2023 Predictions: the next chapter of the digital-first, artificial intelligence era
Changes are ahead for professionals in life sciences sales and marketing, and medical affairs. From the widening gap between AI-users and those companies still holding out; to the next evolution in AI, and how companies will seek to make it more practical on a global scale; to the impact of AI on leveraging digital opinion leaders to get more clinical evidence in the hands of doctors, Aktana offers its predictions for the coming year.
Prediction #1: In 2023, the chasm will widen between those companies investing in analytics-based, digital-first commercial models and those still sitting on the fence and taking a measured approach.
Alan Kalton, Global SVP: Life sciences companies are notoriously cautious. However, COVID-19 put many companies in the uncomfortable position of forcing new ways of working, new ways of engaging with customers, and new technologies. For many companies, the changes are sticking, ushering in the digital-first era.
We have started seeing the impact of the adoption of new technologies, such as platform intelligence solutions, ‘on the ground.’ In fact, 89% of companies surveyed by DHC Group reported that they are successfully executing an AI-driven omnichannel strategy across sales and marketing and scaling up.1
Gone are the days when digital and analytics technologies were merely a shiny new toy to test-run in isolated markets. Today, many companies understand the impact of AI and recognize that it needs to be powering engagement across all markets. As the global director of field force AI enablement at Novartis noted recently during our Omnichannel AI Masterclass, “in three to five years, I hope that our industry has moved to where AI isn’t a buzzword, but rather, it’s baked into the mainstream of our go-to-market strategies because it’s so essential.”
The organizations delaying investment in scaling intelligence platforms across the organization will see a widening gap between them and their competitors in terms of influence, customer engagement and ultimately, financial success.
Prediction #2: Companies will connect data science models to day-to-day operational activities to execute on strategic business goals across the entire organization.
David Ehrlich, CEO & Chairman: Next year, we will see the start of the next chapter in AI for life sciences commercial organizations.
Traditionally, AI has lived in one of two places – either with headquarters teams, analyzing massive amounts of data to generate ‘smart’ conclusions, or within discrete applications, helping to tune the application’s impact (i.e., marketing automation systems). At headquarters, AI is used to strategically assess business opportunities on a broad scope whereas the tactical AI embedded into individual applications is very specific and application limited.
Both are valuable, but what’s missing is the connective tissue between HQ’s broad-scope AI to the various operational systems required to execute HQ’s strategic business goals. Such connective capability would reach into the multiple operational systems required for execution and guide the appropriate actions. As a result, operating teams could agilely deploy data science models to guide a wide range of day-to-day activities.
Ultimately, companies will be both more effective (more good decisions) and more efficient (less bad decisions that waste resources), cycling through the ‘try it, fix it’ rhythm much faster to continuously improve AI’s outputs across the entire organization.
Prediction #3: AI-driven identification of digital opinion leaders (DOLs) will accelerate evidence dissemination.
Deepak Patil, Senior Director of Medical Strategy: Medical affairs teams are racing to provide a personalized “Netflix-like” engagement for ever-expanding targets, predicting needs and preferences and then delivering unbiased scientific information in the most useful formats and channels. Field medical affairs or medical science liaisons (MSLs), work to engage with physician key opinion leaders (KOLs), but also have a new target: digital opinion leaders.
DOLs, in essence, are KOLs active on digital platforms. DOLs may be practicing or non-practicing HCPs but have major influence over consumer behavior and informing other physicians. Some rise to near-celebrity status, such as Dr. Mikhail Varshavski – better known as Dr. Mike – who has a combined social media following of over 21 million people. He has been featured in Time, Men’s Health, Business Insider, and People Magazine, to name a few. Also, Dr. Don Dizon is a professor at Brown University and director of medical oncology at Rhode Island Hospital who shares cancer research via video primarily on TikTok. He has 38,000 followers.
In addition to doctors, nearly 90% of all adults in the U.S. search for health information on Facebook, Twitter, YouTube, and other social media sites. From doctors to patients, MSLs can multiply their influence by engaging with the right DOLs. AI and natural language processing technologies can help by mining available information – based on specialty, therapeutic area expertise, followers, outreach network, and posts – to help identify the right influencers to engage and cultivate a relationship.
Next year, as the role of the MSL continues to expand and evolve, MSLs will demand new smart technologies to help them engage with the growing fleet of digital influencers. And when these relationships are formed, MSLs will increase education and information dissemination faster and farther than they have ever done before.
- The DHC Group. (November 2022). “The State of Omnichannel HCP Engagement in Pharm”.