Keynote2026 · Martech World Forum, Melbourne
Agentic Marketing & Human-in-the-Loop
Opening keynote on the operating model behind autonomous marketing.
Enterprise Transformation · AI Operating Models · Process Architecture
For more than 15 years, Satya Upadhyaya has helped some of Australia's largest organisations modernise their customer engagement, decisioning, data and marketing technology platforms. His focus has since moved to a harder problem: designing the operational architecture that AI-enabled organisations need to function.
Global Enterprise Architect · Personalisation
Head of Campaign Operations
Head of CRM Platforms
Head of CRM · Lifecycle Marketing
Digital Engagement Lead
Analytics & Retention
Analytics & Process
Retention & Process
Customer Engagement · BankingThe Shift
For most of the last 2 decades, enterprise transformation meant implementing systems: choosing the platform, migrating the data, training the teams and measuring adoption. Satya led that work across banking, healthcare, wagering and hospitality, building the CRM, marketing technology, data and decisioning capability that large organisations still run on today.
2004–2011 · The CRM Era
The discipline was getting data into one place and acting on it consistently.
2011–2017 · The Platform Era
The work became rationalisation, integration and governance across complex, multi-brand environments.
2017–2023 · The Personalisation Era
Omni-channel execution meant organisations could finally act on intent at scale.
2023–Present · The Operational Era
The data is largely connected, yet the same friction persists, because the constraint was never only the technology.
In every environment, the same pattern appeared. Organisations kept buying technology, but the real constraint had moved somewhere the software could not reach.
Process design, the coordination of work across teams, and the manual handoffs and delays that sit between a decision and its execution. AI is making those constraints visible. The next phase of transformation will be less about implementing software and more about redesigning how work moves through the organisation.
"Technology implementation is no longer the differentiator. Operational architecture is."
Selected Work
4 recent programmes, each a working system rather than a set of recommendations. Each one takes a recurring operational failure and moves it from human effort into engineered infrastructure.
Complaints arrived through 6 channels into a manual process with no commercial visibility. Guests waited hours, handoffs lost cases, and campaigns kept reaching unresolved guests.
Inbound leads funnelled into one inbox with a person deciding which broker received each. Workable at 20 leads a day, unworkable at 80, and the delay handed warm borrowers to faster competitors.
A 30-person team ran 100–200 campaigns a month with a 30% post-send error rate. The errors started upstream, in ambiguous briefs and misconfigured segments, before any check could catch them.
A customer reaches a decision point online, cannot find the number, switches device, waits on hold, and starts over with an agent. A measurable share give up before they connect.
Track Record
15 years inside large, regulated organisations, as a permanent leader and as an external architect, across financial services, healthcare, wagering, hospitality and membership loyalty.
Head of Platforms for digital, decisioning and channel execution across the retail bank.
Global Enterprise Architect on a 3-year, $8M personalisation roadmap across AU, US and EMEA.
Head of Campaign Operations on a $120M book of work, with error rates reduced from 30% to under 3.
Head of CRM Platforms for customer engagement across 9 business units and $10M in investment decisions.
Head of CRM for lifecycle marketing and personalisation capability in wagering.
Digital engagement lead building connected experience roadmaps for major banking and telecommunications clients.
Foundational analytics, retention and process roles across banking and membership.
Trusted by CIOs, CMOs and CDOs to unify platforms, reset governance and turn customer technology into commercial results.
AI Operating Models
Success with AI rarely comes down to having the most advanced model. It comes down to understanding how the organisation's own work moves, and having the discipline to redesign it for autonomy without losing control.
Most of the work sits away from the algorithm: deciding which steps can run on their own, which ones still need a person in the loop, and how every step stays auditable in a regulated setting.
Responsible-AI principles, bias-audit requirements and audit-trail standards aligned to APRA, ASIC and Privacy Act obligations.
Identifying where autonomous agents add value above the automation layer, and where they do not belong.
The decision gates, escalation paths and approval points that keep autonomy accountable.
End-to-end redesign that removes duplication, cuts manual intervention and creates repeatable patterns for AI to scale against.
The connective layer between platforms, data, APIs and channels, so AI capability is built in rather than bolted on.
Operating models, enablement programmes and standards that raise AI fluency and adoption across the organisation.
Drawn from keynote work at CMO Connect and the Martech World Forum, a published AI-governance whitepaper with Kantar, and agentic-marketing frameworks developed for executive audiences.
Research & Perspectives
Opening keynote on the operating model behind autonomous marketing.
Closing keynote on the architecture beneath real-time decisioning.
On the shift from marketing automation to AI-driven systems.
Practitioner documentation for executive and senior leadership audiences.
Industry whitepaper on AI governance and responsible AI for practitioners.
On why operational architecture, rather than technology, increasingly decides transformation outcomes.
They will have the clearest operational architecture.
Most of the platforms are built and the data is connected. What separates organisations now is whether they understand how their own work moves, and whether they have designed it for what comes next. That is the conversation worth having.
For enterprise leaders looking at AI adoption, operating-model redesign, customer engagement transformation or workflow architecture.