Your Vendor Contract Won't Save You: Australia's AI Disclosure Deadline Is December 10 | APP 1.7

⚠️ LEGAL & SCOPE DISCLAIMER: This episode provides commercial and operational strategy only. It does not constitute formal legal advice. Your obligations under the Privacy Act depend on your specific circumstances. You must obtain independent advice from your General Counsel or external legal team to settle your compliance posture and privacy policy wording.

Subscribe: If your board thinks vendor contracts or a "human-in-the-loop" protects you from the upcoming Privacy Act changes, this episode is your briefing.

A client walked into the boardroom with 27 AI products sitting on their risk register. The general counsel asked one simple question: Which of those 27 products are making decisions about our customers?

Nobody in that room knew the answer.

Going in, they figured the real number was probably five or seven. After mapping the decisions properly, they walked out with nearly 30 automated decision points shaping real customer outcomes, and not a single one had been disclosed.

From 10 December 2026, that silence is an active legal liability in Australia. APP 1.7 under the Privacy Act requires every organisation using automated systems to make or substantially influence decisions about individuals to publicly disclose that fact.

The Office of the Australian Information Commissioner (OAIC) is already reviewing 60 companies' privacy policies in a dress rehearsal sweep. With a ceiling penalty of $50 million, this is no longer a theoretical risk.This episode is Ramon's detailed playbook to close this critical compliance gap before the deadline hits.

What you'll learn:

The One-Sentence Email: The exact wording to send to your GC today to instantly expose where your organisation stands.

The 3 Boardroom Myths: Why vendor contracts, human-in-the-loop approvals, and "legacy automation" won't protect you from liability.

The Technology-Neutral Test: Why a 15-year-old SaaS scoring platform carries the exact same disclosure requirement as a brand-new generative AI model.

The 4-Step Decision Mapping Process: How to work backward from customer outcomes rather than tool lists to uncover exposure.

$50 Million: The ceiling penalty for serious or repeated privacy interferences under the new framework.

1 in 3: The number of AI vendor contracts that actually offer intellectual property indemnification if something goes wrong (Stanford CodeX & TermScout data).

8 to 16 Weeks: The realistic timeline for an enterprise (50M–2B revenue) to build a compliant decision map.

48-hour action

"The law is technology-neutral. It doesn't ask what you call the tool. It asks what the tool does. If it touches personal information, and it shapes a real decision about a person, it's in scope." Ramon

Timestamps:

• 0:00 — Intro: The Boardroom Story
• 0:54 — Welcome to Applied AI Australia
• 1:09 — The New Rule: APP 1.7
• 1:42 — What We'll Cover Today
• 2:14 — Action: Send This Email Today
• 3:55 — Why Your GC Will Struggle to Answer
• 4:31 — Vendor List vs Decision Map
• 6:52 — Myth 1: Our Vendor Handles It
• 8:27 — Myth 2: The Human in the Loop
• 11:50 — Myth 3: It's Just Automation
• 13:60 — The Penalties at Stake
• 15:28 — How to Fix It: Start With Customer Outcomes
• 20:04 — Closing & Call to Action

About Applied AI Australia: We help Australian companies between $100M and $1B turn AI into revenue, margin, time back, and better operating discipline. One podcast and one newsletter each week, built so you can brief a board in under an hour.

Need immediate execution support? Acquire Intelligence runs six-week, governance-led sprints to build compliant decision maps from scratch before enforcement arrives.

Reach out at www.acquireintelligence.ai to close your gap.

Machine Customers Are Here. Your Business Was Built for Humans | Katja Forbes, Author of The Machine Customers.

Subscribe: If your board is talking AI strategy but nobody has raised machine customers, this episode is the briefing.

Your Next Customer Won't Be Human: 5 Machine Buyer Types Hitting Australian Commerce.

Adobe reported a 4,700% year-on-year increase in AI agent traffic to retail websites. That is not a forecast. That already happened.

Your commerce channels, your checkout, your fraud stack, your entire customer journey were built for humans. There are five distinct types of non-human buyer already trying to transact in the Australian economy, and most mid-market businesses are blocking revenue they do not even know is walking in.

