From vision to reality: A 5-step playbook for unified automation and AI

2025년 12월 4일Harper Buete3분 읽기

Twenty-eight percent of businesses surveyed in the recent S&P Global Market Intelligence 451 Research report, “The value of a unified automation platform,” responded that their company uses 50-100+ tools that don’t seamlessly integrate. This widespread adoption of disparate solutions, often driven by a "do it yourself" mentality, can lead to overwhelming tool sprawl. The resulting lack of interoperability directly hinders innovation, fragments data insights, and ultimately undermines the effective delivery of AI solutions.

As automation and AI become increasingly interdependent, systems must be capable of cohesive information exchange. This critical need points directly to platform engineering (PE), which enables self-service capabilities through a, "bidirectional exchange of both data and workflows," between tools. A unified automation platform isn't merely a convenience, it's the strategic foundation for AI development and deployment.

1. Assess your current state

Take a moment to evaluate your organization's automation maturity:

Are your IT operations bogged down by manual, repetitive tasks across various domains: Network, security, cloud, and infrastructure?
Do different teams (IT Ops, DevOps, SecOps, Network Ops, Line of Business) grapple with inconsistent automation tools and processes, fostering silos and inefficiency?
Is your current automation fragmented, making it challenging to scale or maintain consistency across hybrid and multicloud environments?
Can you accurately measure the ROI of your automation efforts, and pinpoint where automation could deliver the most significant time and cost savings?
Do you have a clear strategy for integrating emerging technologies like AI into your IT operations? Is your automation foundation truly prepared to support these initiatives?

2. Build your business case

The next hurdle is effectively articulating the value of a unified platform to your stakeholders and decision-makers. Rather than simply stating the need, building a robust business case involves concrete steps and data-backed arguments:

Quantify the cost of inaction and tool sprawl: Detail the financial impact of maintaining a fragmented environment, including lost productivity and manual work. The S&P Global Market Intelligence 451 Research report shows that 28% of businesses use 50-100+ non-integrated tools, highlighting significant interoperability challenges.

Define and measure tangible benefits: Outline how a unified platform will lead to efficiency and cost savings by reducing manual processes and consolidating tools. Red Hat Ansible Automation Platform’s automation dashboard uses the automation calculator to track and measure the total value of your automation efforts by time and financial savings. Notably, S&P Global Market Intelligence 451 Research indicates that increased efficiency and productivity are primary drivers for 54% of unified IT automation platform adopters.

Demonstrate clear ROI and strategic alignment: Present a clear return on investment analysis. The Ansible Automation Platform automation dashboard helps you monitor key metrics such as time savings, project success, and ROI to demonstrate the impact of your automation and showcase wins to stakeholders. An integrated approach translates directly to concrete business benefits like faster deployment and improved consistency, which are critical for AI readiness.

3. Choose the right platform

As AI increasingly drives automation, it's important to implement a robust policy enforcement approach with Ansible Automation Platform. This strategy effectively puts guardrails in place for AIOps, so operations remain within defined business boundaries. When an event triggers your observability tools, policy enforcement automatically validates that actions align with your established policies. If a conflict is detected, the process pauses for a human decision-maker, assuring users their automation is consistently running in line with business policies and regulatory requirements.

4. Adopt a phased approach

A prime example of proactive automation is Event-Driven Ansible, enabling immediate, automated responses without manual intervention. AI and observability tools act as sentinels, notifying Event-Driven Ansible of critical events like Linux or Windows service errors. Pre-defined rulebooks then use Ansible Automation Platform, often in conjunction with AI, to diagnose the issue and determine a solution, demonstrating clear cost savings by reducing downtime. Playbooks collect data for further analysis, delivering tangible benefits like improved consistency and a stronger foundation for AI readiness.

5. Measure success

With the implementation of any new platform or system, demonstrating its value is key. Here are a few key performance indicators (KPIs) to consider for measuring automation success:

Decreased time spent on configuring and maintaining automation workflows. Automate provisioning, configuration, and ongoing compliance.
Faster response times: Did your team's response times to business needs accelerate, particularly in incident response and remediation?
Improved risk posture: Were security blind spots reduced? Was there faster vulnerability remediation?
Ease of AI adoption: Was your automation foundation stable and prepared when integrating AI into your operations?

Embrace the future of IT by taking these strategic steps towards a unified automation and AI platform. The path to unlocking your full IT potential begins now.

Read the infographic: 3 reasons why enterprises need a unified automation platform.