April 22nd is Earth Day, a day dedicated to raising awareness and inspiring action to protect our world. The very first Earth Day was in 1970. Since then, it has mobilised over 1 billion individuals to work towards the future of our planet and has over 75,000 partners working to drive positive action.
This year’s theme is ‘Invest in Our Planet’. There are many ways in which individuals, businesses and organisations can contribute to this movement. For example, you can support a drive for climate education, help reduce plastic pollution, attend a clean-up or support sustainable fashion.
Advances in technology can also be used to drive more sustainable, environmentally positive processes and Invest in Our Planet. Digital applications can be used to optimise the use of resources, track sustainability and reduce businesses’ carbon footprints.
More recently, innovations in artificial intelligence (AI) and machine learning (ML) are opening up even more potential for driving business-wide sustainability. Our blog takes a closer look at how.
What are the differences between (AI) and machine learning (ML)?
AI and ML are often used interchangeably. However, there is a subtle difference.
The name Machine Learning (ML) quite accurately describes what this technology does. ML can be thought of as a sophisticated and more independent form of statistical analysis. It gathers and reviews data to make decisions, solve problems and complete tasks.
By employing algorithms, ML can ‘learn’ directly from the data it is fed, with minimal human input. The more data ML receives, the more the learning increases, and performance improves.
The goal of Artificial Intelligence is to match or even exceed the abilities of humans. AI is an umbrella term encompassing ML, and also Deep Learning or DL (a more complex form of ML). However, it includes other machine capabilities. For example, Natural Language Processing (NLP) can process human language. AI models can also replicate our speech, vision, hearing and movement (in the case of robotics).
So how are AI and ML supporting businesses with their sustainability goals?
The current challenges of IT Operations
From changing consumer behaviour to technological advances or challenges in our wider environment, IT operations are tasked with implementing new strategies to support businesses in keeping up with demand and facilitating growth.
Yet, implementing change fast can be challenging due to system complexity. IT Operations are adopting many new applications and tools to plug the gap. But in the long run, these siloed systems are hindering business performance.
Filtering through vast volumes of data to solve problems is also slowing operations. These delays can cause problems to escalate, creating more damage to the business and the environment. At the same time, IT Operations are under pressure to keep costs down, all while maintaining a high level of service.
Leave these issues unaddressed, and they will spiral. Volumes of data will increase, and the increasingly siloed infrastructure will be unable to cope. Operational workflows urgently need streamlining to cut out the 'noise', and more processes must be automated to enable businesses to perform with more efficiency and less waste.
How AIOps can help
AI offers a solution when humans are unable to scale in real-time. It also provides support where institutional expertise needs to be replicated. AI can spot things we miss, such as operational activity errors or issues requiring troubleshooting. Furthermore, its analysis skills mean it can also predict pending problems.
AIOps harnesses the capabilities of AI to drive improvements in IT operations.
AIOps, or Artificial Intelligence for IT Operations, was initially conceived by Gartner, who describes it as combining “big data and machine learning to automate IT operations processes, including event correlation, anomaly detection and causality determination.”
The main goal of AIOps is to use AI to automate and streamline IT operations. Bringing together manual IT operation tools into an automated IT operations platform that leverages AI, it aims to solve many challenges in today's IT landscape.
AIOps provides 24/7 availability, automatic triage and insights. Offering predictive analytics, proactive response and self-healing capabilities, AIOps delivers immense benefits to the challenges faced by IT Operations.
Identifying issues and self-healing
AIOps supports more informed decisions to address various site, network or ISP issues. It offers predictive recommendations for next steps and remediation, supporting faster issue resolution or prevention. Using self-healing with a 97.7% success rate, AIOps ensures the potential impact of any issues is significantly reduced or avoided entirely.
Improving efficiency and agility to scale
AIOps can complete tasks much more quickly and scale with ease where required. This capability frees up employees to focus on other, more complex areas.
Providing better visibility across different departments, AIOps enables better collaboration and performance and more optimal use of resources.
Improving service quality and customer experience
With issues resolved proactively, there is a reduction in customer escalation. Furthermore, as customer interactions decrease, help desks have increased time and resources to deal with other non-network issues that support a better customer experience.
Wide-ranging environmental benefits
From an eco-friendly perspective, this boost in efficiency and proactive issue resolution leads to a more optimal use of resources that supports better sustainability. For example, AIOps health scoring and prescriptive self-healing elements reduce the need for callouts and onsite visits, minimising carbon footprints.
Meanwhile, its predictive analytics and proactive response supports a reduction in errors that decreases waste.
AIOps has an important role to play in sustainability, contributing to this year’s Earth Day theme of Invest in Our Planet. This role is only likely to grow as the technology behind AIOps becomes more sophisticated.
As a managed network services provider, we are leveraging AIOps across an increasing number of our services to improve customer experience, efficiencies and sustainability. To find out more about our AIOps capabilities, please get in touch with our team.