The key to successful collaboration between human specialists and AI is to identify areas in which people excel

The media loves to paint darkly, so when it comes to AI and related technologies, it’s not surprising we see robots depicted as the enemy in our cinemas, and headlines screaming about swingeing job losses as automation 'takes over'.

Cognizant’s research is rather more encouraging. Far from fearing massive job losses as new digital technologies are adopted, we actually expect to see net gains. That’s because the future isn’t in the media’s dark vision of machines replacing people, but in machines supporting people in their job roles, making our jobs more interesting, more rewarding and more productive.

Collaboration, not replacement

The key to successful collaboration between human specialists and AI is to identify areas in which people excel, such as social interaction and innovation, and those in which digital technologies perform best, such as structured, repetitive processes and calculations.

By analysing tasks across end-to-end business processes in this way, outcomes can be markedly improved.

Oncology provides a great example of this approach – a Harvard Business School study has shown that pathologists supported by AI achieve better rates of detection than either they or the machines working alone.

How, then, can pharma navigate this journey?

The physical task master model

Cognizant has developed the Physical Task Master model to break job roles into their individual tasks and identify their varying levels of suitability for AI and human intervention, optimising the capabilities of both. This provides a sound footing for rigorous re-engineering of diverse business processes.

At one end of the spectrum lie tasks, such as the detailed analysis of large quantities of research data, requiring a high degree of structure but little social interaction or dexterity. These are typically well suited to AI intervention.

Conversely, unstructured tasks demanding copious social interaction – advising patients of their condition and their treatment options, for example – would require human intervention.

By appropriately allocating each task to either human or AI intervention, entire end-to-end processes can be optimised, often to a remarkable degree.

Augmentation and enhancement

This is, emphatically, not a matter of replacing employees with automated systems. This is the augmentation of employees’ (blue and white collar) abilities with precisely targeted digital systems support, to enhance their capabilities, success rates, and outputs.

HCPs commit many years to their studies in medicine, with the over#arching goal of saving lives and reducing suffering. Augmenting their capabilities with AI tools in this way makes their analysis and interpretation of patient test data, medical notes and scans more rewarding and more productive, ensuring a higher rate of successful diagnosis and better health care outcomes.

Tip of the iceberg

The opportunities presented to pharma businesses by this collaborative approach to AI adoption are near limitless.

We explore the topic in greater detail in the Cognizant Center For The Future of Work report, The Symbiosis of Humans and Machines: Planning for Our AI-Augmented Future. Download your copy here.