The consistent and exponential technological developments in the life sciences industry have vast implications for its future. Technology is becoming more efficient as the years pass, through data analysis, the Cloud and digital medical practices which have already become an integral part for most healthcare providers who have to use digital tools for their business to perform.
This means that many traditional roles within the current industry will likely change over the next couple of years, as the lines blur between human disciplines and machine learning. This is already in place as technology is facilitating much of the current patient and practitioner relationship, with personalised data that can accentuate care in a more specific manner.
Artificial Intelligence is set to become the biggest revolution as its forecasted to help both patients and practitioners throughout the industry. Machine learning is also expected to drastically change many aspects of healthcare, life sciences and biotech.
Impact on careers
The World Economic Forum predicted back in 2016 that a third of the most crucial skillsets would not yet be considered important by 2020. This opens up a huge window of opportunity for many technologically orientated career opportunities that may not have existed previously.
The focus on datasets and machine learning will provide pathways for individuals who can improve AI decision making and program many analytical focused services that can enhance patient care. As this form of AI is leaving some aspects of patient care by the wayside, it’s allowing for a whole other window of opportunity for those who can improve it. Therefore, blurring the lines between human and machine cognition in life sciences.
As data becomes the biggest commodity for a lot of big pharmaceutical companies, job roles in AI and robotics will become the priority for future careers – especially considering the vast amount of data the new generation of AI will have to take into consideration. From patient symptoms, behaviours, treatment and individual cost, this will all have to be pre-programmed with specialised datasets by machine learning specialists.
Occupations for AI enhancement are already finding themselves at the forefront of life science companies’ agendas. These jobs range from Data Engineers, Analytics Directors, Statisticians and Algorithm Engineers. These job roles are already proving tricky to fill, so training for these skills is a necessity with upcoming generations. As data moves to a more central focus for the Life Sciences industry, further pathways will open up for Data Security, Computer Systems Validation and Legal to ensure that the vast amount of private information companies will hold on each of us is fully protected and also can adhere to regulations such as GDPR.
Accenture Research found that 82% of current employees expect AI machine learning and upcoming digitization to transform much of their work in the next 3 years. The medical world is expanding with AI and there’s a constant looming question for companies to innovate and accommodate. The rise of Technology is not just transforming the workload of current professionals but inviting many new skillsets that would have only been speculation a couple years ago.