IDC dropped a bombshell forecast this week: agentic AI will command over 26 percent of worldwide IT budgets—$1.3 trillion—by 2029, up from less than 2 percent today. This massive shift is already playing out as enterprise giants roll out production-ready agent platforms that promise to transform how businesses operate.

Major Platform Launches Reshape Agent Development

Broadcom unveiled a comprehensive suite of AI-driven enterprise solutions targeting automation, security, hybrid cloud management, and edge computing. For developers, this represents a significant expansion of enterprise-grade infrastructure specifically designed to support next-generation AI workloads at scale.

HPE launched Mist Agentic AI for self-driving network operations, automating troubleshooting, anomaly detection, and network optimization. This platform demonstrates how specialized agents can achieve greater uptime, resilience, and efficiency in critical infrastructure—a template developers can follow for building domain-specific automation solutions.

Hyland introduced two groundbreaking frameworks: the Enterprise Context Engine and Agent Mesh. These tools centralize contextual data and orchestrate agent-based workflows across distributed business functions, solving the integration challenges that have plagued enterprise AI deployments.

Real-World ROI Numbers Emerge from Production Deployments

Fortune-class organizations are reporting substantial returns from agentic AI implementations. Fortune 50 Financial Services companies achieved 180% growth in agent, app, and automation volume while maintaining security standards. A Fortune 20 Technology company remediated 90% of existing vulnerabilities within 4 months using just 2 full-time employees supported by AI agents.

The business case extends beyond cost savings. Fortune 50 Pharmaceuticals reported that 82% of people developing AI systems are not professional developers—yet they successfully deployed 2,000 instances of agents and apps across their organization. This democratization of AI development is accelerating time-to-value for business process automation.

AI agents are eliminating job displacement fears while creating new roles. Contact centers using AI for routine inquiries are transforming agents into "super-agents"—strategic problem-solvers focused on complex, high-value interactions. Only 36% of organizations feel very confident in their AI training programs, despite 95% identifying upskilling as a strategic priority.

Practical Starting Points for AI Agent Adoption

For those new to agentic AI, think of these systems as sophisticated digital assistants that can complete multi-step tasks independently. Unlike simple chatbots that respond to questions, AI agents can perform tasks, make decisions, and interact with multiple systems to achieve specific goals.

Zocks expanded their AI assistant capabilities with native Zoom and Webex meeting support, plus enhanced workflow features like 'Ask Anything' and Search & Replace for faster meeting note edits. These practical applications show how agents can immediately improve daily productivity without requiring technical expertise.

The emergence of specialized frameworks like Hyland's Agent Mesh means businesses can now orchestrate multiple AI agents working together—imagine having a team of digital specialists handling your routine operations 24/7 while your human team focuses on strategy and innovation.

Security and Identity Management Take Center Stage

A critical development for all stakeholders: AI agents are creating new classes of identity risk that require immediate attention. As agents operate across multiple systems with inherited permissions, organizations need robust identity security strategies to prevent potential vulnerabilities while enabling innovation.

Zenity reported that companies using their AI agent security platform achieved 90% reduction in security violations and 95% automatic remediation of high-risk violations. This demonstrates that proper security frameworks can enable rapid AI agent adoption without compromising organizational safety.

The takeaway for developers: build identity management into agent architectures from day one. For business leaders: budget for security alongside agent implementation. For newcomers: understand that AI agents require different security approaches than traditional software—but proven solutions already exist.