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AI’s Promises and Challenges
Interest in AI exploded just a short time ago with the advent of public-facing large language models powering generative AI (GenAI) applications.
A study by Cisco4 shows that companies are turning to AI to automate business processes (40%), improve efficiency (63%), drive innovation (51%), and improve customer experiences (47%). Leaders also aim to improve their risk management practices and reduce business risk overall with the help of AI (35%).
Organizations are also concerned about AI-associated risks5, with security breaches topping the list, as cited by 37% of survey respondents. A third of business leaders (33%) are worried about the possibility of customer data being exposed via AI usage, with concerns about related regulatory risks close behind (29%). Feared consequences from the inability to properly manage AI applications and its use of data include damage to brand reputations and revenue loss (both cited by 23% of respondents).
This push-and-pull of AI benefits and risks hampers business leaders' efforts to sort through emerging technologies and build compelling use cases around AI. To get where they need to go, they must lay the right foundational elements. Principles should not rely on government regulations, which frequently play catch up to fast-evolving technology.
A study by Cisco4 shows that companies are turning to AI to automate business processes (40%), improve efficiency (63%), drive innovation (51%), and improve customer experiences (47%). Leaders also aim to improve their risk management practices and reduce business risk overall with the help of AI (35%).
Organizations are also concerned about AI-associated risks5, with security breaches topping the list, as cited by 37% of survey respondents. A third of business leaders (33%) are worried about the possibility of customer data being exposed via AI usage, with concerns about related regulatory risks close behind (29%). Feared consequences from the inability to properly manage AI applications and its use of data include damage to brand reputations and revenue loss (both cited by 23% of respondents).
This push-and-pull of AI benefits and risks hampers business leaders' efforts to sort through emerging technologies and build compelling use cases around AI. To get where they need to go, they must lay the right foundational elements. Principles should not rely on government regulations, which frequently play catch up to fast-evolving technology.
Getting ready for AI
Gartner recommends approaching AI implementations with three essential elements in place that are designed to safeguard data and ensure regulatory compliance.6
1. AI-ready cybersecurity must be built with an understanding of new attack vectors enabled by AI.
For example, in some situations, GenAI could be tricked into divulging (or hiding) information—some of which may be sensitive in origin. As with every aspect of cybersecurity, people are part of the solution. In this case, employees need training on the data security and regulatory risks of using AI. They also need the guidance of company-created acceptable use policies (AUPs) for AI applications—including public GenAI services.
2. AI-ready data must be:
For example, in some situations, GenAI could be tricked into divulging (or hiding) information—some of which may be sensitive in origin. As with every aspect of cybersecurity, people are part of the solution. In this case, employees need training on the data security and regulatory risks of using AI. They also need the guidance of company-created acceptable use policies (AUPs) for AI applications—including public GenAI services.
2. AI-ready data must be:
- Ethically governed
- Immune to unintended data leaks
- Unbiased (by being gathered from diverse sources)
- Enriched with effective rules and tags
- And—most of all—free of inaccuracies
Accurate data may require double-checking and adjustments by humans to avoid falling victim to that age-old trap of data processing: garbage in, garbage out. A professional readiness assessment can help organizations discover, protect, and properly govern their data.
3. AI principles define how your organization uses AI, providing guidelines for everyone around what they should and should not do with AI.
These principles should be based on your organization’s core values. As Gartner states, “Without a clear definition of the lines you won’t cross, it will be impossible to know when you’ve crossed one.” The principles must be precise and written in plain language, providing clear guidance to managers and frontline workers on technology purchasing decisions, accessible use cases, and data handling. Principles should not rely on government regulations—which frequently play catch-up to fast-evolving technology.
3. AI principles define how your organization uses AI, providing guidelines for everyone around what they should and should not do with AI.
These principles should be based on your organization’s core values. As Gartner states, “Without a clear definition of the lines you won’t cross, it will be impossible to know when you’ve crossed one.” The principles must be precise and written in plain language, providing clear guidance to managers and frontline workers on technology purchasing decisions, accessible use cases, and data handling. Principles should not rely on government regulations—which frequently play catch-up to fast-evolving technology.
AI and Compliance: What You Need to Know
Only 39% of North American organizations surveyed say they have an AI governance body to oversee responsible AI.
AI is on almost every business leader’s mind, presenting an incredible opportunity to improve productivity—for those who can properly harness its power. In this eBook, we’ll walk you through the security and compliance risks of AI.
We’ll also share some practical ways to mitigate these risks through preparation, policies, and technology.
Embedded AI and Trusted Services
Given AI’s fast-evolving nature, many organizations choose to deploy AI solutions embedded in hardware and software from vendors they already trust and use. For example, Microsoft recently announced7 Copilot+ PCs with powerful and efficient neural processing units (NPUs) that reduce the need to process AI in the cloud. NPUs increase the speed and performance of AI applications without compromising battery life.
Announcements by other major technology companies—including Apple, Dell, and NVIDIA—herald a new era of embedded AI devices and applications. These products promise to streamline and accelerate AI-powered workloads by cutting the lag associated with communicating with cloud sources. They also enhance privacy by keeping sensitive data on devices instead of sharing it with public cloud services.
These new AI tools, combined with AI-ready cybersecurity, AI-ready data, and clear AI principles, can all put businesses and their users on the path to realizing the full benefits of AI without unnecessary compliance and data protection risks.
And for those still short on the skillsets they need to help AI make good on its promises, a trusted partner like Connection can lend a hand. For example, our Microsoft 365 Copilot Readiness Assessment helps organizations prepare their data for use with Copilot, Microsoft’s new productivity-enhancing AI tool. The assessment is a comprehensive, customized evaluation of an organization’s data environment that helps managers apply best practices for data loss prevention, security, compliance, and more. Read our Readiness Assessment Solutions Brief to learn more.
Announcements by other major technology companies—including Apple, Dell, and NVIDIA—herald a new era of embedded AI devices and applications. These products promise to streamline and accelerate AI-powered workloads by cutting the lag associated with communicating with cloud sources. They also enhance privacy by keeping sensitive data on devices instead of sharing it with public cloud services.
These new AI tools, combined with AI-ready cybersecurity, AI-ready data, and clear AI principles, can all put businesses and their users on the path to realizing the full benefits of AI without unnecessary compliance and data protection risks.
And for those still short on the skillsets they need to help AI make good on its promises, a trusted partner like Connection can lend a hand. For example, our Microsoft 365 Copilot Readiness Assessment helps organizations prepare their data for use with Copilot, Microsoft’s new productivity-enhancing AI tool. The assessment is a comprehensive, customized evaluation of an organization’s data environment that helps managers apply best practices for data loss prevention, security, compliance, and more. Read our Readiness Assessment Solutions Brief to learn more.
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- https://blogs.microsoft.com/blog/2023/11/02/new-study-validates-the-business-value-and-opportunity-of-ai/
- https://www.cisco.com/c/m/en_us/solutions/ai/readiness-index.html
- https://news.microsoft.com/source/wp-content/uploads/2023/11/US51315823-IG-ADA.pdf
- https://www.cisco.com/c/dam/m/en_us/solutions/ai/readiness-index/documents/cisco-global-ai-readiness-index.pdf
- https://blogs.microsoft.com/blog/2023/11/02/new-study-validates-the-business-value-and-opportunity-of-ai/
- Gartner, 2024, Get AI Ready — What IT Leaders Need to Know and Do
- https://blogs.microsoft.com/blog/2024/05/20/introducing-copilot-pcs/
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