Artificial Intelligence

Defence against Big Tech

Defence against Big Tech

Amazon recently announced its move into the healthcare space through the acquisition of primary care organisation One Medical. It’s a move that is likely to bring a new wave of disruption to the healthcare industry. Amazon specifically mentioned the immense opportunity to make healthcare more affordable, accessible, and enjoyable. When a company that knows more about you than yourself, coupled with their unparalleled logistics and automation capability makes a statement like that, you tend to believe them. This is another example of a new technology-first company that just so happens to operate in a particular industry. Tech companies like this have a strong competitive advantage as they generally have no legacy systems, are data and AI driven from day one and have a strong magnet for talent. So how do you compete against such a force of disruption? Here are three strategies from an AI and data perspective that can help your business play defence. 

#1 Leverage data to move up the value chain 

Shapeways is a 3D printing business founded in 2007 that prints bespoke components in low quantities which are difficult and expensive to make for traditional manufacturing. The business started by allowing customers to send in their CAD files directly to Shapeways for printing. However over time, as 3D printing technology was becoming commoditized, the cost of printing also came down. This lowered the barrier to entry for new competitors and enabled a new market of 3D printing businesses which could compete against Shapeways by being local and offering faster turnaround times. Shapeways thus needed to change its business model. Fortunately for the company, over the years of operation, it had amassed a large dataset of print designs, configuration settings and pricing. The business was able to leverage this data to create a new software-as-a-service offering OTTO, which provides the 3D printing market with instant price quoting and configuration software.

This classic example of transitioning from selling hardware to selling software is a way of moving up the value chain in a commoditized market. A number of companies such as WayBeyond and Spidertracks offer insights-as-a-service to unlock new value for customers. Consider the unique data you have and how it could be leveraged to create new products and services for your customers. 

#2 Use AI and automation to improve efficiency and profitability

Another way to compete against technology-first companies is to use automation to improve your operating efficiency and profitability. Businesses with a large labour force not only struggle with recruitment and staff absenteeism (especially during Covid) but also have high operating costs that results in low profitability. Companies like Reynolds Group offer a range of automated labelling, inspection and handling technologies for manufacturing and primary industries. 

Other avenues of improving profitability can come from the clever use of AI to efficiently allocate and utilise resources. Cloud file storage company Dropbox uses Machine Learning to save over $1.7M a year in infrastructure costs by predicting which documents users are likely to view to cache document previews. Uber uses real time demand forecasting that considers the weather, traffic and event information to optimise pricing, which increases their profit. RosterLab uses AI to schedule nursing rosters for hospitals and aged care, saving countless hours of manual work. 

Think about where the inefficiencies and bottlenecks are in your business and how you can leverage AI and automation to increase productivity and reduce costs. 

#3 Focus on differentiation through customer experience 

Customers have increasingly higher expectations for speed, personalisation and accessibility. This presents an opportunity to win by delivering a better customer experience. Here are 3 ways of improving your customer experience with AI


Insurance companies such as Lemonade offer faster claims processing by leveraging natural language processing (NLP) to instantly read insurance claims and supporting documents. They then couple this with machine learning to categorise and validate claims and also identify fraud. Real Estate company OpenDoor uses data science to instantly price the value of a house by considering similar properties that have recently been sold and house features including square footage, backyard space, number of bathrooms and bedrooms, layout, natural light. 


eCommerce and retail companies commonly use a wide variety of personalisation tools to help shoppers discover and purchase products. We recently helped New Zealand’s largest retailer, The Warehouse, develop a Gift Recommendation Engine to help shoppers find gifts. Kiwi company Fingermark uses cameras and computer vision to detect vehicles in the drive-thru for quick service restaurants and uses AI to learn trends and predict patterns to optimise the customer journey.  


The traditional 9-5pm call centre is a common point of frustration for many customers.  

Customers now want to be served at the time and place that is most convenient for them, and in their preferred language. The University of Auckland developed a 24/7 chatbot to answer commonly asked questions from students and staff. This has helped reduce the load on their contact centre and allows contact centre reps to work on more important calls. The chatbot also speaks English, Chinese, Te Reo Māori and Samoan. 

Customers are also expecting businesses to be available across a number of different social channels. Insurance companies like Cove allow customers to purchase insurance via their Facebook chatbot. UneeQ is taking this to the next level and building digital ambassadors and virtual assistants for the metaverse. 

Consider how you can leverage AI to reduce customer wait times, increase personalisation and extend your offering across multiple languages and channels. 

Final thoughts

AI and data have a transformative power to help businesses move up the value chain, increase profitability and enhance the customer experience. In the wake of a growing number of technology-first companies disrupting traditional markets, the best form of defence is to play offence and think like a tech company. Here are a couple of additional considerations as you embark on your AI journey

Develop a data strategy 

Data is a key ingredient for AI and machine learning and a real competitive advantage for companies that can build a data moat. Understand what data you have and what data you need to enhance your existing offerings and to create new products and services. At ElementX, we use a ‘work backwards from the end customer experience’ approach to create a roadmap on how to get there. 

Identify and automate bottlenecks in your operations

A key to improving profitability is to leverage automation technologies to increase efficiency and output while reducing operating costs. Understanding how things like chatbots, computer vision, and document processing could be leveraged to increase speed and scale up existing workflows and processes will have a big impact on profitability as well as your customer experience.  

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