Part 2 of our practical innovation tool. Discover how to innovate in IT successfully.
Uncover the secrets to successful machine learning (ML) projects in enterprises, from avoiding common pitfalls to driving significant business value.
After nearly two years of hype, speculation, use case analysis, pilots, and scaling deployments, generative artificial intelligence in the enterprise has some results to show for the multi-billion dollar investments made by the big tech vendors. Explore success stories and key lessons from Australian enterprises.
ICT policies often leave even seasoned executives uneasy, perceived as lengthy, endless compliance exercises yielding little reward beyond periodic reviews.
Generative artificial intelligence (AI) has delivered significant return on investment (ROI) for software development teams and is recognised as more of an opportunity than a threat. With big tech and venture capital firms continuing to invest in AI-assisted software development tools, this trend is going to accelerate. However, concerns around IP and security are not yet fully resolved.
Generative (gen) artificial intelligence (AI) risks span data, model, deployment, and governance dimensions, with different concerns coming to the forefront at each adoption stage.
Unlock the potential of Google’s Vertex AI in revolutionising your ML projects. Explore seamless integration and enhanced efficiency today.
As customer service leaders navigate the rapidly evolving technological landscape of artificial intelligence (AI), it is crucial to reassess the entire customer journey, and strike the right balance between digitised efficiency and personalised responsiveness at scale.
To present AI effectively to the board, emphasise its role in augmenting rather than replacing existing capabilities.
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