of enterprises with deep pockets and large teams. Zoho has built much of its reputation on exactly this pitch, positioning its suite as an affordable alternative to the pricier American giants of the martech world, and agent workflows extend that argument.
The sceptical reading is harder to dismiss. Marketers have been burned before by automation that promised to think for them and instead flooded inboxes with mistimed or poorly targeted messages. Handing more decision-making to an agent raises genuine concerns about brand voice, compliance and the risk of an autonomous system acting on flawed data. There is also the uncomfortable labour question that follows every agentic launch: if the software can run the campaign, what happens to the junior roles that used to learn the craft by doing exactly that work? These are not reasons to dismiss the technology, but they are reasons to deploy it with the brakes within reach.
The Australian stakes
For Australian businesses, the arrival of agent workflows in a mainstream, affordable platform lands at a particular moment. Local adoption of AI tools has been brisk among marketers, yet the regulatory environment is still catching up. Any system that automatically decides who receives a marketing message has to operate inside the Spam Act 2003, which requires consent, clear identification of the sender and a functioning unsubscribe option. An agent that sends on a business’s behalf does not absorb that legal responsibility; the business still does. That puts the onus on Australian firms to understand exactly what their agents are empowered to do before letting them loose on a customer list.
Privacy is the other pressure point. The federal government has been working through reforms to the Privacy Act, and automated decision-making is squarely in the frame. Marketing agents that profile and segment audiences draw on personal information, and the direction of travel in Canberra points toward greater transparency obligations about how that data is used. Australian marketers adopting agent workflows now would be wise to assume the compliance bar will rise rather than fall, and to document how their automated systems reach the decisions they make.
There is a competitive angle too. Zoho has invested in local infrastructure and data residency to court Australian customers wary of sending their data offshore, and agent features baked into a platform with an Australian footprint may appeal to organisations in government-adjacent sectors or regulated industries that care where their information lives. In a market dominated by the large US platforms, a credible alternative with agentic features and a local presence changes the calculus for buyers.
What comes next
The honest answer is that the proof will be in the sending. Agent workflows are easy to announce and hard to perfect, and the real test is whether they reliably improve open rates, conversions and customer relationships without generating the kind of errors that erode trust. Expect the rest of the martech field to match the feature quickly, because no major vendor wants to be seen as the one still offering yesterday’s rules-based automation while rivals talk about agents.
For Australian marketers, the sensible posture is curious but careful. These tools are worth piloting on low-risk campaigns, with human review kept firmly in the loop, while the compliance and performance picture becomes clearer. The businesses that win with agentic marketing will likely be the ones that treat the agent as a capable junior colleague rather than an infallible replacement, delegating the repetitive work while keeping judgement, and accountability, in human hands.
Sources: GNews · AU retail & consumer AI.
