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Industry Insights: CIO vision 2025 — bridging the gap between BI and AI

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Healthcare of the future driven by AI? It’s closer than you think.

Healthcare industry CxOs recognize the highest strategic importance to their organization is generating actionable insights from their data. The future of healthcare depends on it.

Between now and 2025, artificial intelligence (AI) will help healthcare organizations tackle the industry’s toughest challenges, targeting use cases from molecular modeling, to clinical trial acceleration, to personalized patient and employee experiences with chatbots.

But getting from here to there requires leaders to rethink their current data architecture. 72% of the 600 respondents to the MIT Technology Review survey cited problems with data as being more likely than other factors to jeopardize the achievement of their AI goals between now and 2025. 38% of leaders believe regulatory and security concerns will slow their progress. On the contrary, leaders who are data-forward today have found AI tangibly benefitting better security and risk management (31%), faster product development (20%) and improved efficiency (14%).

Fast-forward to 2025, and AI will play a key role in increasing top-line growth (30%), improving efficiency (26%) and reducing cost (16%). It will even play a role in recruiting talent and facilitating skills development, with which 48% of CIO respondents agreed. Further, a multicloud strategy and open approach to data architecture and standards can help address the key data concerns of leaders as their organizations undergo digital transformation.

For life sciences organizations like Johnson & Johnson, Rowena Yeo, Chief Technology Officer, expects AI to accelerate clinical trials and impact revenue generation. “Overall we’ve seen increased productivity, better risk mitigation from human error, and faster and more insight-driven decision-making,” says Yeo. “Having a multipronged, multicloud approach, and then incorporating APIs and microservices as part of our data architecture, are key for us.” She cites examples of AI-powered solutions, including disease-forecasting models, that helped Johnson & Johnson locate COVID-19 hot spots during the pandemic, and better target clinical trials.

Case Study

Johnson & Johnson

For life sciences organizations like Johnson & Johnson, technology leaders will invest in AI over the coming months and years. AI will power use cases from molecular modeling in drug discovery, to clinical trial acceleration, to end-user experience improvements with enhanced chatbots for employee and customer interaction. Acceleration has proven to be an important benefit of AI. Rowena Yeo, Chief Technology Officer at Johnson & Johnson, cites the example of AI-powered disease-forecasting models that helped Johnson & Johnson locate hot spots during the COVID-19 pandemic. Yeo also expects AI to better target and accelerate clinical trials, impacting revenue generation.

Johnson & Johnson

“Overall we’ve seen increased productivity, better risk mitigation from human error, and faster and more insight-driven decision-making.” 

“Having a multipronged, multicloud approach, and then incorporating APIs and microservices as part of our data architecture, are key for us.”

—Rowena Yeo, Chief Technology Officer and Global Vice President, Technology Services, Johnson & Johnson

Case Study

Walgreens Boots Alliance

Leaders across the healthcare industry are embedding AI into their strategy. In fact, 92% of leaders surveyed by MIT Technology Review agree that unifying their data platform for analytics and AI is crucial to their enterprise data strategy. Walgreens Boots Alliance developed its new data platform with a focus on the use of open standards and open data. That foundation supports use cases ranging from micro-fulfillment centers being driven by AI and robotics, to more precise prediction of inventory needs using analysis of omnichannel transaction data.

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“At our core, we support the use of open source technologies on our cloud data platform, which increasingly supports integration across different cloud providers. Open source standards and the ability to integrate cloud services across providers is important to our efforts to fully embed AI and machine learning in our business.”

—Mike Maresca, Global Chief Technology Officer, Walgreens Boots Alliance

How to future-proof

The research points to these key attributes to instill in your data and technology foundations: openness, multicloud, democratization. An open and unified platform like the Databricks Lakehouse Platform makes it possible to scale AI efficiently — and ultimately, create business value.