2024 Global Report on Generative AI

Source: Survey Report: The 2024 GLOBAL REPORT ON GENERATIVE AI — Breakthroughs & Barriers by BigID

Executive Summary

The 2024 Global Report on Generative AI highlights the rapid adoption of generative AI in workplaces, transforming business processes, enhancing productivity, and optimizing decision-making.

Despite these benefits, organizations face significant challenges in data security, privacy, governance, and compliance. BigID, partnering with YouGov, surveyed 327 IT decision-makers and influencers worldwide to provide insights into these issues.

Current & Future AI Adoption

Adoption Rates: 83% of organizations are utilizing or planning to adopt generative AI, with 51% actively using it and 32% planning to adopt it soon. Only 17% have no plans for adoption due to data management and security concerns.

Adoption Timelines: Organizations planning to adopt AI within 1–2 years must prioritize data security and governance. Those with longer timelines should focus on comprehensive AI strategies and continuous monitoring of technological and regulatory changes.

Purpose of Adopting AI

Primary Applications: The top uses of generative AI include IT operations management (51%), conversational interfaces like chatbots (47%), and customer service operations (43%).

Efficiency and Innovation: AI is leveraged to drive efficiency and innovation, necessitating stringent data management policies to ensure data integrity and security.

Barriers to AI Adoption

Talent and Infrastructure: 67% of non-adopting organizations cite a lack of skilled talent and technical infrastructure as major barriers.

Data Governance: Challenges in data governance and maintaining data integrity are significant hurdles, highlighting the need for thorough data visibility and control.

Key Decision-Making Criteria for Adopting AI

Security and Privacy: Security risks, such as data breaches (36%), and privacy concerns (35%) are the top decision-making factors.

Transparency: Organizations prioritize transparency in AI decisions to ensure ethical and accountable AI practices.

Challenges When Implementing AI

Data Security: 50% of organizations using AI identify data security as the biggest challenge, necessitating advanced solutions for data protection and access control.

Cross-Functional Collaboration: Effective AI implementation requires collaboration across IT, security, legal, and business departments.

Adversity When Using Generative AI

Adverse Outcomes: Nearly half of the organizations (49%) report adverse outcomes from AI usage, with data breaches being the most common (32%).

Risk Management: Organizations must implement robust security measures, proactive risk management, and comprehensive data breach response plans.

AI Concerns

Top Concerns: Security risks (56%), privacy risks (64%), and transparency (60%) are the top concerns.

Sector-Specific Challenges: Healthcare, education, and government sectors face unique challenges requiring stringent data protection and AI governance strategies.

Protecting Sensitive Data When Using AI

Data Protection Strategies: Common strategies include data encryption, continuous employee training, data retention and minimization, access control, and data quality monitoring.

Lifecycle Management: Effective data protection involves comprehensive lifecycle management, from data collection to deletion.

Securing AI

Security Confidence: 73% of organizations are not fully confident in their data security measures for generative AI.

Essential Security Measures: Implementing strict access controls, monitoring AI applications, and enforcing data security policies are critical.

Governing AI

Data Governance: Effective governance is crucial for ensuring the reliability, ethical conduct, and regulatory compliance of AI applications. Regular audits and stakeholder involvement are essential.

Policy Development: Continuous review and adaptation of governance policies to align with evolving AI technologies are necessary.

Meeting AI Regulations & Compliance

Regulatory Concerns: 72% of organizations are concerned about meeting future AI regulations. Establishing a robust governance framework and conducting Privacy Impact Assessments (PIAs) are imperative.

Compliance Framework: Organizations must ensure data protection, transparency in AI decision-making, and adherence to legal standards.

Current Sentiment on the Future of AI

• Positive Outlook: 72% of organizations foresee a positive impact of generative AI in the next five years, anticipating significant innovations and enhanced operational efficiency.
• Areas of Impact: Healthcare, finance, retail, education, and environmental conservation are expected to benefit significantly from AI advancements.

Conclusion

The report emphasizes the transformative potential of generative AI, while also underscoring the importance of robust data security, privacy, governance, and compliance measures.

Organizations must adopt comprehensive strategies to manage these challenges effectively and ensure the ethical and secure use of AI technologies.