AI can be a powerful tool, but in pharma, it’s only useful if it fits how teams actually work. You can build all the models you want, if they don’t reflect market realities, they’ll be ignored.

AI for pharma commercial analytics is most effective when it’s trained on real-life questions. Not just “Which region has lower uptake?” but “What’s causing the shift, access, awareness, or provider behavior?” Those are the questions commercial teams care about.

At KMK, we’ve seen this firsthand. Clients often come to us after trying platforms that promised automation, but delivered confusion. The difference comes down to understanding how data, strategy, and field dynamics intersect.

Looking for AI that helps your team move, not pause?
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More info: www.kmkconsultinginc.com