Human trust in AI: 5 challenges and how to overcome them
Humans don't have trust in AI for many reasons, but without trust, AI can't reach its full potential.
Across industries, the buzz around generative AI is inescapable. Conversations around AI among business professionals increased by an astounding 70% over the past year, according to a recent LinkedIn report.
But as business leaders plan ways to put gen AI to work in their digital transformation, the technology raises ethical and cloud data protection issues.
For example, a survey conducted by PWC indicated that 69% of senior executives will use gen AI for cyber defense in the next 12 months.
Using gen AI-tools to analyze emails and messages for malicious code and phishing attacks brings up questions about using data for training models and potential leaks.
How can businesses harness the full power of AI while safeguarding sensitive data?
Humans don't have trust in AI for many reasons, but without trust, AI can't reach its full potential.
A low-risk approach may seem like better data protection and security, but it can hamstring an organization’s ability to address internal and external customer requirements and unlock the value of the data.
In some cases, it may even lead to shadow IT projects with uncontrolled data sharing, potentially feeding the large language models behind gen AI.
Although done with good intentions, the consequences of your data turning up in the results of a gen AI conversation can be very harmful to your company and its reputation.
Ultimately, the key to harnessing the full power of AI while safeguarding sensitive information lies in choosing a cloud provider that not only understands these data protection intricacies, but also prioritizes them.
Data compliance encompasses the standards and regulations in place to ensure data is secure, protected from data theft, misuse, and loss. Here's a primer on getting started.
Cloud delivery options enable you to manage and protect your data in accordance with local and global laws, and regulations. There are flexible options to meet your internal needs for security and your risk appetite.
From public cloud and hybrid cloud to private and sovereign clouds, organizations have a range of options for driving innovation, regulatory compliance, and security.
Depending on your risk preference, for some data processing scenarios, you’ll need a cloud that might be less feature rich but has additional security controls. But in other cases, a standard public cloud offering might provide greater flexibility at a lower cost.
It also could be that your risk appetite can evolve if certain conditions are met, such as where data is hosted or how encryption keys are controlled with the result that greater value can be extracted from that data.
SAP helps customers transform their systems and processes within their technology boundaries to maintain security, compliance, and governance of data in the cloud.
As organizations aim to optimize operations, improve CX, and drive innovation, they're turning to various cloud types. Learn the pros and cons so you can make the right decision for your org.
Whether it’s adhering to regional data storage laws, meeting stringent government standards, or ensuring industry-specific certifications, there’s a cloud to meet your needs.
Organizations that make the right cloud choice can navigate the complexities of the modern digital landscape with confidence. They also can establish a resilient defense against ever evolving cyber threats, safeguarding their most golden asset, data.
In doing so, they not only protect their data, but foster an environment where AI and digital transformation can flourish responsibly and ethically.