Katja Forbes is a executive director at Standard Chartered's corporate and investment bank, AFR 100 Women of Influence, and author of The Machine Customers. She has been mapping the taxonomy of machine buyers since before most boards acknowledged the category existed.

If your board's AI strategy does not account for the fact that your next customer might not be human, it has a gap.

What you'll learn:

• The five machine customer types already in market: co-buyer, delegated agent, autonomous buyer, multi-agent network, intermediary broker, and why each one needs a different receptor
• Why Salesforce just removed the human UI layer entirely and rearchitected its platform for AI agents as the primary actors
• The shift from KYC to KYA: what agent verification looks like and why American Express is now covering losses from registered agent errors
• How Kyriba's agentic AI is already executing autonomous FX transactions inside a $208 trillion cross-border payments flow
• What went wrong when an AI agent was given $100K and told to open a retail store

Key stats:

• 4,700% YoY increase in AI agent traffic to retail websites (Adobe).
• $30 trillion machine customer economy forecast by 2030 (Gartner).
• $208 trillion in cross-border payment flows, $625 billion in bank revenue. Banks that build headless receptors for machine customers will amplify that number.

48-hour action: Identify which of the five machine customer types is most likely to arrive at your business first. Check whether your current channels can serve it. Discoverability gets you into the consideration set. Operational trust is the minimum. Values-based differentiation is what makes the agent choose you over the competitor.

"When everyone's discoverable, everyone becomes interchangeable." - Katja Forbes

Timestamps:

• 00:00 - The machine customer economy hits $30 trillion
• 01:00 - Adobe: 4,700% AI agent traffic increase
• 05:00 - The five types of machine customer
• 09:00 - Amazon Rufus, Woolworths Olive, and the neutrality problem
• 13:00 - Salesforce goes headless
• 15:00 - Receptors: why each type needs a different customer journey
• 19:00 - From KYC to KYA: agent verification and privacy
• 22:00 - Ramon's own machine commerce misfire
• 26:00 - The $208T cross-border FX opportunity
• 31:00 - Luna's $100K autonomous business experiment
• 33:00 - Anthropic: Opus vs Haiku trading outcomes
• 36:00 - Your 48-hour action
• 38:00 - Close

www.appliedaiaustralia.com.aulinkedin.com/in/ramonrod

Guest:Katja Forbes, Author of The Machine Customers | AFR 100 Women of Influence | linkedin.com/in/katjaforbes Book: amazon.com/dp/1923630008Machine Customer Canvas (free): thecxevolutionist.ai/resources/machine-customer-canvas

About Applied AI Australia:We help Australian companies between $100M and $1B turn AI into revenue, margin, time back, and better operating discipline. One podcast and one newsletter each week, built so you can brief a board in under an hour.

The AI Risk Your Board Can’t See: Identity, Fraud and AI Agents | Dan Mountstephen, Okta

Subscribe - know a director who still thinks cyber is an IT problem? Forward this.

CBA self-reported $1B in suspected AI-generated fraud this year and committed $900M to fight back.

For every human logging into your systems, there are 82 machine identities. Service accounts, API tokens, AI agents. Most have no owner. Most have more access than the people they serve.

When one of them goes rogue, the board's looking at you.

Dan Mountstephen runs Asia Pacific for Okta, a $3B identity-security business. 20 years in enterprise tech, the last five deep in identity.

The biggest risk in your business isn't the people you hire. It's the accounts you forgot about.

What you'll learn:

• ​The 82:1 ratio: how machine identities outnumber human ones, and why nobody's watching
• ​Why AI isn't breaking new systems. It's scaling the weaknesses you already have.
• ​ How to govern an AI agent the same way you'd govern a contractor
• ​The kill-switch: what to do when an agent goes rogue
• ​Why directors are personally on the hook if due diligence can't be proven

Key stats:

• ​ 82:1 machine to human identity ratio.
• ​ 86% of staff using unsanctioned AI.
• ​ 22% of incidents start with stolen credentials.

48-hour action: Get visibility of every identity across your organisation, human and machine. You can't secure what you can't see.

