No business is free from the risk of disruption, which means all business leaders need to constantly assess whether their current business model will still be relevant in the market in 5-10 years’ time. Therefore, business model innovation should be one of the key tools for company leadership when it comes to considering long term value creation. What artificial intelligence (AI) has to offer for business model development and innovation?
Start small but think big
AI is a complex topic, so it makes sense to start small by improving the existing business with easy-win experiments and applications that address cost efficiencies or add customer value.
That said, horizon thinking is the responsibility of the CEO and Board, and AI is no different. While experimenting with AI in small ways, the leadership team should be working with data scientists and CTOs to imagine how the collection of technologies that makes up AI could be used to identify new markets and revenue streams or even to reinvent the business model altogether. Here are five examples of how AI can help with business model innovation:
1. Become a capacity or performance business
One established approach to business model change is the shift from selling products to selling capacity or performance. The tyre industry, for example, has started moving from tires-as-product to guaranteeing performance.
In this type of business model change, AI provides the means to analyse usage patterns, optimise equipment or asset usage and aggregate and coordinate usage and maintenance across a wide range of different clients. AI also helps to analyse the performance and impact of used machines.
2. Monetise data and related insights
Following the example of tyre manufacturers collecting data from tyre sensors to transform themselves into capacity businesses, business leaders can also start exploring what other insights can be extracted from data and who might benefit from it. For example, data collected via tyre sensors about road conditions is useful for those organisations responsible for highway maintenance seeking to optimise their own operations. Value can also be found beyond the sectors a business operates in, like with harbour data: insights derived from comings and goings of cargo ships provide important indicators for economic development and, as such, can be monetised and sold to analysts and investors.
3. Create data driven business extensions
Rightly or wrongly, AI enables new opportunities for expansion by allowing businesses to leverage what might seem like an unfair advantage. Take the example of electronic invoicing data; AI could potentially assess how quickly customers settle their invoices and use this information to credit score them. With this information, businesses could extend their services to offer additional credit or finance facilities to customers and vary the terms depending on the customer’s credit risk. This approach can be used to drive holistic growth whereby companies are using AI to continuously identify areas where a combination of their own and external data provides them with access to new markets.
4. Enable business model flip
In extreme cases, the insights extracted from data are so valuable that companies are able to heavily subsidise sales of the original product as a means of acquiring more customers and thus more data. In the most extreme examples, the value of the extracted data exceeds sales of the original product. This means the company can decide to give away the original (commodity) product for free just to get access to the maximum amount of data. This approach is the same adopted by digital native companies like Google and Facebook that provide their search engine or social connecting platform for free while monetising the usage via advertising and data sales.
5. Sell knowledge instead of products or services
AI enables new ways to capture and analyse knowledge such as how to use and operate machines. However, it can also be applied in more intangible contexts such as consulting. AI’s knowledge capture ability creates an opportunity for businesses to switch from selling physical products or people’s time to selling knowledge and even wisdom. For example, a state-of-the-art manufacturing plant could use AI systems to white label its knowledge or processes to its competitors in the same sector.
This text is a shorter version of an article published in Boardview magazine 2/2018.
