In this presentation, Nic Hohn Chief Data Scientist at QuantumBlack, discusses the importance of generative AI and how organisations can harness its potential.

He begins by emphasising the rapid evolution of generative AI and its potential for significant impact in various industries. Additionally, Nic highlights the importance of a clear strategy, capabilities, talent, and operating models to effectively implement generative AI.

Nic introduces the concept of being a ‘taker’, ‘shaper’, or ‘maker’ in the context of generative AI adoption. He explains that organisations can choose their level of involvement, from simply using pre-existing models (taker) to fine-tuning existing models (shaper) or building their own models from scratch (maker).

The presentation also underscores the significance of data quality and subject matter expertise in training and evaluating generative AI models. Furthermore, Nic advises organisations to be cautious about the licensing restrictions associated with different generative AI models.

The need for human feedback and oversight in conjunction with generative AI is crucial to ensure that it delivers useful results, suggesting that organisations should implement feedback mechanisms early in their AI projects.


Key Takeaways:

  • Generative AI offers significant potential impact across various industries, including sales and marketing, software engineering, customer operations, and research and development.
  • To harness the power of generative AI, organisations should start with a clear strategy that focuses on value creation, ensure senior business sponsorship, and consider whether they should be takers, shapers, or makers of generative AI models.
  • Data management, subject matter expertise, and feedback mechanisms are crucial components in successfully implementing generative AI while striking a balance between automation and human oversight. Licensing considerations for AI models should also be carefully evaluated.
Nic Hohn Nic Hohn
Nic is a distinguished Data Scientist at McKinsey & Company in Melbourne and the Chief Data Scientist for QuantumBlack Australia. He leads... More

Nic is a distinguished Data Scientist at McKinsey & Company in Melbourne and the Chief Data Scientist for QuantumBlack Australia.

He leads data science teams to extract actionable insights from data in a pragmatic and responsible way across a range of fields, including telecommunications, IoT and financial services.

Nic has more than 15 years of post-PhD experience in research, development and commercialisation of product innovation in big data analytics and predictive modelling. His areas of expertise include: data science, machine learning, analytics transformation programs, MLOps and ethics in AI.

Prior to joining McKinsey, Nic led data science at Dun & Bradstreet and analytics at a Big Data start-up in the US.