"AI isn't breaking systems. It's scaling the weaknesses you already have." - Dan Mountstephen

Timestamps:

1. 0:00 - 82 machines per human
2. 1:00 - CBA: $1B fraud, $900M response
3. 3:00 - AI scales weaknesses, doesn’t create them
4. 5:00 - 212% YoY cybercrime growth
5. 5:10 - 86% using unsanctioned AI
6. 6:00 - What good cyber looks like
7. 7:00 - Identity Security Posture Management
8. 8:00 - Directors personally on the hook
9. 10:00 - Static API keys = standing privilege
10. 12:00 - Kill chain: identity to damage
11. 13:00 - Agents as contractors: the ownership model
12. 16:00 - Dell case study
13. 18:00 - Where to start: visibility first
14. 19:00 - 48-hour action
15. 20:15 - Blast radius and kill switch
16. 22:00 - Close

www.appliedaiaustralia.com.au

linkedin.com/in/ramonrod

Guest:

Dan Mountstephen, SVP & GM APAC at Oktalinkedin.com/in/danmountstephen | okta.com

About Applied AI Australia:

We help Australian companies between $100m and $1b turn AI into revenue, margin, time back, and better operating discipline. One podcast and one newsletter each week, built so you can brief a board in under an hour.

Fewer People, More Output: The Vacancy Strategy (Diego Mogollon, VentureCrowd)

Subscribe: Know a leader still hiring the same org chart? Forward this.

You can drive AI transformation in compliance heavy industry! This episode proves it!

Diego Mogollon wears two hats at VentureCrowd: CMO and CTO. The regulated FinTech platform has raised $440 million.

• Over the last two years,
• Tech team shrank 60%.
• Development time dropped 90%.
• Marketing team went from six people to one, and they're handling more volume than ever before.

He didn't fire anyone. His team kept getting poached because they were good. Each time someone left, instead of opening a job req, Diego mapped every task that person owned and asked three questions:

1. what can an agent handle
2. who can upskill into this,
3. what process can we redesign

He calls it the Vacancy Strategy, it's changed everything about how VentureCrowd builds.

What you'll learn:

• Why backfilling roles the traditional way is the biggest missed opportunity in AI adoption
• The Customer Zero strategy: build AI agents for your team before your customers
• How a crew of specialised AI agents replaced a marketing team of six in a regulated FinTech
• Agent KPIs most companies aren't tracking: resolution rates, escalation rates, latency, and context poisoning
• Why giving agents more data makes them worse, not better
• The shift from human in the loop to human at the helm
• How to run a 24-hour agent challenge with your team this week

Key frameworks:

• Vacancy Strategy: Every time someone leaves, don't backfill. Map. Reassess. Redesign.
• Customer Zero: Build AI for your internal team first. Solve your problems, then your customers'.
• Agent KPIs: Resolution rate, escalation rate, latency, tokens per agent.
• Context Poisoning: An agent should know what it needs to know. You don't dump the company wiki on a new hire's first day.

Key stats:

• Tech team 60% smaller over two years
• Development time down 90% (months to weeks, weeks to days)
• Marketing team: 6 people to 1
• $440M raised through VentureCrowd's digital platform
• Bug debugging time cut 90%+ with a single agent

48-hour action: Next time a role opens on your team, hold the job req for 48 hours. Map every task that person did. Identify one that an agent could handle. You'll find it.

Guest: Diego Mogollon, CMO/CTO at VentureCrowd

LinkedIn: linkedin.com/in/diegomogollon

Company: venturecrowd.com.au

Host: Ramon Rodriguez

LinkedIn: linkedin.com/in/ramonrodriguez

Website: www.appliedaiaustralia.com.au

$28M Spent on AI. One Question Tells You If It's Working.

Subscribe - Know a CFO still measuring AI by project count? Forward this.

Episode Summary:

90% of Australian companies have invested in AI. Only 40% are seeing results. The problem isn't the technology.

In Part 1, we showed you which type of AI leader you are: Believer, Driver, or Builder. In Part 2, we reveal why that's only half the picture. There are two tracks of AI maturity and most organisations only measure one. Anthony Mittelmark calls it the Two-Track Trap: your AI usage might be advancing, but if your organisation isn't built to carry it, the investment leaks value.

