05Technologies that anticipate experiences
Preventive healthcare leads the way
Automation was the first step - the building of routines and algorithms to complete tasks based on historical data. The next step is anticipation - predicting what will happen next, providing the answers to questions before you have time to ask. From retail to logistics, manufacturing, healthcare and smart mobility, anticipatory technologies are about to scale up.
What will change
Industry will move from from automation to anticipatory experiences - intuitive, seamless experiences powered by data, AI and automation. People will receive the answers to questions before they think to ask them. Anticipatory tech is set to bloom in many industries, from self-driving cars and agriculture to smart homes and insurance. Predictive, personalised health-care points the way as one of the current fastest growing consumer areas.
Use healthcare as an example, consumers are taking self-care to the next level by harnessing smart gadgets and sensors to measure and fine-tine every activity in their body. They are investing money to track their sleep, stress, physical activity and recovery, following recommendations their devices provide. From a data perspective, people want to do more than track their activities - they want to understand how their genetics impacts their lives. For instance, Thryve Healthcare harmonizes all health data from different consumer devices to provide better insights.
Opportunities worth taking
Businesses are ready to respond to rising demand, with many M&As taking place recently as companies aim to serve consumers by giving AIs holistic data they can use to better anticipate your nutritional, diet, activity, exercise, meditation and recovery needs to name a few. With the right guidance for nutrition and analysing our health data, we will live longer and healthier lives.
The whole healthcare industry faces massive disruption as new platform-based predictive healthcare solutions challenge traditional healthcare providers. Remote monitoring will for instance enable the prescription of proactive, preventive actions for patients.
smart anticipatory tech will enable diets to be tailored in real-time, with optimal nutritional content delivered to your door based on wearable data.
Maintenance and operations
We see intelligence moving from predictive to prescriptive. Connected machines will not only predict maintenance breaks - but also suggest what should be done next, leaving humans free to accept recommendations for maintenance plans.
Self driving cars that adjust music, ride quality and ventilation according to your body temperature, schedule and stress levels.
Deep-dive into this bet
Global healthcare market size 2019 approx. $9 trillion. Global industrial machinery maintenance and repair forecast 2024: $720bn.
Look at these 2024
Methodology: A high-level view gathered from various openly available data sources on market size & compound annual growth rates. To simplify comparison between analysts sources, we’ve removed differences in market details by calculating an estimated average for total market size 2024 and average CAGR for selected time period. This allows us to gain “correct enough estimates”. Unless linked directly to one source, each of our market estimate has included 2-8 sources e.g. WEF, CB Insights, Mordor Intelligence, Markets & Markets, Research & Markets, Grand View Research, PWC, Allied Market Research, McKinsey, Market Watch
Proactive wellness alone is evaluated as being a $1 trillion+ industry. Digital therapeutics $9bn market. AI market in 2024: $146bn and IOT market in $935bn.
Top 18 unicorn sniffing smart money VCs, 1376 investments 2018-2020
Source: Crunchbase Pro, accessed: 03/20, research of company description terms between 01/2018-02/2020, investment types: early stage investments by top 18 unicorn sniffing smart money VCs, n=1376 investments
Artificial intelligence 14%, Health 17%.
Myriad sets of image, voice, video, statistical data are impossible for human eyes to analyse and recognise patterns. To anticipate events and provide increased customer value, recognition algorithms help in the detection of patterns, anomalies and correlations.
Biometric surveillance ethics
Monitoring can lead to tracking, and recommendations can lead to manipulation. Where do we draw the line on what we want our machines to learn from us?
When everything is quantified, it is easy to become obsessed with maintaining your stats.
Machine-driven decision making in medicine
There is skepticism concerning the influence of machines in medical decision making. AI-powered anomaly detection can help doctors spot risks, but current consensus is that humans should make final decisions.
Unforeseen environmental side effects
Anticipatory AI without proper data and domain knowledge could lead to problems - as an example, Waze ruins whole neighbourhoods while trying to reduce congestion.
Home kit for DNA sampling to receive genetic reports including risk of chronic diseases, and take actions early on to prevent risk of genetic
AI-supported drug discovery for neurodegenerative diseases (e.g. Parkinson and Alzheimer in which the nervous system starts eroding)
Thryve health harmonizes all the health data from different consumer devices, to provide better insights
Brain-sensing wearable for real-time device control aims to make the power of thought a real deal.
CardioSignal is a reliable and easy to use CE certified (Class IIa) medical device that can easily detect atrial fibrillation in your heart. CardioSignal uses motion sensors on the phone to detect atrial fibrillation, analyzing measured data to determine whether it is a normal or atrial fibrillation rhythm.
Health information predicting, preventing and adverting chronic diseases from simple blood sample with NMR (nuclear magnetic resonance) technology
Smart electronic devices that can be incorporated into clothing or worn on the body as implants or accessories as point of interaction or source of data.
P2P trust solutions, blockchain
Decentralization for verifying the privacy and authenticity of the transaction., Blockchains can be utilized to add trust regardless of affirmed identity smart contract.
Components that are required to run an ML Algorithm locally on a device. In edge computing, a microcontroller unit (a small chip) is embedded with the ability to perform AI/ML computing offline based on sensor inputs without needing a cloud connection.
Although cloud computing is nothing new its role will be redefined with the define its the advanced storage architecture that links cloud with edge.
Using video image as a source for identifying, analysing and acting (objects & faces to provide access, personalise, charge, recommend, etc.)
Using voice as a source for identifying, analysing and acting. (e.g. speech to text, identification, measuring, etc.)
Indicators of change
Adoption of wearables like Ouraring
Intelligent phone sensors for 247 monitoring, examples from Apple and Samsung
The technology is already in place from connections between sensors, IOT, 4G/5G, edge computing, AI, machine learning. It’s about wiring these together for use cases for anticipation
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