AI agents revolutionise business & cybersecurity with automation
The integration of artificial intelligence (AI) agents into business and cybersecurity operations is rapidly shifting from experimental trials to real-world deployment, as organisations across sectors seek to harness the power of automation, efficiency, and data-driven decision-making. Recent commentary from senior technology leaders underscores both the gains and the challenges facing enterprises as they embed AI agents into core processes.
In the realm of cybersecurity, the accelerating sophistication of threats driven by AI is a growing concern. Fabio Fratucello, Field Chief Technology Officer World Wide for CrowdStrike, highlights that malicious actors are increasingly using AI, including large language models (LLMs), to launch more convincing phishing scams, business email compromise, and social engineering attacks. "AI is lowering the barrier to entry for adversaries, allowing them to automate social engineering, misinformation campaigns, and credential harvesting at unprecedented speed and scale," Fratucello notes, citing findings from CrowdStrike's 2025 Global Threat Report.
This surge in AI-powered attacks is amplifying the pressure on security teams, already hampered by overwhelming alert volumes and a shortage of skilled analysts. According to Fratucello, the key to regaining the upper hand lies in deploying AI-enabled tools that automate detection and triage of threats. CrowdStrike's Charlotte AI, for instance, uses machine learning to validate and prioritise security alerts with more than 98% accuracy. By automating repetitive tasks, Charlotte AI reportedly saves security teams up to 40 hours per week, enabling them to concentrate on proactively hunting advanced threats and halting breaches before escalation.
Importantly, Charlotte AI operates within a "bounded autonomy framework," allowing organisations to set specific parameters for automated decision-making. Analysts retain control by defining thresholds and determining when human review is required, ensuring that the balance between automation and human oversight is maintained. Fratucello stresses, "This combination of machine speed and human-defined guardrails returns the AI advantage to defenders and ensures organisations can operate at the speed of threats."
Elsewhere in the enterprise technology space, companies are contending with the challenge of bringing AI agents out of the prototype lab and into large-scale, reliable production. Nick Eayrs, Vice President, Field Engineering, APJ, at Databricks, observes that while enthusiasm for AI agents is high, moving beyond proof-of-concept still eludes many organisations. "The challenge is not just building them – it is making them scalable, efficient and reliable enough to stand up in the real world," Eayrs explains. Too often, businesses rely on trial-and-error approaches and are forced into trade-offs between operating costs and performance, which undermines the requirements of enterprise-grade use cases.
In response, Databricks has launched Agent Bricks, a system designed to streamline AI agent creation using real enterprise data. Agent Bricks deploys automated evaluation benches, generates synthetic data, and leverages custom judges to test agent quality and efficiency. This reduces the manual, repetitive work typically involved in agent development, freeing AI engineers to focus on higher-value tasks. Eayrs says that common industry uses of such AI agents already include structured information extraction, knowledge assistance, customised data transformation, and multi-agent orchestration. "Ultimately, it is about building production-grade AI agents that are useful, reliable and ready for deployment — that is what we are focused on," he adds.
The potential benefits of AI agents are also being demonstrated at the customer coalface. At the property services company hipages Group, AI agents have transformed backend operations. Jeremy Burton, Chief Technology Officer, reports that the introduction of Agentforce has reduced lead response time by 60% and automated verification processes, dramatically speeding up license and registration checks for tradespeople. "Agentforce and Data Cloud are now a core part of our ecosystem, helping us connect better with our customers and tradies," he states. By bringing disparate data and customer touchpoints onto a unified platform, hipages has streamlined work for staff and improved satisfaction levels for both customers and end users.
Hospitality firm Urban Rest has leveraged Agentforce to scale up its service operations in step with rapid growth. Jeff Baars, Chief Commercial Officer, explains that Agentforce's centralised knowledge base provides round-the-clock self-serve support for guests, enabling the business to operate without on-site staff across 800 properties in four countries. This has increased productivity by 50% for the operations team, while anticipated field service visits have dropped by up to 40%. Baars notes, "Agentforce empowers our guests with instant, self-serve access to everything they need to know about their apartment, freeing up our guest relations team to focus on support that requires a human touch."
At Kudosity, an AI agent named 'Emily' now handles up to 40% of general customer support queries, ensuring prompt responses and reducing the workload for support staff. When a query is too complex, Emily refers it to a human agent, preserving personalised service where it matters most.
The evolving landscape of AI agents in the real world demonstrates the transformative potential of the technology, balanced by the need for systematic deployment, human oversight, and ongoing adaptation to rapid changes in both business and cybersecurity domains. As enterprise adoption accelerates, the focus is squarely on building reliable, scalable, and human-aligned AI agents that deliver tangible benefits across sectors.