This episode gives you diagnostic questions most leadership teams can't answer, a real case study of how one multinational reframed AI as a valuation play, and a 48-hour action you can run this week without budget or approval.

What you will learn:

• Why treating AI projects like IT projects is the #1 reason programs stall
• The four levels of AI usage maturity (Tool User to AI-First) and where most companies are stuck
• The second maturity track nobody measures: organisational readiness
• Why tactical AI integration can make the rest of the business worse
• How a multinational used upstream data IP to change their valuation narrative
• A 48-hour brutal audit you can run with your leadership team this week

Key Frameworks:

Two-Track Trap
Track A: AI Usage Maturity (Tool User > Process Runner > Commercial Operator > AI-First)
Track B: Organisational Maturity (leadership articulation, business resistance, architecture to roadmap)
Most companies measure Track A and ignore Track B. That's where investment leaks.

Portfolio Mindset: Every AI project must deliver commercial value, build reusable capability, and advance organisational AI fluency.

Valuation Reframe: Not "what does your org look like in 2030" but "how will it be valued in 2030?"

Key Stats:

• 12% of Australian leaders say GenAI is transforming their business (vs 25% globally)
• 90% invested in AI, only 40% seeing results (Frontier, March 2026)
• Financial services moving to AI-first: cost-to-serve gap makes it impossible to compete without it

48 Hour Challenge:

Ramon: 30 mins. One page. Can leadership articulate why you're investing in AI (commercial reasons, not efficiencies)? Is the business resisting - where and who? What does next-gen CX look like? Does tech map AI architecture to a roadmap with cost-benefit? For every AI initiative, does the org support it or is tech running ahead? If you can't answer with confidence, there's a gap.

Anthony: List every AI tool, subscription, pilot, and POC. Portfolio strategy or just a collection of stuff? CEO to CFO: are we aligned on AI investment and what's the return?

"The board doesn't need another AI update. They need a name to it next quarter."

Timestamps

• 0:00 - Intro: the two-track blind spot
• 1:00 -Why AI programs stall: IT projects vs portfolio mindset
• 5:00 - The four levels of AI usage maturity
• 8:30 - The Two-Track Trap: organisational readiness
• 11:30 - What happens when leadership can't articulate why
• 14:30 - Level 3 usage, Level 1 organisation
• 17:30 - The $500M CEO building a business within her business
• 19:00 - Upstream data IP and valuation narrative
• 21:30 - Does this project advance your AI thesis?
• 23:00 - The brutal audit
• 25:30 - Close: AI maturity runs on two tracks

Part 1 (Believer, Driver, Builder): Here

Applied AI Australia:

• https://appliedaiaustralia.com.au
• https://www.linkedin.com/in/ramonrod
• Podcast + Executive Newsletter

Guest:

Anthony Mittelmark, 20+ years AI strategy across ASX 100 companies and high-growth ventures..

• LinkedIn: linkedin.com/in/anthonymittelmark

AI Ready in 2026: Know Your Type (Part 1)

Applied AI Australia

In Conversation With: Anthony Mittelmark. Technology executive with 20+ years delivering enterprise-scale AI strategy and digital transformation across ASX 100 companies and high-growth ventures.

Duration: ~28 minutes

EPISODE SUMMARY

Every Australian executive falls into one of three AI leadership categories. The problem: most think they're a different type to what they actually are.

Ramon Rodriguez and Anthony Mittelmark unpack the Believer, the Driver, and the Builder using real data from KPMG, Deloitte, and MIT. Part 1 is diagnosis.

Part 2 covers what to do about it.

THE 3 TYPES

Type 1: The Believer

Well read, forwarding articles to leadership, but hasn't committed to a first commercial move. The risk of being wrong feels bigger than the risk of waiting. That's a false trade-off. Every quarter at Level 1 widens the gap.

Type 2: The Driver

Committed, shipping results, capital deployed, reorgs done. But running from fear of being caught flat-footed. The tension between AI's 9-18 month value curve and 6-month ASX reporting cycles pushes Drivers toward highly visible, low-impact tools over structural redesign.

