A recent Salesforce survey reveals that 84% of chief information officers, or CIOs, believe artificial intelligence is a game changer for businesses; however, only 11% have fully implemented AI systems. The survey, which included 150 verified CIOs from companies with over 1,000 employees, indicates that while strong executive support for AI exists, 68% of CIOs feel their business partners have unrealistic expectations regarding the return on investment. CIOs allocate four times more of their budgets to data initiatives than to AI projects, with a median of 20% spent on data management compared to just 5% on AI. The survey highlights that CIOs prioritize data security and infrastructure before diving deeper into AI adoption. With 75% of CIOs describing their organizations as being in the experimental stage of AI adoption, it is evident that while the potential of AI is recognized, many organizations are still navigating the best path forward.
A recent report from MIT Technology Review Insights, in partnership with Snowflake, reveals that 78% of businesses are hindered in capitalizing on artificial intelligence due to inadequate data foundations. The report highlights that 95% of organizations face challenges implementing AI, and only 22% of business leaders feel “ready” to engage with AI technologies. Key findings show that 72% of businesses aim to enhance efficiency with generative AI, yet many struggle with data governance and quality. Baris Gultekin, Head of AI at Snowflake, emphasizes that a robust data foundation is essential for unlocking AI’s potential and driving market innovations. Companies that have invested in strong data strategies are beginning to see the benefits of AI, reinforcing the need for organizations to prioritize their data foundations.
A recent study by researchers at Lehigh University and Seattle University reveals that emphasizing human biases can enhance patient acceptance of AI in healthcare. Nearly 1,900 participants were involved in six experiments, demonstrating that when patients were reminded of inherent biases in human decision-making, they viewed AI as more trustworthy and fair. The findings indicate that while many still prefer human healthcare, awareness of bias significantly reduced resistance to AI recommendations.
Why do we care?
We can learn a lot from medicine about the application of communications. Remember, we’ve seen data that AI can be more empathetic than some doctors, and while AI is biased… so are humans. There isn’t a perfect solution out there. Providing context is key for using these tools.
AI is about data. Data management, governance and establishing the foundation for data is the key unlock right now… and also very useful even without applying AI.