How are you evaluating which AI and emerging technology investments to prioritize? What criteria determine which projects continue, versus which get paused?

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CIO in Healthcare and Biotech3 months ago

Our company employs a rigorous demand management process, balancing supply and demand. We set annual goals and quarterly review shifts, ensuring capacity allocation across four focus areas: growth and innovation for new revenue, transformation with at least 30% capacity, operational excellence to maintain customer satisfaction, and governance to manage trade-offs and disruptions. This balanced approach keeps our portfolio in check.

VP of IT in Healthcare and Biotech3 months ago

Our approach begins with identifying the core problems we aim to solve. By focusing on significant business challenges, we can effectively evaluate which technologies offer the most incremental value. Measuring and articulating this value is crucial, though it requires time and diligence, especially with the growing interest in AI. Pilots are integral to our strategy, allowing us to test technologies for value and build compelling cases for scaling. As AI ideation grows across our business, creating a forum for prioritizing these needs becomes essential. We aim to accelerate AI adoption by partnering with promising vendors to expand their roadmap and tackle additional use cases.

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no title3 months ago

Our process mirrors Sarah's approach, with a governance structure where ideas can be presented and validated at a high level. Pilots are conducted, and outcomes—whether successes or failures—are reported back. Based on these results, decisions on further investment and scalability are made.<br>

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Established AI governance framework with defined policies and oversight52%

Currently developing governance models and risk controls67%

Relying on existing security/compliance frameworks (no AI-specific policy)26%

No formal AI governance approach in place

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