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Four Proptech leaders to take part in AI + Machine Learning Webinar

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Don’t miss the next Proptech Australia Webinar – AI + Machine Learning – as we bring together  four of the foremost leaders in the Proptech industry to discuss the latest technology innovation, adoption rates and emerging opportunities.


Please join our host, Proptech Australia President Kylie Davis, for a 1-hour webinar from 1pm-2pm on July 29 with:.


Damian Merchan - CEO of Sonar AI

Leann Jones – CEO of Nimo Industries

Aonghus Stevens – CEO of Asseti

David Howell – CEO of Dynamic Methods


The panel will discuss a variety of topics, including

  • State of AI and Machine Learning in Australian Proptech:

    • Significant current trends and adoption rates across residential and commercial, and property management.

    • How Australia compares to global leaders in proptech AI adoption. 

    • What are our unique strengths or weaknesses?

  • Emerging Technologies and Trends:

    • What's next for AI/ML in Australian proptech – Generative AI, agentic AI and much more.

  • Human-AI Collaboration:

    • How does AI augment, rather than replace, human expertise in real estate?

    • The importance of human oversight.

  • Investment and Innovation Landscape:

    • Where are the key investment opportunities in Australian proptech AI?

  • Use Cases and Success Stories:

    • How AI is being used for property valuation, market forecasting (rental trends, sales prices), and identifying investment opportunities. 

    • AI-driven solutions, such as tenant experience, predictive maintenance, energy optimisation and automating compliance.

    • Personalised property recommendations, virtual tours, lead generation and automated client communications.

  • Barriers to Adoption:

    • What are the biggest challenges, and how can these barriers can be overcome?

  • Data, Privacy, and Ethics:

    • The critical importance of data quality, quantity and access for effective AI.

    • Navigating data privacy regulations and ensuring compliance when handling sensitive property and personal data.

    • Addressing potential biases in AI algorithms

    • Who owns the data generated by AI tools, and what are the implications?

 
 
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