Empowering a secure autonomous AI future

AI is rapidly becoming the new digital frontier, much like how digital technology has revolutionized the way we work and live. As companies scale their AI initiatives and harness the power of generative AI, we are witnessing the dawn of a new era. This technology is not only solving complex problems and driving innovation but also fundamentally changing our work processes and daily lives. From industries to governments, the transformation is underway and securing an AI-powered future is more critical than ever.

If trust defines the limits of AI's possibilities, then ensuring security is crucial. In this article, I share my insights on the cybersecurity aspects of the four key technology trends highlighted in the Technology Vision 2025 report.

Convergence of autonomy and trust

Cybersecurity and gen AI are the top two emerging areas of innovation and technologies that are inspiring organizations’ vision or long-term strategy (Figure 1)– Accenture’s Technology Vision 2025.

This convergence underscores the importance of cybersecurity in shaping the future of organizations.

When foundation models cracked the natural language barrier, it kickstarted a shift that would forever change the fundamentals of software development and ecosystems. From a cybersecurity perspective, the shift toward gen AI-assisted software development and the rise of multi-agent systems present both exciting opportunities and significant challenges. While these advancements can enhance efficiency and personalization, they also introduce new vulnerabilities and attack surfaces.

The increased attack surface is a primary concern. As more systems become adaptive and personalized, the potential for advanced cyberattacks grows.

The Tech Vision 2025 survey reveals that 78% of executives believe digital ecosystems will need to be developed for AI agents just as much as for humans within the next 3–5 years. Continuous monitoring and incident response are vital in this dynamic environment. Ensuring that each agent is secure and that their interactions are monitored and controlled is crucial to maintaining the integrity of these systems. The nature of multi-agent systems also requires real-time threat detection and automated response mechanisms to quickly identify and mitigate security incidents.

The complexity in security management is another significant challenge. The World Economic Forum’s Global Cybersecurity Outlook 2025 report indicates that while 66% of organizations expect AI to have a major impact on cybersecurity in 2025, only 37% report having processes in place to assess the security of AI tools before deployment.

As Chapter 2 of our Digital Core research points out, in order to benefit from the advances of gen AI and multi-agent systems, organizations must move from traditional instruction-driven, predefined technology stacks to intention-based systems, powered by AI, with a cognitive architecture that mimics human-like thinking and learning. This is essential for an era characterized by deep generative AI integration, enabling machine operations and customization to meet specific industry needs.

However, the transition from static application architecture to intention-based frameworks and agentic systems adds layers of complexity for Security. Traditional security measures may not be enough to protect these dynamic and adaptive systems. New security paradigms and tools will need to be developed to address the unique challenges posed by multi-agent systems. Most current security tools rely heavily on manual configuration, policy updates and human oversight, making them resource-intensive and error-prone. By embracing next-generation solutions and incorporating gen AI, security leaders can overcome the limitations of manual, rules-based systems, making the security landscape proactive, adaptive and far more resilient to evolving cyber threats.

Protecting AI interactions

77% of executives agree their organizations will need to proactively build trust between personified AI and their customers – Accenture’s Technology Vision 2025.

From a cybersecurity perspective, the rush to integrate AI as a new customer touchpoint introduces a range of security challenges. Organizations must address them to ensure both brand differentiation and customer trust. While it's crucial to build personified AI experiences that reflect a brand's unique culture, values and voice, these efforts must be underpinned by robust security measures.

For example, data used to train and personalize AI models must be protected against breaches and unauthorized access. Additionally, the AI systems themselves need to be designed with security in mind, including regular updates and patches to guard against vulnerabilities. Organizations should also implement strong authentication and encryption protocols to safeguard customer interactions and data.

Moreover, as AI experiences become more complex, the risk of AI-driven phishing attacks and other forms of social engineering increases. The WEF’s Global Cybersecurity Outlook 2025 report highlights that 72% of respondents observed an increase in cyber risks over the past year. They point to a rise in cyber-enabled fraud, more frequent phishing and social engineering attacks and identity theft as the leading personal cyber risks. Brands must educate their customers about these risks and provide clear, secure channels for communication. By prioritizing cybersecurity alongside the development of unique AI experiences, organizations can not only differentiate themselves but also build a trusted and secure environment for their customers.

