3 Ways to Prepare for AI-Driven Pharma Quality Management

Look over any list of pharmaceutical industry trends that has surfaced over the past decade and you’ll notice a common theme: artificial intelligence (AI) is consistently the №1 recommended tool that pharma companies should invest in and implement. The only difference in 2021 is that AI and other emerging technologies — once widely viewed as having phenomenal potential but few practical applications in common pharma settings — are yielding an increasing number of meaningful results in myriad activities throughout the industry.

Pharma companies of all sizes have already started capitalizing on emerging technology-powered tools. According to Gartner’s industry research, AI has become “the most powerful and pervasive emerging technology across healthcare and life sciences.”(1)Companies that have incorporated emerging technologies into their overall digital transformation strategies are well ahead of competitors who are still considering whether to jump on the bandwagon.

Not even the COVID-19 pandemic slowed the advancements emerging technologies are making. Gartner polls show that most companies have been maintaining or even increasing their investments in AI throughout the pandemic.(2)Additionally, the reach of AI within pharma organizations is expanding beyond conventional R&D and clinical applications to enable step changes in other areas like quality management and postmarket monitoring.

The proliferation of AI into quality and other previously untapped pharma functions shows no sign of letting up. Emerging technologies are even contributing to the overhaul of management roles, with projections indicating that 69% of managers’ duties will be automated by 2024.(3)This automation will make it possible for managers to reduce the time they spend doing paperwork and other manual tasks and allow them to concentrate on their core responsibilities and revenue-driving efforts.

“AI techniques are reaching deeper into the work environment, not only replacing and augmenting mundane jobs, but also changing or augmenting those that remain,” according to Gartner’s research into industry use of emerging tech.(4)

AI and related advanced technologies have evolved from being premium advantages that only the wealthiest pharma companies could afford to indispensable tools that resource-limited organizations can leverage to drive efficiency and speed. In fact, industry forecasts signal that pioneering life sciences organizations of all sizes will incorporate AI into half of all core enterprise processes by 2023, which Gartner predicts will expose new data challenges (i.e., gaps in IT architecture, governance and skills) while creating new opportunities for growth and change in the pharma industry of tomorrow.(5)

3 Steps to Lay a Foundation for Advanced Technologies

There are three practical steps that any company can take to be better positioned for the future as AI continues to shift from being a wish-list luxury to a practical tool for enhancing efficiency.

#1. Promote Digital Maturity in Your Organization

Digitally advanced pharma companies are more successful at adapting to technological and industry changes and are in a better position to leverage cutting-edge tools. Among the organizations that have successfully generated value from AI, 88% have interwoven their AI initiatives into a broader companywide digital transformation, Boston Consulting Group (BCG) studies show.(6)Companies that lag behind their digitally mature cohorts will likely find themselves unable to maximize the potential of emerging technologies.

#2. Plan for and Adopt Beneficial Tools Early

Get ahead of the game by involving business and IT stakeholders as early as possible. When cross-functional groups work together to strategize and implement emerging technologies into core digitized systems and processes, it helps IT teams be better prepared for integration. It also helps ensure that new solutions are properly oriented toward solving pressing business challenges quickly.

#3. Aim to Incorporate Predictive Tools

Innovative technologies and statistical techniques for data mining, predictive modeling and machine learning can help companies anticipate future or otherwise unknown events by improving data analytics. The companies that wait to see others’ outcomes before making predictive technologies a priority will always be playing catch-up. As proof of that point, Gartner researchers found that predictive maintenance initiatives that do not establish the requisite infrastructure for operationalizing AI in advance take twice as long to create business value as those that do.(7)

Achieving ROI From AI

Getting your money’s worth from investments in new technologies requires a sound strategy. To drive business value with AI tools, BCG recommends companies follow these six steps:

  1. Integrate AI into business strategy: Identify the business objectives that can benefit the most from AI and focus on the initiatives with the greatest potential impact.
  2. Prioritize revenue growth over cost reduction: The greatest value comes from growth driven by deeply embedded AI.
  3. Take bigger risks to achieve greater impact: BCG reports that half of large, high-risk initiatives bring value compared with just 23% of those focused on low-risk projects.
  4. Align AI development with its usage: The implementation of AI should be a collaborative effort between business stakeholders and process owners.
  5. Treat AI as a business transformation: The introduction of AI should be part of an overall digitization and modernization plan, not an isolated initiative.
  6. Invest in AI talent, governance and process change: Companies that get the best results from AI are those that invest in recruiting, reskilling and training. Robust and agile data management platforms are also key components of successful AI initiatives.(8)

To learn more about AI’s impact on the trajectory of life sciences industries, check out this article on the future of quality.


  1. “Predicts 2020: Life Science CIOs Must Digitalize for Business Growth,” Dec. 2019, Gartner.
  2. “Debunking Myths and Misconceptions About Artificial Intelligence, 2021,” Sept. 10, 2020, Gartner.
  3. Ibid.
  4. Ibid.
  5. “Predicts 2020: Life Science CIOs Must Digitalize for Business Growth,” Dec. 2019, Gartner.
  6. “How to Turn AI into ROI,” BCG website.
  7. “A Comprehensive AI-Enabled Predictive Maintenance Plan Starts With Business Understanding,” Dec. 4, 2018, Gartner.
  8. “How to Turn AI into ROI,” BCG website.

James Jardine is a marketing content writer at MasterControl, Inc., a leading provider of cloud-based quality and compliance software solutions. He has covered life sciences, technology and regulatory matters for MasterControl and various industry publications since 2007. He has a bachelor’s degree in communications with an emphasis in journalism from the University of Utah. Prior to joining MasterControl, James held several senior communications, operations and development positions. Working for more than a decade in the non-profit sector, he served as the Utah/Idaho director of communications for the American Cancer Society and as the Utah Food Bank’s grants and contracts manager.

Originally published at https://www.mastercontrol.com.



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