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Gen AI capabilities are being explored across different functional areas, from Research & Development (Derisking Drug Discovery) to Clinical Trials (Accelerated time to market) to Commercials (reinventing HCP engagement). A McKinsey survey revealed that 79% of LS organizations plan to build their own gen AI solutions tailored to their unique requirements.
AI appears poised to address many of these challenges, yet many life science and pharma organizations need help in utilizing this technology effectively. Our perspective: AI is only as good as your trust in the data that it uses. Data trust is still an ongoing part of AI development and requires a framework built on people, processes, and technology.
That’s why Wipro and Alation are teaming up with DQ Labs to share our Data Trust for AI solution and architecture built specifically with the unique situations of life science and pharmaceutical companies in mind.
You’ll learn:
How Data Trust is essential to solving current challenges
The need to involve people and technology in the implementation of trusted AI solutions
Where Gen AI capabilities are being explored across different functional areas and how this increases focus on data privacy and data access controls
Join us October 17th at 9AM CDT to find your way to trusted AI solutions.
Speakers
Wipro - Deepa Behl
Alation - Steve Wooledge
DQLabs - Raj Joseph
Datasheet
Enable Trusted AI Governance with Alation’s AI Readiness Accelerator
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Building a data-driven culture starts with robust data literacy.
Webinar Registration
In this webinar, discover how to unlock the full potential of your Critical Data Elements (CDEs) by focusing on where to start, how to govern them effectively, and the value they bring when managed well. We’ll explore how Alation’s powerful features can help you define, govern, and maintain trust in CDEs to drive business outcomes while meeting regulatory demands like APRA CPS 230. Learn actionable steps to establish strong CDE governance, empowering data users to make informed decisions with trusted, compliant data.