Applied AI Australia

Ramon Rodriguez

Applied AI Australia is the podcast for Australian executives turning AI into measurable business outcomes. Hosted by Ramon Rodriguez - an executive, not a career consultant. This show cuts through AI hype to focus on what matters: Growth and Margins. Now part of Acquire Intelligence, the podcast brings commercially grounded AI strategy and practical executive insight to CEOs, CIOs,CFOs, boards, and senior operators navigating rapid change and competitive pressure. Each week, Applied AI Australia delivers real-world conversations, operator perspectives, and practical frameworks leaders can apply quickly , often within 48 hours. This is not a tech podcast. It is practical AI leadership for executives accountable for results. Subscribe.

  1. 14h ago

    Does AI Always Mean Fewer People? How CEOs Move Teams Into Higher-Value Work | Emma Fawcett, CEO Compare Club

    Does AI always mean fewer people? In some parts of a business, it can. The leadership challenge begins when AI removes, compresses or changes existing work. Leaders need to decide what stops, where the capacity goes, what higher-value work replaces it and what standard the team must now meet. In this episode of Applied AI Australia, powered by Acquire Intelligence, Ramon Rodriguez speaks with Emma Fawcett, CEO of Compare Club, about leading that shift across a real business. AI does not make people less important. It makes the right people, the right culture and the right work more important. Emma draws on her experience, including leading MYOB’s largest division, where one million customers generated four million calls a year and waited up to 40 minutes for support. Before approving an eight-figure technology program, Emma’s team stepped back to understand why customers were calling. They found that around 20% of calls came from customers who could not understand their bill. By fixing those root causes before investing in new technology, the team cut call volume by roughly half. The business later reached 86% digital service and lifted customer satisfaction by around 20 percentage points. At Compare Club, the same discipline underpins the Make Work Better program. The business has identified 135 potential AI use cases, with each required to define the problem, expected return and where the freed capacity will go. The results include: • Board reporting reduced from nine days to two• A monthly finance task reduced from 39 hours to around 25 minutes• A recruitment tool that narrowed 400 applications to 30 for human review Each example shows what happens when leaders treat saved time as capacity to be deliberately redirected, rather than the final result. What you’ll learn • Why AI programs stall when leaders begin with the tool• What the right team looks like in an AI-enabled business• Why emotional intelligence, curiosity and adaptability matter• How to raise standards without creating fear• Why saved time is not value until leaders decide where the capacity goes• How to communicate changing roles and higher-value work honestly Your 48-hour action Choose one AI initiative already being discussed and ask: What low-value work does this remove? Where will the freed capacity go? What higher-value work should people do instead? What capability must the team build next? How will we explain the shift in a way that builds trust rather than fear? If the leadership team cannot answer those questions, the initiative is not ready to scale. Chapters • 00:00 Outcomes before technology• 00:16 Welcome and guest introduction• 01:10 Why AI starts in the wrong place• 02:18 Four million calls and the eight-figure trap• 08:58 EQ over IQ in the AI era• 15:17 Who owns AI and Make Work Better• 17:35 Nine days to two, 39 hours to 25 minutes• 20:22 Cathy Bot and 135 AI use cases• 29:38 Reducing 400 CVs to 30• 35:50 Leading people through AI change• 38:51 Moving people into higher-value work• 46:40 From channel chaos to 86% digital service• 49:57 Stop the Work and the 70/20/10 model• 56:38 Put AI on the calendar• 1:00:03 Where to find Emma and Compare Club• 1:01:09 Final takeaways About Applied AI Australia Applied AI Australia is powered by Acquire Intelligence. We help Australian companies turn AI investment into measurable business value. We help you, decide what to fund, what work must change, where value should land and who owns the result. Get in touch - https://www.appliedaiaustralia.com.au/book-briefing Ramon: linkedin.com/in/ramonrodGuest: Emma Fawcett, CEO of Compare Club

    Does AI Always Mean Fewer People? How CEOs Move Teams Into Higher-Value Work | Emma Fawcett, CEO Compare Club

