The application of all things technology has always been an interest of mine, both professionally and personally. So during Melbourne’s Stage 4 lock down, I decided to embark on some personal development and commenced the MIT Sloan Short Course on AI: Implications for Business Strategy.
My interest is not only about the technology, but also about what it means for organisations in terms of business strategy and the resulting impact on the required organisational culture, capability and leadership to truly deliver value through AI. Over the next few weeks, I will briefly summarise what I have learnt and what the implications for organisations may be. What follows is a brief summary of module 1.
- There are a range of definitions of AI but the one that I like, because of its simplicity is “machines acting in intelligent ways”. The very heart of AI is to build a machine that is capable of “thinking”.
- The research is centred on two branches of AI: Narrow AI and General AI.
- Narrow AI applies to machine-based systems designed to solve a specific programs, such as computers being taught to scan patient images, or detection of potential credit card fraud.
- General AI refers to machines with the ability to solve many different types of tasks, just like the human brain, on their own. The reality is that this is decades from true realisation (although AI is progressing very quickly).
- Much of the research and development is centred on the notion of collective intelligence, that is, how to we machines in “partnership” with humans to create collective intelligence. That is that we use what each one does best. What roles should a machine do and what tasks should people do? In other words, let the computers do what they can do better than people and vice versa. For example, computers are better and processing and remembering vast amounts of information and people are better at interacting with other people.
- Porter’s framework for how organisations gain competitive advantage is a way to align the application of AI to the overall strategy (cost leadership, differentiation or focus).
- Some really great examples are:
- Insurance – Lemonade are creating competitive advantage and using AI to increase the customer experience and reduce the time taken to approve claims (differentiation strategy)
- KLM – AI is used in customer service to respond to the rapid increase of customer enquiries from social media. Competitive advantage is created by improving the customer experience to respond quickly to customer enquiries (differentiation strategy with delivery of cost savings)
- Cogito – An AI application provides feedback to customer services representatives on their last call with a customer, looking at the effectiveness of their interaction. The feedback is provided in a non-judgemental way to representatives to remove bias and improve the quality of every interaction (differentiation through improved customer experience)
- As an application of AI that I believe will really change the way we deliver services in the aged care and disability sectors (differentiation through improved client outcomes) is MiiCare where the AI collects data on an individual to predict health issues, for example falls.
By considering the range of examples that already exist, and more broadly considering the business strategy adopted in the organisation, it is apparent that the range of opportunities are immense and the rate at which organisations will look to introduce AI can only increase. Just look at the way that many businesses have had to adapt to digital technologies during this pandemic. I believe this has given individuals and organisations confidence that people can change their mindsets and adapt to new ways of working, much more rapidly than we once all thought. There is no doubt, this is enabled by new organisational capabilities, especially in terms of leadership and data analytics.
Bruce McCowan, Partner Performance