More organisations are turning to digital disruptive technologies to increase growth and relevance. Artificial intelligence (AI), specifically machine learning (ML), is helping a range of industries in unique and unexpected ways. The predictive insight and planning mechanisms ML provides are transforming industries, levelling the playing field amongst businesses, and improving IT processes. And, the transformational role of AI is just as positive for organisations as it is for their stakeholders.
AI can help businesses collect, store, manage, and aggregate large amounts of data from customer sales, client interactions, payment transactions, or survey results, and ML helps organisations put this data to use. For example, finding meaningful patterns and outliers in data groups can help organisations understand consumer purchasing habits connected to successful and less successful campaigns.
Collecting and analysing competitor data can help businesses gain a competitive advantage. This is particularly useful for small retail businesses that may need to adjust pricing based on competitor activity. Data insights can help identify margin-preserving or volume-driving pricing strategies within the context of the market, and predictive data analytics can help retailers structure smart and effective pricing campaigns to match prices set by retail giants.
ML and predictive technologies are also helping the medical and health industry improve patient service and care, and to develop more comprehensive understandings of future health. From a business perspective, predictive technologies help bolster doctors’ and hospitals’ patient engagement and satisfaction, due to shorter wait times for medical services, and enhanced care. Data patterns can indicate which patients are more likely to miss appointments, and, paired with automated technologies, booking systems can send patients multiple appointment reminders. This means doctors and receptionists are prepared to move queues along quickly when a patient doesn’t arrive for their appointment.
The benefits of AI in healthcare extend far beyond speeding up patient processing times. Increasingly, medical professionals are using data from blood tests, check-ups, and hospital visits to determine future rates of illness and disease. The Australian Digital Health Agency refers to a report by JASON (PDF), an independent scientific group that advises the United States government, on AI in healthcare trends. The report states that data collected from blood tests can help the medical field predict heath challenges like diabetes and coronary artery disease in patients and, on a larger scale, certain regions and states. Doctors and medical staff are also using apps to clearly and safely process patient data.
Internally, AI is also boosting decision-making for businesses across a range of sectors. Predictive analysis in business has improved organisations’ knowledge and management of IT infrastructures, and helped strengthen businesses against cybercrime and data breaches.
Using data collected from consumer devices to fuel decision-making lets organisations act proactively rather than retrospectively, and prepare for future customer needs and consumer attitudes. Increasingly, businesses can target consumers with precise and perfect scheduling, and offer personalised and fine-tuned content ahead of time.
It’s important to remember AI isn’t solely reserved for technology professionals and IT teams. The ability to predict future phenomena carries benefits beyond pure business growth. Predictive technologies help organisations match their competitors, and get ahead of consumer demand, offering unique and personalised products, services, and care to customers before they even need it. Organisations and businesses across a range of industries need to prioritise and leverage their data to gain critical insight into the future.
James Bergl is sales director, Australia/New Zealand, Datto and an executive council member ANZ, CompTIA.