Robots under watch

74% of executives agree their organization sees the promise of adaptable and intelligent robots –Accenture’s Technology Vision 2025.

The rise of generalist robots that can quickly adapt to new tasks and collaborate with humans presents both thrilling possibilities and significant challenges. As these robots become more autonomous and integrated into physical environments like warehouses, the potential attack surface expands. Ensuring the security of these AI-driven systems is crucial to prevent unauthorized access, data breaches and malicious manipulation that could compromise safety and operational integrity.

For example, if a robot can learn from its interactions with humans, it must be protected against adversarial attacks that could corrupt its learning process or exploit vulnerabilities in its software. Additionally, seamless interaction between robots and warehouse staff requires robust authentication and authorization mechanisms to prevent unauthorized access and ensure that only trusted entities can interact with the robots.

The collaboration between robots and humans must be accompanied by a strong focus on cybersecurity, including regular security audits, continuous monitoring and the implementation of secure communication protocols. Building trust and collaboration between people and robots is not just about improving efficiency—it's also about ensuring that these systems are resilient against cyber threats.

Learning in sync

68% of executives report a need to upskill/reskill their employees in gen AI tools and technologies, within the next three years – Accenture’s Technology Vision 2025.

While the continuous improvement of AI through human interaction can lead to more complex and valuable tools, it also introduces new cybersecurity risks. As AI systems become more integrated into daily operations, they can become attractive targets for cyberattacks. Ensuring the security and integrity of these AI systems is crucial to prevent data breaches, unauthorized access and the control of AI outputs. However, as Global Cybersecurity Outlook 2025 report indicates, since 2024, the cyber skills gap has increased by 8%, with two in three organizations lacking essential talent and skills to meet their security requirements. What is more, this report also shows that only 14% of organizations are confident they have the people and skills they need today.

Leaders must prioritize not only the positive relationship between people and AI but also the robustness of their cybersecurity measures. This includes implementing strong access controls, regular security audits and continuous monitoring of AI systems. Training employees on the benefits, the potential risks and ethical considerations of AI is essential.

Our Tech Vision 2025 survey indicates that 95% of executives expect that the tasks their employees perform will moderately to significantly shift to innovation over the next three years. Equipping every employee with a digital sidekick is a powerful idea, but it must be done with a strong focus on security. Employees should be educated on how to recognize and report suspicious activities, and the organization should have clear protocols in place for handling security incidents involving AI tools. By fostering a culture of cybersecurity awareness, organizations can ensure that the benefits of AI are realized without compromising their security.

Next-level cybersecurity

In the rapidly evolving landscape of autonomous AI, cybersecurity is more critical than ever. To safeguard AI systems and ensure they remain robust and secure, organizations must adopt a proactive and comprehensive approach. Here are key insights on how to achieve next-level cybersecurity for autonomous AI:

1. Define your security roadmap

Start by conducting a thorough risk assessment to gain a clear understanding of your current AI security posture. This assessment should identify potential vulnerabilities and threats, allowing you to define a clear and actionable plan for remediation and future enhancements. A well-defined roadmap will serve as a guiding document, ensuring that all security efforts are aligned and effective.

2. Establish cross-functional alignment

Cybersecurity is not a solitary endeavor. It requires collaboration and alignment across various departments, including Business, Technology and Compliance. Ensure that key stakeholders from these areas are involved early and often in the security process. By fostering a collaborative environment, you can embed security into product roadmaps and operations, making it an integral part of your organization's culture.

3. Continuously evolve

The threat landscape is constantly changing, and so should your cybersecurity strategies. Adopt an agile mindset that emphasizes the importance of anticipating threats, responding quickly to vulnerabilities and driving incremental improvements. This approach ensures that your security measures remain aligned with the dynamic nature of business and technological advancements.

4. Prioritize ongoing learning

Train your workforce on the latest AI technologies, including gen AI and emerging data science approaches. This ongoing education ensures that your teams are well-versed in security, privacy and compliance best practices across the entire AI lifecycle. By investing in continuous learning, you can build a workforce that is not only skilled but also adaptable to new challenges.

By following these insights, you can build a robust cybersecurity framework that not only protects the autonomous AI systems but also supports long-term growth, innovation and trust.