Partner content: The growing sophistication of AI brings new risks and security concerns – global cybercrime costs are expected to rise to $12.2trn by 2031
As AI drives a new era, enterprises are reimagining their operating models leveraging intelligent automation and data-driven insights, to unlock opportunities for growth and innovation.
However, the growing sophistication of AI also brings new risks and security concerns, forcing senior decision-makers to rethink their cybersecurity strategies. From phishing to deepfake scams, cybercriminals are leveraging generative AI (GenAI) to scale and to enhance the precision and sophistication of their attacks. This amplifies the potential impact of cybercrime.
Cybersecurity Ventures projects global cybercrime costs to rise at 2.5% annually through to 2031, reaching $12.2 trillion a year as the threat landscape matures. To remain resilient, business leaders must adopt new models that prioritise speed, agility, and collaboration across ecosystems.
Shifting landscape of connectivity and security
The rise of connected devices, multi-cloud infrastructures and distributed ecosystems has created a network perimeter that is nearly impossible to define. This exposes organisations to risks that traditional security methods can no longer address.
This complexity demands a rethink of the traditional approach to cybersecurity. At the heart of this transformation lies the need for unified security architectures that operate seamlessly across distributed environments. This means integrating security directly into core network infrastructure and ensuring it adapts to the unique requirements of cloud, edge computing, and multi-device ecosystems.
Foundation for resilience
For enterprises, securing their networks is the first step in defending against cyber threats. While AI has given hackers new tools to exploit vulnerabilities, it also empowers organisations to create stronger defences through intelligent automation.
AI-powered self-healing networks can now identify and isolate breaches autonomously, detecting vulnerabilities faster than human teams could. These systems ensure connectivity even when an attack occurs, enabling businesses to maintain service reliability and protect customer trust.
Moreover, advanced connectivity solutions offer end-to-end visibility into network performance. By providing real-time insights into configurations, capacity, and performance, business leaders can optimise operational efficiency and stay ahead of potential threats.
Addressing a multi-cloud reality
With 92% of businesses adopting multi-cloud strategies, enterprises increasingly find themselves operating across diverse cloud environments. While multi-cloud adoption offers flexibility, it also increases security risks and operational complexity. For senior decision-makers, the priority is to create a consistent and secure environment that provides full visibility into the cloud infrastructure and improves business resilience.
Advanced cloud connectivity solutions enable this by offering on-demand bandwidth, rapid configuration capabilities and dynamic adaptability. For instance, connections can be set up in minutes using intuitive platforms, enabling faster response to fluctuating workloads or emerging threats. These tools offer great flexibility and help ensure business continuity when disruptions occur in any one cloud environment.
Another effective approach to improving resilience is adopting a distributed data processing model like edge computing. By shifting some of the data processing demands from the cloud to local devices, critical functions remain operational even during connectivity disruptions.
The move toward Zero Trust
As organisations expand their digital footprints, the Zero Trust model has emerged as the gold standard for cybersecurity. Zero Trust assumes that no user or device is trustworthy by default, implementing strict access controls and continuous validation across the network.
However, for large organisations, adopting Zero Trust is often daunting due to the complexity of integrating legacy systems with newer technologies. This includes embedding encryption, identity-based access protocols, least-privilege principles and real-time security checks across their networks.
Beyond technology, shifting to Zero Trust requires rethinking security policies and user experiences. Ensuring that security measures do not disrupt the experience of employees, partners, or customers is critical. This is not a quick fix but a process of constant iteration, requiring updated security controls and continuous improvement to adapt to evolving cyber threats.
Strengthening security with AI
AI’s capabilities extend far beyond enhancing network performance. In cybersecurity, AI acts as a force multiplier for overwhelmed IT teams, enabling faster threat detection, smarter prioritisation and more comprehensive responses in real time.
Consider the challenge of vulnerability management. Many organisations rely on fragmented systems and multiple threat monitoring tools that generate high volumes of data. Making sense of this data in time to prevent breaches is nearly impossible using manual methods. Here, AI’s ability to analyse user behaviour, network patterns, and system logs at scale is transformative.
Not only does AI identify vulnerabilities, but it also prioritises them based on risk, recommends immediate fixes, and even simulates potential attack scenarios.
For business leaders, the benefits are clear: faster detection and response mean reduced downtime, fewer disruptions and greater customer trust.
Responsible AI adoption
The promise of AI in cybersecurity is immense, but it doesn’t come without risks. Data privacy concerns, algorithmic biases and ethical challenges can undermine trust if not carefully addressed.
To address these issues, it is important to embed responsible AI practices into every stage of the AI lifecycle. Business leaders can do that by creating data privacy guidelines to protect sensitive customer information and by introducing effective mechanisms for detecting and eliminating AI bias. Ensuring human oversight and fostering a culture of security awareness and continuous education is also essential for minimising the risks of AI.
Balancing innovation and security
The rise of agentic AI brings both significant threats and powerful tools for defence for organisations across all industries. Communication Service Providers (CSPs) occupy a critical position at the intersection of connectivity, data flow and digital environments, so they can play a larger role in the global cybersecurity ecosystem.
By embedding AI and intelligent connectivity into their core operations, CSPs can innovate faster and redefine their business models with new security service offerings. This will allow them to unlock new opportunities for growth for both them and their customers.
To succeed in this AI-driven era, organisations must adopt strategies to address the complex risks posed by evolving cyber threats. Frameworks like Zero Trust, AI-driven tools for threat detection and management, and flexible security architectures for cloud and edge environments, are essential. Equally important is embedding responsible AI practices. This includes fostering trust through data privacy and ethical safeguards and ensuring collaboration across ecosystems. By balancing innovation with robust protection, CSPs and enterprises will be able to transform confidently and succeed in the AI-driven economy.
