Visibility Is the New Ranking
Marketing Week reports that most B2B brands are ramping up their focus on AI visibility, meaning whether they get named when a buyer asks ChatGPT, Gemini or Perplexity for a shortlist. This is the practical successor to the SEO conversation, and it is moving fast. The problem is that most of the advice circulating, including the “free traffic from ChatGPT” tutorials, is thin and untested.
What I can say is that the basics have not changed. Models draw on clear, well-structured, credible content, and on mentions across sources they trust. If your product pages are vague and your case studies are gated, you are hard to cite. Sydney B2B teams should run a simple test this month: ask the major assistants the ten questions your buyers actually ask, and record whether you appear, how you are described, and who appears instead.
That audit costs almost nothing and it will tell you more than another tool subscription.
The Boardroom Gets Cautious
Wesfarmers chair Michael Chaney has been preaching AI caution while the market is full of transformation talk, according to the SMH. Coming from the chair of one of Australia’s largest and most disciplined retail and industrial groups, that matters. He is not saying avoid AI. He is saying be wary of promises that outrun evidence.
I think that is the right posture for 2026. McKinsey’s research has repeatedly found that many companies are using generative AI, but a much smaller share can point to a material effect on earnings. That gap is an execution problem, not a technology problem. Pilots stall, data is messy, and nobody owns the outcome.
For mid-sized Sydney firms, the lesson is to pick two or three use cases with a measurable result, such as reporting time, lead qualification or support triage, and run them properly before adding more.
Your Team Isn’t Talking About AI
The SMH ran a piece on the communication gap in the AI workplace, and it matches what I hear from both clients and candidates. Some staff are using AI heavily and quietly. Others are avoiding it because they are unsure what is allowed. Managers often do not know which group is which.
That silence carries real risk. People paste client data into public tools because nobody said not to. Others miss out on genuine productivity gains because they fear looking lazy or replaceable. Neither outcome is a technology failure.
The fix is dull and effective: a plain-English AI policy of one page or less. Say which tools are approved, what data must never go in, when AI use should be disclosed to clients, and who to ask when unsure. If your policy needs a lawyer to decode it, your team will ignore it.
Big Tech Gets a Pushback
On the policy side, the ABC reports a crossbench push to give Australians a free way to fight back against big tech. The detail will matter, and it may not pass in its current form, but the direction is clear. Scrutiny of platform behaviour, complaints handling and accountability is increasing, and AI products will be pulled into it.
For marketing and tech teams, this is a reminder that your stack has regulatory exposure. If you rely on a single platform for acquisition, or on an AI vendor for customer-facing decisions, you need to know where your data goes and what recourse you have. Ask vendors direct questions about data handling and keep a record of the answers.
One Smaller Signal Worth Noting
Marketing Week’s roundup of interesting stats pointed to shrinking timelines, rising AI costs and wobbly consumer confidence. The rising cost point deserves more attention than it gets. Many teams adopted AI tools on the assumption that they would be cheap, and usage-based pricing is making budgets harder to predict.
Review what you are paying for each quarter. Cancel overlapping tools, and ask whether anyone has actually used the licences you bought.
Keiran’s Take: Boring Beats Loud
I would skip the “top 10 AI tools” lists entirely. Most are recycled, some are years old, and none know your business. The real signal this fortnight is that ambition is running well ahead of execution, and that is where Sydney teams will win or lose.
My suggestion is to make one practical move in three parts. First, audit how your brand appears in AI answers. Second, write a plain-English internal AI policy and circulate it. Third, be deliberate about who you hire next.
On hiring, the people I would prioritise in 2026 are the ones who bridge strategy and execution. That means a marketer who can turn an AI visibility finding into a content plan and measure it, or an engineer who can explain a trade-off to a commercial director without jargon. These people are scarce, and SEEK and LinkedIn data both show employers competing hard for anyone with demonstrated, applied AI experience rather than a certificate or a buzzword on a CV.
When you interview, ask candidates to describe an AI project that failed or was scaled back, and what they learned. Good operators answer that easily. Hype merchants do not.
Disciplined, unglamorous adoption will beat loud transformation. Chaney understands that, and I suspect the teams still standing in 2027 will too.
The future is bright, let’s go there together!
Thanks for reading,
Cheers Keiran
Big Wave Digital.
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Keiran Hathorn is the CEO & Founder of Big Wave Digital. A Sydney based niche Digital, Blockchain & Technology recruitment company. Keiran leads a high performance, experienced recruitment team, assisting companies of all sizes secure the best talent.
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