  2. Jul 20

    Fast Tech, Slow Org: The AI Execution Gap | Salesforce SVP & CMO ANZ Leandro Perez

    Fast Tech, Slow Org: The AI Execution Gap | Salesforce SVP & CMO ANZ Leandro Perez Subscribe if your leadership team is investing in AI but still cannot clearly explain what work has changed. AI progress is easy to perform. Pilots launch. Platforms get bought. Agents get tested. Boards receive updates. Value is harder. It shows up when workflows change, ownership is clear, metrics move, customers get a better outcome, and the organisation knows what the agent is allowed to do. That is the AI execution gap. In this episode of Applied AI Australia, powered by Acquire Intelligence, Ramon Rodriguez speaks with Leandro Perez, SVP & CMO ANZ at Salesforce, about what has to change before AI capability becomes business value. The conversation goes past tools and into the operating reality: agents need owners, metrics, supervision, escalation paths, business context, clean data and better work design. Leandro also raises one of the sharper leadership shifts: this may be the last generation of managers who only manage people. As agents enter workflows, leaders will need to manage both people and AI systems. The core message: The tool is not the transformation. The proof is whether the work changed. What you’ll learn: Why AI pilots, tools and training do not automatically create business valueWhat changes when AI moves from answering questions to acting inside workflowsWhy agents need owners, metrics, supervision and escalation pathsHow poor data and weak context limit AI performanceWhy customer service, sales and marketing metrics need to changeWhat leaders should ask before scaling AI agentsKey stats and examples: 76% of Australian service leaders are looking at or using AI56% of employees are using personal AI tools without disclosing itSalesforce says 84% of cases are now handled autonomously in one support use caseMore than 2.2 million cases have been deflected through Salesforce’s support agentSalesforce has more than 300 agents operating internallyOne prospecting agent had to be slowed down after following up outside normal business expectations 48-hour action: Pick one AI agent, pilot or workflow and ask: What work has changed?Who owns the outcome?What metric proves value?What authority does the agent have?Where does a human step in?What outcome has improved?What needs to change before this scales?If you cannot answer those questions, you may be scaling AI activity, not AI value. “Treat agents like an employee. You don’t just hire someone and leave them in the corner.” - Leandro Perez Chapters: Fast tech, slow orgAI activity versus AI progressWhy AI pilots fail to become valueWhy personal AI does not equal enterprise AISalesforce’s internal agent lessonsWhy business experts need to manage agentsData, privacy and guardrailsWho owns an agent when it goes wrong?How to set success metrics for agentsWhy AI changes old performance metricsWhat leaders should do next About Applied AI Australia: Applied AI Australia is powered by Acquire Intelligence. We help Australian companies turn AI into revenue, margin, time back, and better operating discipline. Need immediate execution support? From 10 December 2026, APP 1.7 requires organisations using automated systems to make, or substantially influence, decisions about individuals to disclose that fact in their privacy policy. Serious or repeated privacy interferences can carry penalties up to $50 million. If your AI agents, scoring tools, triage systems or automated workflows touch customer decisions, you need a decision map before you can know what must be disclosed. Acquire Intelligence runs six-week, governance-led sprints to build compliant decision maps from scratch before enforcement arrives. Websites: www.appliedaiaustralia.com.auwww.acquireintelligence.ai Ramon:linkedin.com/in/ramonrod Guest: Leandro PerezSVP & CMO ANZ, Salesforcelinkedin.com/in/leandro-perez

    Fast Tech, Slow Org: The AI Execution Gap | Salesforce SVP & CMO ANZ Leandro Perez

