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9 Months In: Insights from Generative AI Implementations in Pharma & Biotech – Our 4 Focus Areas
In an age of rapid technological breakthroughs, the usage of artificial intelligence has progressed beyond mere buzzwords to become an essential component of company operations. A subclass of AI known as generative AI has enormous promise, allowing Pharma & Biotech organisations to leverage the power of creativity, automation, and problem-solving. When it comes to deploying generative AI technologies, however, a specialised, bespoke approach is frequently the key to success. In this blog post, we’ll look at the process of creating and deploying private (or customised) generative AI in Pharma & Biotech, focusing on four key areas: internal situational analysis, governance, solution creation, and piloting.
Implementing Generative AI requires focus on 4 areas
In the journey toward generative AI excellence, we help organizations undergo a systematic process to ensure optimal utilization of resources and alignment with unique objectives. This involves these key focus areas:
1. Internal Generative AI situational analysis & assessment
Organizations initiate their generative AI journey by thoroughly assessing their internal landscape. This involves gaining a clear understanding of existing resources, identifying generative AI needs and use-cases, evaluating data assets, and assessing the skills within the workforce. This foundational step forms the basis for the organization’s path to generative AI excellence, often supported by leadership interviews and employee surveys.
2. Building an AI Governance
The development of a robust structure involves establishing policies and guidelines for the ethical and responsible use of AI, addressing potential changes related to internal data management and classification but also the governance of external generative AI solutions. FFI helps to build governance functions and processes to ensure that the organization’s AI initiatives adhere to ethical standards and legal requirements.
3. Build bespoke & secured solutions
Building on the foundational steps, organizations tailor internal and external solutions based on their unique needs and objectives across medical, commercial, R&D and any other function. Compliance is key thus Pharma & Biotech want to rely their gen AI investments mainly on private (or bespoke) generative AI solutions where there’s no connection to open gen AI technologies and internal sources from typical Pharma solutions like Veeva can be directly connected. This phase focuses on creating private solutions, step-wise learning and adapting solutions for optimal outcomes and value. Visit gingr.ai for more information on private gen AI in Healthcare.
4. Pilot use-cases, learn & provide training
The final stage involves the practical application of generative AI through pilots and projects. Organizations kickstart with small-scale pilots to validate the efficacy of the solution before gradually expanding into larger projects. Internal training & employee upskilling plays a pivotal role in equipping the workforce with the skills and knowledge needed to effectively utilize generative AI, ensuring a smooth integration into daily activities, driving efficiencies or new, impactful results.
Contact the experts
In navigating the transformative landscape of generative AI, organizations embark on a journey marked by strategic steps. From assessing internal landscapes to fostering ethical infrastructures, tailoring solutions, and practical application, each stage contributes to the overarching goal of achieving excellence in generative AI utilization.
FFI-Ventures is a valued partner as organisations strive for innovation and quality in AI deployment. FFI-Ventures has a solid track record in AI strategy, delivering customised support and personalised Pharma AI solutions.
Please contact us today for a demonstration or if you have any questions related to AI implementation & use-cases in Pharma & Biotech.