Type 3: The Builder

Budget, pilots, task force, enthusiasm. Missing the commercial thread. Has AI champions but no AI owners. The champion raises their hand. The owner answers to the board when it fails.

KEY DATA

• 63% of Australian C-suite rank AI as chief concern for 2026 (KPMG)
• 12% of Australian leaders report AI is actively transforming their business, vs 25% globally (Deloitte)
• 28% of Australian organisations have moved 40%+ of AI pilots to production (Deloitte)
• 95% of enterprise gen AI pilots fail to deliver measurable impact (MIT)

THE EXECUTIVE LANGUAGE DECODER

• "Exploring AI opportunities" = We haven't committed to anything
• "Piloting in one department" = We don't know if it works yet
• "Monitoring the landscape" = We're waiting for someone else to go first
• "Developing our AI strategy" = We don't have one
• "AI-augmented workflows" = We added a chatbot
• "Responsible AI approach" = We're using compliance as a brake

YOUR 48-HOUR FIRST MOVE

Believers: Map your category against a 20% margin compression scenario. One page. This week. Have the conversation.

Drivers: Ask your leadership team: where are we still making decisions the same way we did three years ago? Find it before a competitor does.

Builders: Name one AI initiative running right now and put a strict dollar figure on it. Savings or revenue. If you can't do this by Friday, pause the build.

TIMESTAMPS

00:00 Introduction and episode framing

01:07 The Australian AI readiness gap in numbers

03:11 The 3 types of AI leader: overview

03:37 Type 1: The Believer

09:26 Believer self-diagnosis questions

11:00 Type 2: The Driver

12:42 Tactical AI vs AI-first

16:09 Type 3: The Builder

22:00 The Executive Language Decoder

23:56 Traditional frameworks vs probabilistic technology

26:08 Your 48-hour first move

27:20 Closing and Part 2 preview

LINKS

Website: www.appliedaiaustralia.com.au

Executive Newsletter: https://substack.com/@appliedaiaustralia

Ramon Rodriguez: https://www.linkedin.com/in/ramonrod

Anthony Mittelmark: https://www.linkedin.com/in/anthonymittelmark/

SUBSCRIBE TO APPLIED AI AUSTRALIA

The #1 source for Applied AI strategy for the Australian C-Suite. Frameworks you can apply in 48 hours..

ABOUT APPLIED AI AUSTRALIA

Applied AI Australia helps execs cut through the noise and deliver practical outcomes: growth, margins, and time. We translate AI into executive action every Monday and Friday.

Tasks tell you what happened. Decisions explain the outcome. If you aren't capturing the logic behind your decisions, your workflow is broken.

90% of Australian executives believe AI is critical for survival, yet only 3% have successfully operationalised it. Why the gap? Because their data is fragmented across too many tools.

In this episode, Andrew McCarthy (GM, Notion APAC) joins us to dismantle the "AI Aspiration Gap." We move beyond the hype to discuss the infrastructure required to turn your company's "Institutional Memory" into a queryable AI asset—and deliver massive operational ROI.

Key Takeaways & ROI:

• The $1M Efficiency Play: How consolidating decision logic saved over $1 million in costs and reduced reporting time from 3.5 days to just 6 hours

• The "Heidi" Case Study: How one workflow change saved 260 hours a month by automating context, not just tasks

• Scaling Decision Logic: A framework for capturing the "why" behind executive decisions so they can be replicated at scale

• The Cost of Tool Sprawl: How fragmented data silos are preventing your AI from generating accurate insights

• Retention as ROI: How reducing workflow friction directly impacts your ability to retain top talent

Timestamps:

• [00:00] Introduction: The disconnect between AI strategy and execution

• [01:49] The state of AI in Australian Enterprise: Why we are "aspirational" but not "operational"

• [02:59] The "Tool Sprawl" Crisis: Why your tech stack is killing your AI potential

• [04:17] Framework: How to consolidate knowledge infrastructure

• [10:24] Case Study: Practical examples of AI reducing operational drag

• [16:47] Leadership Strategy: How to govern AI adoption without stifling inovation

• [35:13] Andrew's forecast for the future of work

Links:

• Connect with Andrew McCarthy on LinkedIn: https://www.linkedin.com/in/awmccarthy/

• Explore Notion for Enterprise: https://www.notion.so/product/enterprise

• Connect with Ramon Rodriguez on LinkedIn: https://www.linkedin.com/in/ramonrod/

SUBSCRIBE TO APPLIED AI AUSTRALIA
The #1 source for Applied AI strategy for the Australian C-Suite. Frameworks you can apply in 48 hours.