  3. Jul 2

    10 December 2026: The AI Decision Deadline Executives Can’t Ignore

    10 December 2026: The AI Decision Deadline Executives Can’t Ignore From 10 December 2026, Australian organisations covered by the Privacy Act face new automated decision-making disclosure obligations under APP 1.7. If AI, automation, scoring tools, workflow engines or legacy SaaS platforms help make decisions about customers, employees or applicants, executives need to know where those decisions happen and whether they are disclosed. This episode gives leaders a practical way to find the gap before the deadline. Map The Decisions Before You Rewrite The Policy Many organisations can list their AI tools. Fewer can show every automated or AI-assisted decision those tools shape. That is the exposure. APP 1.7 makes automated decision-making a privacy policy issue. But the real work starts earlier. Executives need a decision inventory. Send One Email To Expose The Gap Send this to your General Counsel: “Can you show me the current map of every automated or AI-assisted decision that affects customers, employees or applicants, and confirm which of those decisions are already disclosed in our privacy policy?” A clear answer means the organisation has visibility. An unclear answer means the organisation has mapping work to do. Challenge The Three False Comforts This episode breaks down three assumptions that can leave executives exposed: * Vendor contracts do not replace internal accountability. * Human approval does not always remove automated decision-making risk. * Older automation can still be caught by technology-neutral rules. Build The Decision Inventory From Outcomes The practical fix starts with the people affected by the decision. Start with customer, employee and applicant outcomes. Then work backwards to the systems, data, vendors, workflows and approvals that shape those outcomes. That is how leaders find the decisions that a tool register misses. What You’ll Learn * Why 10 December 2026 matters for Australian executives using AI and automation * What APP 1.7 changes under the Privacy Act * Why automated decision-making is broader than generative AI * How to test whether your organisation has a decision inventory * Why vendor contracts and human review may not be enough * How old SaaS platforms and scoring tools can still create disclosure obligations * How to map automated decisions from customer outcomes backwards * Why larger organisations may need 8 to 16 weeks to build a usable decision map Timestamps 0:00 — The boardroom story 0:54 — Welcome to Applied AI Australia 1:09 — APP 1.7 and the new disclosure rule 1:42 — What executives need to know 2:14 — Send this email to your GC 3:55 — Why the answer may be unclear 4:31 — Build a decision map, not just a vendor list 6:52 — Test vendor accountability 8:27 — Test human-in-the-loop approvals 11:50 — Test legacy automation 14:00 — Understand the penalty exposure 15:28 — Start with customer outcomes About Applied AI Australia Applied AI Australia helps executives turn AI complexity into business outcomes: growth, margin, time back and better operating discipline. Each week, Ramon Rodriguez breaks down the AI shifts that matter for Australian leaders, boards and executive teams, so they can stay clear, current and in control with AI. Need Execution Support? Acquire Intelligence runs governance-led sprints to help organisations identify, map and manage automated and AI-assisted decisions before the 10 December 2026 deadline. Visit Acquire Intelligence to close the gap. 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.

  4. Jun 29

    Season 3 Launch: Weekly AI Conversations for Leaders

    Season 3 of Applied AI Australia starts now - with new episodes every week. In this short update, Ramon shares the next chapter for the show, including Applied AI Australia joining Acquire Intelligence and a sharper focus on helping Australian leaders stay clear, current and in control with AI. Expect weekly executive conversations with leaders from Salesforce, Workday, Finder, Compare Club and other Australian businesses making real decisions about AI, strategy, risk, work, growth and governance. The goal is simple: turn AI complexity into practical business outcomes, with conversations and advice leaders can take into Monday morning. Follow the show and share it with a leader who needs it.

  5. May 27

    Machine Customers Are Here. Your Business Was Built for Humans | Katja Forbes

    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 receptorWhy Salesforce just removed the human UI layer entirely and rearchitected its platform for AI agents as the primary actorsThe shift from KYC to KYA: what agent verification looks like and why American Express is now covering losses from registered agent errorsHow Kyriba's agentic AI is already executing autonomous FX transactions inside a $208 trillion cross-border payments flowWhat went wrong when an AI agent was given $100K and told to open a retail storeKey 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 trillion01:00 - Adobe: 4,700% AI agent traffic increase05:00 - The five types of machine customer09:00 - Amazon Rufus, Woolworths Olive, and the neutrality problem13:00 - Salesforce goes headless15:00 - Receptors: why each type needs a different customer journey19:00 - From KYC to KYA: agent verification and privacy22:00 - Ramon's own machine commerce misfire26:00 - The $208T cross-border FX opportunity31:00 - Luna's $100K autonomous business experiment33:00 - Anthropic: Opus vs Haiku trading outcomes36:00 - Your 48-hour action38:00 - Closewww.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.

