Automation and AI are transforming IT operations, enabling faster, smarter, and more efficient delivery of services and solutions. But how can you leverage these technologies effectively and responsibly in your IT operations? Here are some best practices to help you get started.
Before you dive into automation and AI, you need to understand your current capabilities and gaps, as well as your goals and challenges. You can use frameworks such as the IT Automation Maturity Model or the AI Maturity Model to assess your automation and AI maturity across different dimensions, such as strategy, governance, data, skills, tools, and culture. This will help you identify where you are, where you want to be, and what actions you need to take to get there.
Automation and AI can be applied to various IT operations tasks, such as monitoring, incident management, configuration management, security, testing, and deployment. However, not all tasks are equally suitable or beneficial for automation and AI. You need to define your automation and AI use cases based on your business needs, value proposition, feasibility, and risks. You also need to prioritize your use cases based on their impact, urgency, and complexity.
Begin with the Familiar: Initiate your automation journey by focusing on "good." Start with well-established tech and data pipelines, where quick wins can showcase tangible progress. Avoid the pitfall of commencing with overly complex tech and datasets or tackling the largest business units or geographic locations right away.
In addition, consider creating a culture of openness and providing users with the tools to experiment with automation and AI as a use case. This approach has the potential to uncover novel applications, empower individuals, and instill a culture of continuous learning and adaptability. This will require an effective implementation strategy that ensures consumers will have access to tools and models in a secure environment - a Tech Playground that is user centric!
There are many automation and AI tools available in the market, each with its own features, benefits, and limitations. You need to choose your automation and AI tools based on your use cases, requirements, budget, and integration needs. You also need to evaluate the quality, reliability, and scalability of the tools, as well as their compatibility with your existing IT infrastructure and processes. Some examples of automation and AI tools are Ansible, Chef, Puppet, Jenkins, Kubernetes, TensorFlow, PyTorch, Watson, and Azure AI.
Remember that AI is intended to augment and not replace your existing human team. While AI can help in a lot of use cases, be sure to only implement AI tools in situations where your humans will be able to effectively manage and leverage the tools.
Craft a Pragmatic Operational Plan: Lay the foundation for automation resilience with a well-grounded operational plan that acknowledges the dynamic nature of the data and tech landscape.
Once you have chosen your automation and AI tools, you need to implement your automation and AI solutions in a systematic and iterative way. You need to follow the best practices of software development, such as agile methodology, DevOps principles, testing, documentation, and version control. You also need to ensure that your automation and AI solutions are aligned with your IT governance policies, standards, and procedures. You should also monitor and measure the performance, efficiency, and quality of your automation and AI solutions, and make adjustments as needed.
Embrace Adaptation: Acknowledge that your data and tech automation implementation plan will naturally evolve, often undergoing 3-4 significant changes within the initial year. Keeping your team, executives, and board informed fosters a culture of transparency.
Automation and AI are not meant to replace your IT staff, but to augment and empower them. However, your IT staff may need to acquire new skills and competencies to work effectively with automation and AI tools and solutions. You need to train and upskill your IT staff on the basics of automation and AI, such as concepts, terminology, methods, and applications. You also need to provide them with opportunities to learn and practice the specific automation and AI tools and solutions that you use in your IT operations. You should also foster a culture of learning, collaboration, and innovation among your IT staff.
Automation and AI can have significant ethical and social implications for your IT operations, such as privacy, security, accountability, transparency, fairness, and trust. You need to manage these implications proactively and responsibly, by following the ethical principles and guidelines of your organization, industry, and society. You also need to communicate and engage with your stakeholders, such as customers, employees, partners, and regulators, about the benefits, risks, and expectations of automation and AI in your IT operations. You should also seek feedback and input from them to improve your automation and AI solutions and practices.
Define metrics right from the start. Track automation and AI progress effectively. Monitor your journey using a combination of external benchmarks and internal assessments.
Select tools that facilitate process tracking. Consider that developers may change within the company, so opt for tools widely known in the market. Ensure smooth onboarding for seamless transitions. This entails maintaining neat and comprehensive documentation. Communicate clearly with upper management and stakeholders regarding change management and the scope of your capabilities.