The global market for AI in the Life Sciences industry is expected to grow to $7.09 billion by 2028 as more organisations use AI applications to further advance innovation. The disruption caused by technologies such as AI, ML and Big Data has ignited a revolution in the industry, propelling it into an era of unprecedented possibilities. 

 

You will probably know that one of the main areas in which these technologies are transforming the industry is precision medicine, which uses AI and ML to offer personalised healthcare by analysing genetic data and patient records to guide treatment decisions. Another heavily impacted field is drug discovery, in which AI and ML are enabling the mining of unstructured data to improve trial participant selection and predict drug properties, potentially boosting the pharma industry’s growth by $60-$100 billion annually. 

 

It goes without saying that the anticipated economic growth across the whole Life Sciences sector due to AI and ML applications underscores the immense potential these technologies hold. 

 

So far, we’ve discussed the beneficial impact these technologies will have on the healthcare and pharma sectors, yet it’s important to acknowledge that there are challenges, too.

 

As companies navigate this new landscape, it is imperative to tackle the potential issues presented by AI, ML and Big Data if we are to fully realise their benefits. 

 

The Hays Salary Guide surveys across the EMEA region show that, while employers think AI is beneficial for business growth, 60% of them still have no quality assurance protocols in place, though most will surely be aware of the need to implement robust data protection measures to safeguard patient information.  Ensuring the integrity and quality of data used for training AI models is essential, as it directly influences the performance and reliability of AI systems in clinical and research settings. 

 

The EMEA Hays Salary Guide survey results reflect a common anxiety that AI might lead to job displacement, with 32% of employees and 35% of employers in the Life Sciences sector anticipating that AI could potentially eliminate more jobs than it creates. This underscores the need for strategic planning and policymaking to ensure that the integration of AI into the workforce is accompanied by measures to reskill and upskill employees. By doing so, the workforce can transition into new roles that are created as a result of AI advancements, thus mitigating the impact on employment and harnessing the full potential of AI for innovation and growth in the industry. 

 

There’s a lack of skilled professionals who can effectively navigate the intricacies and keep pace with the advancements that are constantly being made in the industry. As the sector continues its rapid evolution, the demand for professionals who can adeptly manage these complexities and stay ahead of new developments is increasing. Some of the new in-demand roles include research data specialists, AI scientists in fields such as imaging foundation models and healthcare data scientists.

 

A collaborative effort in education and training is needed to cultivate a workforce that is proficient in current technologies and can adapt to future innovations. Initiatives such as specialised training programs, partnerships with academic institutions, and investment in continuous professional development are essential to bridge this gap and ensure that the Life Sciences field remains at the forefront of scientific and medical progress.

 

Companies in the healthcare and pharma sector are being faced with multiple challenges. But it’s clear that they need to move forward if they want to remain competitive. So, what can Life Sciences organisations do to cope with the challenges posed by AI, ML, and Big Data?

 

By channelling funds into learning initiatives like workshops and webinars, workers can gain essential insights into AI and its practical applications within the Life Sciences and healthcare sectors. The Hays Salary Guides show that 90% of EMEA Life Sciences employees report having no AI training, yet 75% are willing to receive it, which means Life Sciences workers want to leverage technology. Investing in this knowledge can foster an environment of innovation and efficiency, ultimately enhancing the quality of services provided in healthcare and pharma.

 

Maintaining a focus on transparent and direct communication is essential in cultivating a sense of trust and understanding among employees in the Life Sciences sector concerning the adoption of AI technologies. Having open forums and collaborating with experts can help employees reduce anxiety and overcome challenges when using the new technologies. This commitment to openness can lead to a workforce that is more engaged and better prepared to leverage AI for innovative solutions and improved outcomes in healthcare. 

 

Forming alliances between Life Sciences companies and technology enterprises to establish AI pilot initiatives can offer a structured and safe environment for the trial and examination of AI technologies. Sanofi, a global leader in healthcare, has recently joined forces with Aqemia, a Pharmatech leveraging quantum physics and AI for drug discovery. These partnerships can pave the way for innovation, allowing for the careful assessment and refinement of AI’s role in advancing healthcare and scientific research. Through these collaborative efforts, both sectors can share expertise, mitigate risks, and optimise the integration of AI into critical workflows.

 

Embracing a comprehensive strategy that tackles upskilling and reskilling to equip your Life Sciences workforce, effectively communicates how AI, ML and Big Data can be safely leveraged in the industry and leans on IT tools to navigate tech confidently is key to driving business growth in the healthcare and pharma sector.

Romain Domenech 

Director

 

Romain Domenech joined Hays 15 years ago, working his way up to his current position of Director at Hays in France.  Romain specialises in the Life Sciences and Technology sectors, managing an extensive team of people and ensuring client expectations are met.