In fact, healthcare’s back offices and supply chains are where AI is gaining traction now, generating quiet efficiencies that don’t garner the same headlines as visions of virtual physicians and robotic nurses but have profound potential to disrupt the industry.
Health businesses are using AI to automate decision-making, create financial and tax reporting efficiencies, automate parts of their supply chains, or streamline regulatory compliance functions. Tax functions in particular stand to benefit from artificial intelligence and robotic process automation (RPA) to simplify and automate processes once done exclusively by humans, such as interpreting, deciding, acting and learning.
For example, companies can use AI/RPA to determine an entity’s tax filing status, analyze the potential tax impacts of changes to accounts, help prepare and review tax returns, calculate tax rates, identify items that could be fraudulent or trigger an audit, and help respond to an audit if it does occur.1 Some processes may be more easily automated than others, but even partial automation can help employees make better use of their time and expertise.
Repetitive tasks in particular may benefit from the introduction of AI and machine learning to replace or supplement human interaction. AI doesn’t forget, tire, get bored with tasks or develop carpal tunnel syndrome. Healthcare providers can leverage AI tools to help their staff analyze routine pathology or radiology results more quickly and accurately, allowing them to see more patients and realize greater revenues.2 Companies such as Boston-based Cogito Corp. are using AI to help health insurers better understand and respond to customers who contact their call centers, making those businesses more effective and efficient. A pharmaceutical company could use AI to automate the intake, analysis, follow-up and reporting of adverse event reports associated with their drugs.
Medical product development also can benefit from AI. The R&D process for new drugs is exceedingly slow and expensive, with some products taking more than a decade to obtain FDA approval after being discovered and costing $1 billion to develop. And that’s if a company gets approval. Several companies are trying to turn this paradigm on its head, using AI tools to better identify which compounds are likely to succeed based on early-stage clinical data.
“We identify drugs that are stuck in the pharma traffic jam,” said Dan Rothman, chief information officer at Roivant Sciences, a Basel, Switzerland-based global pharmaceutical company using AI to assess drug candidates abandoned by other companies and bring them to market. “AI gives us a higher probability of obtaining success, even if we have some failures. It gives us more ‘at bats.’ There’s a lot of value to be found in making the drug development process more efficient.” Roivant isn’t alone. Other companies, such as UK-based Exscientia, are using their AI drug discovery platforms to partner with major pharmaceutical companies like GSK and Sanofi to target specific disease areas (see Figure).3