While AI offers exciting possibilities, its effectiveness depends on thoughtful implementation, clear business cases, and a solid foundation of processes, systems, and people, experts say.
During the AI portion of a panel discussion at this year’s Finance and Accounting for Biosciences conference, Sean Godbout, chief accounting officer, corporate controller, at Biogen, first discussed how his organization’s AI journey is still in its infancy.
“We’re very early in the stage of using actual AI, as it’s come to be known, over the last six months to a year,” he shared. Godbout stated that the company currently utilizes bots in certain areas, employs “some” machine learning, and is exploring predictive analytics for forecasting purposes.
While AI is not yet integral to daily operations, he said automation is a key area of interest, with efforts underway to simplify a purchasing system and enhance processes for compliance and external stakeholder engagement.
“It’s kind of automating where you can and working with an emphasis on out of the box and on building good processes and people around things,” he explained. “Ultimately, if you have the best systems, but terrible people or terrible processes, it doesn’t benefit you.”
Godbout continued, “You have to have all three working together in order to have an effective and efficient organization and to address compliance risk and, other risks that we have as a finance organization.”
Meanwhile, Scott Godsoe, executive director, assistant corporate controller, at Vertex Pharmaceuticals, said, “AI doesn’t fix bad processes. Before you think too deeply around technology solutions, really take a step back and understand your current state process and the pain points.”
He also added that “to get your bang for your buck with AI, you need clean data,” he said. Without it, even the most advanced AI systems will produce unreliable results. “It’s going to be garbage in and garbage out,” Godsoe said.
Gina Tracey, controller at Alnylam Pharmaceuticals, agreed on the importance of clean master data, saying, “Clean master data is a big one. If there are things you’re doing repeatedly because you’re missing a field or manipulating data, focus there. Work with your IT partners and other key sources to ensure you have all the master data in the way you need it.”
Additionally, Godsoe pointed out that while there has been significant discussion in recent years about AI potentially replacing the accounting profession, including reports of AI passing the CPA exam, the reality is different.
“I really don’t think that’s true. I think accountants that use AI or technology at some point will largely replace accountants that don’t at some point, not immediately,” he said.
Tracey, whose company is in the early stages of exploring AI enhancements in existing tools, stressed the importance of governance and cybersecurity regarding AI use. “I think that’s an important piece too… make sure that you’re lockstep and working very closely with your IT partners,” she said.
She added that IT teams are focused on governance and infrastructure, and can provide support, stating, “They can help to support us and maybe even come to us with ideas. ‘Have you thought about these things? Maybe let’s go look at these tools together.’”
Working with third parties
Not all AI solutions need to be developed in-house, the panelists agreed. Many third-party vendors and outsourcing partners are making significant investments in AI, offering biotech companies an opportunity to benefit from technology without incurring heavy development costs.
“A lot of companies that specialize in outsourcing are making huge investments in AI,” Godsoe said. “Some of your biggest AI investments might not be in-house but through partners who incorporate AI into their offerings, making it a really attractive value proposition.”
As it becomes embedded in more tools and systems, its impact on the biotech industry will only continue to grow.
“Everyone is using AI. It’s like a bingo card. What do they really mean by it? Is it an effective use? It can be a shiny thing that does neat tricks but doesn’t really drive what you want it to drive from a business perspective,” Godbout said.
Quotes have been lightly edited for clarity.