    Machine Customers Are Here. Your Business Was Built for Humans | Katja Forbes

  6. May 3

    The AI Identity Risk Your Board Can’t See | Okta SVP & GM Dan Mountstephen

    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: 0:00 - 82 machines per human1:00 - CBA: $1B fraud, $900M response3:00 - AI scales weaknesses, doesn’t create them5:00 - 212% YoY cybercrime growth5:10 - 86% using unsanctioned AI6:00 - What good cyber looks like7:00 - Identity Security Posture Management8:00 - Directors personally on the hook10:00 - Static API keys = standing privilege12:00 - Kill chain: identity to damage13:00 - Agents as contractors: the ownership model16:00 - Dell case study18:00 - Where to start: visibility first19:00 - 48-hour action20:15 - Blast radius and kill switch22:00 - 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.

    The AI Identity Risk Your Board Can’t See | Okta SVP & GM Dan Mountstephen

  7. Apr 1

    60% Fewer People, 90% Faster: The Vacancy Strategy (Diego Mogollon, VentureCrowd)

    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: what can an agent handlewho can upskill into this,what process can we redesignHe 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 adoptionThe Customer Zero strategy: build AI agents for your team before your customersHow a crew of specialised AI agents replaced a marketing team of six in a regulated FinTechAgent KPIs most companies aren't tracking: resolution rates, escalation rates, latency, and context poisoningWhy giving agents more data makes them worse, not betterThe shift from human in the loop to human at the helmHow to run a 24-hour agent challenge with your team this weekKey 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 yearsDevelopment time down 90% (months to weeks, weeks to days)Marketing team: 6 people to 1$440M raised through VentureCrowd's digital platformBug debugging time cut 90%+ with a single agent48-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

    60% Fewer People, 90% Faster: The Vacancy Strategy (Diego Mogollon, VentureCrowd)

  8. Mar 19

    AI Ready in 2026 - Part 2 (Anthony Mittelmark)

    $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 stallThe four levels of AI usage maturity (Tool User to AI-First) and where most companies are stuckThe second maturity track nobody measures: organisational readinessWhy tactical AI integration can make the rest of the business worseHow a multinational used upstream data IP to change their valuation narrativeA 48-hour brutal audit you can run with your leadership team this weekKey Frameworks: Two-Track TrapTrack 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 it48 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 spot1:00 -Why AI programs stall: IT projects vs portfolio mindset5:00 - The four levels of AI usage maturity8:30 - The Two-Track Trap: organisational readiness11:30 - What happens when leadership can't articulate why14:30 - Level 3 usage, Level 1 organisation17:30 - The $500M CEO building a business within her business19:00 - Upstream data IP and valuation narrative21:30 - Does this project advance your AI thesis?23:00 - The brutal audit25:30 - Close: AI maturity runs on two tracksPart 1 (Believer, Driver, Builder): Here Applied AI Australia: https://appliedaiaustralia.com.auhttps://www.linkedin.com/in/ramonrodPodcast + 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 - Part 2 (Anthony Mittelmark)
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About

Applied AI Australia is the podcast for Australian executives turning AI into measurable business outcomes. Hosted by Ramon Rodriguez - an executive, not a career consultant. This show cuts through AI hype to focus on what matters: Growth and Margins. Now part of Acquire Intelligence, the podcast brings commercially grounded AI strategy and practical executive insight to CEOs, CIOs,CFOs, boards, and senior operators navigating rapid change and competitive pressure. Each week, Applied AI Australia delivers real-world conversations, operator perspectives, and practical frameworks leaders can apply quickly , often within 48 hours. This is not a tech podcast. It is practical AI leadership for executives accountable for results. Subscribe.

Information

  • Creator
    Ramon Rodriguez
  • Years Active
    2025 - 2026
  • Episodes
    21
  • Rating
    Clean
  • Copyright
    © Ramon Rodriguez
  • Show Website
    Applied AI Australia

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