📧 Newsletter: HERE

ABOUT APPLIED AI AUSTRALIA
Applied AI Australia helps execs cut through the noise and deliver practical outcomes: growth, margins, and time. We translate AI into executive action every Monday and Friday.

The CTO Trap: Why 80% of AI Pilots Fail | Dawid Naude, Pathfindr

Episode Description: 80% of Australian AI investments are currently failing, costing enterprises north of $28M per failed pilot. The data proves it: this is not a technology problem; it is a leadership failure.

In this episode, Dawid Naude (CEO & Founder, Pathfindr) joins us to dismantle the "CTO Trap"—the dangerous illusion gripping corporate Australia that you can delegate AI strategy to the IT department, a consultant, or a vendor.

You cannot scale what leadership doesn't use, and you cannot govern what leadership doesn't understand. We break down why real transformation must move from "Inbox Sorting" to "Reasoning" and why it must start at the Board level.

What You'll Learn:

• The "CTO Trap": Why assigning AI ownership to the IT department is a P&L risk that leads to "Pilot Purgatory."

• Reasoning vs. Doing: How to move beyond basic automation to leverage the true reasoning capabilities of frontier models for strategic decision-making.

• The $1M PDF Strategy: A practical case study on how simple, non-technical tools can solve complex executive problems and deliver instant ROI.

• Consultant Red Flags: The "PowerPoint Test" to instantly audit if your advisor is a practitioner or just a theorist.

• The 48-Hour Challenge: Three tactical moves you can execute tonight to audit your calendar and your AI readiness.

Timestamps:

• [00:00] The $28M Reality Check: Why 80% of Australian AI pilots never reach production.

• [03:10] Pilot to Production: The governance and cultural friction points killing your ROI.

• [07:20] The "CTO Trap": Why you cannot delegate business transformation to the tech team.

• [09:45] Case Study: How a simple AI workflow saved $1M in logistics costs.

• [13:15] Reasoning Engines: Moving from "Generative" text to "Strategic" thinking.

• [18:40] Vendor Due Diligence: How to spot a "Fake Expert" using the PowerPoint Test.

• [29:30] The 48-Hour Executive Challenge: Immediate steps for the C-Suite.

Links:

• Connect with Dawid Naude on LinkedIn: HERE

• Is your organisation falling into the CTO Trap? Take the 2-minute AI Revenue Scorecard to find your hidden margins and get your personalised risk assessment: [Insert URL]

SUBSCRIBE TO APPLIED AI AUSTRALIA
The #1 source for Applied AI strategy for the Australian C-Suite. Frameworks you can apply in 48 hours.

📧 Newsletter: https://rebrand.ly/9uyuana

ABOUT APPLIED AI AUSTRALIA
Applied AI Australia helps senior leaders cut through the noise and deliver practical outcomes: growth, margins, and time. We translate AI into executive action every Monday and Friday.​

Invested in AI and got no results? You’re not alone - and it’s not the technology. In this episode, Ramon Rodriguez sits down with Brad Granger, Managing Director at Podium, to unpack why Australian executives keep getting burned by AI pilots and how to escape the “Test‑First Trap.”

