PUTTING AI INTO THE ENGINE ROOM

Putting AI Into The Engine Room

Putting AI Into The Engine Room unlocks real and instant value to large organisations with complex IT infrastructure

The real value of Artificial Intelligence (AI) to a business today exists in the engine room of Business Support Systems (BSS) and Operational Support Systems (OSS). As businesses drive their digitalisation strategies, they forget about the complexity that is created for operational management teams who must continue to monitor legacy systems while skilling up and supporting new systems. The operational environments are becoming exponentially more complex and existing staff are expected to support much more than before.

The typical answer to this emerging problem has been the drive towards DevOps structures where new systems are implemented and product subject matter experts provide both development and operational support functions. This allows for quick turnaround of incidents and “roll forward” of operational problems for that system, however, this does not solve the problem of end-to-end operational incident management and root cause analysis.

As a result, during service disruptions, emergency meetings are becoming large and complex as more people from different backgrounds are being pulled in to resolve problems. This process is generally managed by the IT Service Management (ITSM) operations who acts as a co-ordinating end-to-end team to manage the incident. Once the problem has been identified and fixed, a change is made to the system to prevent this situation from reoccurring, however, these fixes tend to be specific to one or two systems and it is post event. It does not prevent another system in the organisation from failing due to the same reason later as there is little to no learning shared across the organisational silos. New systems being rolled out also lack operational support insights and therefore are prone to fail for the same reasons.

At Aizatron, our customers are some of the largest on the African continent. Their ICT systems are becoming increasingly more complex as new technology is required to deliver on the ever-growing business expansion. We leverage AI and Robotic Process Automation (RPA) technologies to automate smart operational bots that act across operational platforms and various company silos.

Our expert service offerings include:

1. Data Automation - Automated extraction of machine data from organisational systems as well as human generated data which is processed by our big data analytics engine.

2. Knowledge Acquisition - We work with existing staff and the ITSM knowledge bases to identify incidents and fixes to those incidents. This is used to provide supervised learning to train operational bots algorithms which use past incidents as training data inputs.

3. Knowledge Transfer - Train existing organisational operations staff to develop their AI models to predict system outages and map out a course of remedial action. In this way, operational support teams become more effective in identifying and preventing outages while creating a self-learning organisation.

4. Automation Operations Manual - We maintain an operation manual (instructions) for the Bots like those that exist for humans, to ensure predictability and consistency in the operational environment. The recommended course of action in the automation manual instructs the operational RPA bots on what actions to take when it is initiated by the AI module.

5. Multi-Bot Execution - The action can be taken by one bot or a set of bots – depending on the security policies of the organisation who has control of the bots. Some organisations create distinct divisions between systems for security reasons as well as to prevent employee fraud. These divisions need to be maintained at an RPA level as well so that organisational security is not compromised. In a multi-bot execution, one bot will complete its tasks and then send a message to the next bot to continue the process in its environment, following the same process humans would if they were executing the fix.

6. Customisation of Automated learning for specific situations - The Bots have the advantage that they learn from the combined knowledge of the entire organisation, for example, lessons learnt from one system can automatically be applied to all systems and therefore, common problems do not repeat themselves. The machine learning identifies the root cause of the problem and based on the problem identification, chooses the appropriate fix to follow in the automation manual. These organisational learnings can be customised for specific scenarios by the system specialists where certain systems do not follow normal organisational best practices.

7. Actionable Operations - Automated actions can be taken by one or more bots depending on organisational security policies. Organisations create distinct divisions between systems and resources enforcing segregation of duties between them for security reasons, to minimise employee fraud. These divisions need to be maintained and reported on to ensure organisational security and integrity.

Our approach to Smart operational management places AI technology inside the engine room of organisations by providing management with the essential dashboards to navigate the business more efficiently to drive bottom line profits.

Aizatron’s operational AI is used to identify the type of problem which it then uses to pick the right procedures to follow from the automation operations manual. Should it fail to resolve the problem, it will then escalate to a human to intervene. The operational AI will then be trained to determine the new scenario based on the data inputs and the human intervention will then be captured into the automation manual for future incidents.

As companies race to rollout their digitalisation strategies, they need to consider AI technology and smart bots to reduce their operational expenses and reduce the dependency on error prone humans. Humans tend to forget things or make mistakes and do not share critical knowledge, resulting in SLA breaches.

Using AI to create smart RPA bots, ensures that learning is built into the organisational systems, thereby improving the business maturity levels by creating a learning organisation. It also frees up employees to focus on more complex, value added and creative tasks within the organisation, making it more agile, flexible, and adaptable to future emerging market and business conditions.