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'Contextual' AI blends human expertise and computer power
Aktana has had significant success in recent years in winning over pharma companies who want to add AI power to their salesforce automation tools; half of the top 20 pharma companies currently use its systems. Now, the company is introducing a next-generation version, branded as the Contextual Intelligence Engine, and claiming that better recommendations for sales and marketing actions will come out of this engine.
Commercial life sciences AI, generally, relies on gathering as wide a variety of data points as possible on the activities and intentions of healthcare professionals, such as the conferences they attend, the peer relationships they have, their prescribing activities and the like. When all goes well, this data, analyzed by the right algorithms, should produce recommendations and projections on next steps sales and marketing teams should take.
According to Aktana CEO Dave Ehrlich, this process is now being enhanced by providing more capacity for salespeople and marketers to add their own expertise to the analysis; Aktana customers can also add their own computer algorithms to those offered by the company. Another feature is “explainable” AI—having the system so set up that the rationale for a recommendation is made clear. (Many AI systems suffer from a “black box” problem—results come out of the analysis, but it’s unclear why that result was chosen).
The end result of this process, says Ehrlich, should be sales reps receiving more relevant recommendations; marketers enabled to execute marketing plans more accurately, and medical science liaisons being better prepared to address HCP concerns.