Automation and AI can help you streamline day-to-day operations while creating room for innovation.

According to The Futurum Group, organizations are dealing with heterogeneous infrastructure, rising security risks, and the need to integrate new technologies like AI with existing systems. A strategic automation approach addresses this by:

• Reducing manual work: Routine, repetitive tasks are automated, which cuts down on human error and speeds up delivery.
• Standardizing processes: Automation creates consistent, repeatable workflows across your IT environment, improving reliability and compliance.
• Scaling operations: You can manage more systems and applications without linearly increasing headcount.

Futurum Group research shows that 36% of organizations have already shifted skilled resources away from manual tasks to AI-driven automation. This not only improves efficiency but also frees IT staff to focus on higher-value, strategic work.

Platforms like Red Hat Ansible Automation Platform support a wide range of use cases—operating system configuration, cloud and network automation, virtual infrastructure management, and application delivery. When combined with generative AI (such as Ansible Lightspeed with IBM watsonx Code Assistant), teams can develop automation content faster, even if they’re not deep automation experts.

The result is a more manageable IT landscape where complexity is handled by automation, and your teams can reimagine how they spend their time—shifting from firefighting to innovation.

The skills gap is a real constraint on IT and application delivery, and automation can play a practical role in closing it.

IBM estimates that 120 million workers in the world’s largest economies will need to be reskilled in the coming years to keep pace with AI and automation. The Futurum Group also found that 50% of businesses admit they don’t have sufficient skill-development strategies in place.

Automation and generative AI help in several ways:

• Lowering the barrier to entry: Low-code tools and AI-assisted automation let non-experts create and maintain automation content.
• Using natural language: AI can generate automation from natural language prompts, reducing the need for deep scripting or platform expertise.
• Freeing time for learning: When routine tasks are automated, your team can focus on higher-value work and skill-building.

Red Hat addresses this with both technology and training:

• Ansible Lightspeed with IBM watsonx Code Assistant helps teams generate full Ansible playbooks and other automation artifacts more quickly, even if they’re new to automation.
• Red Hat training programs support all skill levels, helping teams build confidence in automation while managing complex environments.

By combining automation, generative AI, and structured training, you can rethink how work is distributed, make better use of existing talent, and gradually build the skills you need instead of relying solely on hiring in a tight market.

Modernizing legacy systems while rolling out AI initiatives is challenging, especially when technical debt has built up over time. The Futurum Group notes that this technical debt is a major hurdle in modernization efforts, yet 54% of enterprises already use AI in production applications, which increases infrastructure demands.

Red Hat’s approach is to use automation and AI to manage both your heritage and modern environments in a coordinated way:

• Automating legacy and modern stacks: Red Hat Ansible Automation Platform can handle operating system automation, cloud and network automation, application delivery, and virtual infrastructure management across traditional and cloud-native environments.
• Supporting AI workloads: Automation helps provision, configure, and operate the infrastructure required for AI-based applications, while still managing existing systems.
• Event-driven automation: Systems can automatically respond to real-time events and alerts, helping reduce downtime and improve mean time to resolution (MTTR).
• Virtualization and hybrid support: Red Hat’s virtualization and hybrid cloud capabilities provide flexibility across public cloud, private cloud, cloud-native, and virtualized environments.

On top of this, Ansible Lightspeed with IBM watsonx Code Assistant accelerates the creation of automation needed for migrations and ongoing operations, making it easier for teams to manage complex modernization projects.

In practice, this means you can:

• Gradually migrate legacy workloads to modern platforms with automated, repeatable processes.
• Introduce AI into existing applications while keeping infrastructure manageable.
• Use automation as a “force multiplier” to get more value from current investments—from Cisco devices to Linux, Windows, cloud-native, and virtualized environments.

This approach helps you reshape your IT landscape over time, rather than through disruptive, one-time overhauls, while keeping operations stable and aligned with long-term business goals.