Brad shares a practical framework and three critical questions every CEO and CFO must ask before approving the next AI project.​

You’ll learn:

• Why AI pilots stall in “Pilot Purgatory” and how to move to real, measurable ROI.​

• The three questions that stop bad AI investments before they start.​

• How to treat AI agents like employees, with onboarding, KPIs, and performance management.​

• How to design AI for both efficiency and growth, instead of trading one off against the other.​

• The data, people, and process foundations that actually make AI work in an Australian enterprise.​

• How to balance automation speed with governance, customer experience, and risk.​

This episode is for CEOs, CFOs, and Australian business leaders who tried AI, were disappointed by pilots, and now want a concrete roadmap to real outcomes.​

Key Takeaways:

• The “Test‑First” Fallacy: Why treating AI like a science experiment guarantees failure, and how to shift to an outcome‑based investment model.​

• The 3 Critical Questions: A simple vetting framework for executives to prevent wasted AI capital.​

• AI as an Employee: How to “hire” AI agents with clear roles, onboarding, KPIs, and accountability.​

• Balancing Control vs Speed: How to automate customer experiences without losing the human touch or governance.​

• [00:00] Introduction: The crisis of stalled AI pilots in Australian enterprises.​

• [00:35] The “Test‑First Trap”: Why your AI pilot was doomed from day one.​

• [03:10] Efficiency vs Growth: Solving the AI ROI equation for executives.​

• [08:45] Executive Framework: The 3 questions to ask before signing off on a pilot.​

• [15:20] The “Hiring” Mindset: Treating AI like a staff member, not a software tool.​

• [22:00] Change Management: Getting your team to adopt, not fight, AI.​

• [28:30] Automation vs Experience: Managing the trade‑offs between speed, control, and CX.​

• [34:00] Action Plan: Immediate steps to rescue your AI strategy and escape Pilot Purgatory.​

Is your business ready to move beyond AI pilots?

Take the 2-minute AI Readiness Scorecard and get your personalised risk assessment: HERE

SUBSCRIBE TO APPLIED AI AUSTRALIA

All you need to know in one place, specifically for Australian Executives and Organisational leaders. Frameworks you can apply in 48 hours.

📧 Newsletter: Here🎙️ Podcast: Subscribe on Apple Podcasts | Spotify |

ABOUT APPLIED AI AUSTRALIAApplied AI Australia helps Australian executives cut through AI noise and implement strategies that deliver real business outcomes. Every week, we translate AI into practical actions for growth, efficiency, and ROI.

Episode Title:
The Death of the Search Bar: Mastering Intent Resolution | Anthony Mittelmark, Ex-PwC Partner

Episode Description:
Australian online retail is a $65B market, but up to $19B of that is now influenced by AI-led curation, not traditional search. If your strategy relies on customers typing keywords into a box, you are optimizing for the past.

In this episode, Anthony Mittelmark (Ex-PwC Partner & Ex-CTO, Fujitsu) joins us to dismantle the traditional "Linear Customer Journey." We explore the rise of Intent Resolution—where AI agents don't just find links, they execute decisions.

We discuss the strategic pivot required for Australian executives: moving from "Traffic Acquisition" (SEO/SEM) to "Utility-Led Value" to survive the age of Agentic AI.

Key Takeaways:

• The $19B Disruption: How AI-led curation is cannibalizing traditional search traffic and what this means for your customer acquisition costs (CAC).

• Intent Resolution: Why the future belongs to brands that can resolve a customer's intent (solve the problem) instantly, rather than just providing information.

• The Rise of AI Agents: Preparing your digital infrastructure for a world where your "customer" is a software bot, not a human.

• Startups vs. Incumbents: Why legacy data structures are preventing ASX leaders from pivoting, and how startups are leveraging "Utility" to steal market share.

Timestamps:
[00:00] The $19B Risk: Why AI is eating search traffic.
[04:15] The Death of the Linear Journey: Moving beyond the funnel.
[09:30] Intent Resolution: The new metric for commercial success.
[15:45] Agentic Markets: When your customer is an AI, not a human.
[24:20] Data Strategy: Why legacy data silos kill AI transformation.
[31:10] Executive Action Plan: How to audit your business for AI readiness

SUBSCRIBE TO APPLIED AI AUSTRALIA
The #1 source for Applied AI strategy for the Australian C-Suite. Frameworks you can apply in 48 hours.

📧 Newsletter: https://rebrand.ly/9uyuana

ABOUT APPLIED AI AUSTRALIA
Applied AI Australia helps senior leaders cut through the noise and deliver practical outcomes: growth, margins, and time. We translate AI into executive action every Monday and Friday.​