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CSPs must keep Human Intelligence at the Centres of Service Assurance AI Strategies

  • 8 minute read
  • Published by Charisma Quebral on 22 Feb 2021
  • Last modified 23 Feb 2021
Communication Service Providers (CSP) are establishing and implementing automated systems and artificial intelligence applications. They are accelerating automated solutions rollout to resolve CAPEX/OPEX challenges and workload challenges associated with 5G and Next Generation Network upgrades.

CSPs have always placed their people at the heart of their operations and business. In this brave new world of automation and messianic Artificial Intelligence (AI) autonomous machines, CSPs must keep their people at the centre of their artificial intelligence strategy. The value-add and the creativity required to drive growth and increase revenue in a CSP’s business resides in the hearts and minds of their people rather than an AI solution.

A CSP’s talented people know and understand the CSP’s business on both a logical and emotional level. A company’s AI strategy must acknowledge the importance of human emotion as a driving force to create and form ingenious ideas to grow a business. AIs lack emotion. The love that human intelligence uses to generate ideas and add value is not available to AIs. Love-works and human intelligence motivated by love must be empowered to shape the nature of artificial intelligence and its role in their environment. The value-add that a workforce possesses is often subdued by the overwhelming workload that they manage. AIs are required to take on some of the burdens of that workload. AIs will free-up time for the workforce to establish and execute initiatives that realise the value-add to drive growth and success.

From a service assurance perspective, the relevant subject matter experts and their intellectual property are paramount to the successful establishment of automation and AI solutions. The engagement of subject matter experts in establishing AI strategy guarantees relevant and correct task assignment to AI processes. Subject matter experts are most qualified to highlight areas where AI solutions will augment and support them to execute their jobs efficiently with the highest quality. They know how AI can help them to produce immense value with every action they perform. Service assurance processes facilitate the detection of defects and malfunctions. The ultimate goal is to resolve service degradations before it impacts the experience of users and subscribers. AWTG believes that the success of a company’s AI strategy is dependent on the efficiencies it offers the company’s people and the value it facilitates them to produce. AI should augment and help people to improve performance, skills and also help identify strengths and weaknesses. Human Intelligence challenges must be used to determine the ambition of Artificial Intelligence.

Artificial Intelligence (AI) affords a CSP ability to produce a successful service delivery strategy and to maintain service quality above exceptional levels in real-time. It also allows real-time management of customer satisfaction magnifying the probability of customer retention. AI provides up-to-the-minute information about expenditures enabling the optimisation of capital and operating costs in real-time. The advantages of AI are apparent because of the benefits we see from automation processes currently implemented.

Automation and AI applications significantly reduce the response time for identifying service affecting issues and implementing solutions. Automation and AI applications support continual service improvement processes ensuring solutions are permanent. Residual errors are detected and addressed without delay or impact on the experience of subscribers and users.

Artificial intelligent applications and automated systems are increasingly being used to monitor service usage performance whilst continually evaluating the impact of service degradations and sub-optimum service design on customer experience indices. Resource utilisation and capacity management are also enhanced with AI algorithms to optimise whilst maintaining service quality levels and customer satisfaction. Communication service providers (CSPs) are also adapting their telecoms operations management processes to include automation of asset tracking, automatic rollout management, and automated post-implementation performance acceptance.

Fully autonomous AIs do not yet exist in the field of service assurance management. Several plans are in full flow to establish such solutions. Amongst “Dark Arts” experts (Radio/ RF Engineers), there are murmurs around a belief that a full end2end AI solution (Autonomous Interaction and management of the Air Interface, Customer, Service, Infrastructure, Product, Resources, Market) to manage service assurance may never materialise. They believe that human and artificial intelligence partnership may always be necessary for service assurance excellence. A fully autonomous artificial intelligent entity has much to learn about illogical truths that human intelligence leverages when the facts do not make sense.

AWTG has observed a higher probability of positive results for service assurance automation/AI when the CSP organisation’s subject matter experts (SME) are involved in its strategy, creation, and formation. It reduces the complexity of identifying solutions that are unique to the CSPs network and business. It simplifies the establishment of the solutions for various use cases, services, clutter types, mass events, customer profiles, user devices, etc. Employing the ingenuity of subject matter experts reduces the cognitive complexity of the AI’s machine learning adventure. Subject matter experts ensure best practices and lessons learned are industrialised and used to evolve the network. Lessons learnt are human intelligence assets that must be taught to an AI by a company’s people. Not all lessons learnt are documented. Most of them are locked away in the minds of the workforce.

AWTG has understood that the successful implementation of automation and AI solutions for service assurance requires a service correlation and assurance platform that serves as the Earth for the AI entity. Alva Noe stated that “Action is perception”, which is so true. An autonomous AI may only be trusted when it can perceive & understand information from all relevant external sources.  The AI must perceive all the forces and forms that impact the service assurance use case it manages. A service correlation and assurance platform that captures all relevant data is the foundation that validates the AIs ability to perceive. It is equivalent to Human intelligence relying on the visual (seeing), auditory (hearing), tactile (touch), gustatory (taste), and olfactory (smell) senses.

AWTG also understands the importance of assigning Telecom solution architects and data scientists to work with and translate the CSP’s subject matter experts’ ideas, technical information, processes, procedures, and working-level instructions into algorithms. That then enables software and application development experts to code the algorithms to transition service assurance use cases from automation towards AI processes/solutions. By allowing a company’s workforce to fully participate in the formation and realisation of a company’s AI strategy, the challenge to identify and develop new revenue-generating ideas and business models will be easier to navigate. Subject-matter experts collaborating and sharing ideas about different functionality for a company’s AI community strengthens the AI’s architecture.

High-level service assurance processes adhere to a standard framework. There are procedures and working-level instructions continually improved by expert engineers and service assurance managers using their creative instincts and expertise. A one size fits all AI solution will restrict the capabilities to deliver significant benefits expected for revenue, profit, quality, time, etc. Each member of a CSPs service assurance organisation must contribute their ideas to the AI solutions universe.  It will enable them to maximise the value they add to the service assurance goals and overall business objectives. As an expert for their role, they are best placed to decide how an AI may add unique value.

Artificial intelligence is most valuable when it enhances human intelligence or provides convenience for human beings. The establishment of an autonomous Service Assurance AI must follow a graduate scheme, new starters or new joiners’ process. The AI must be assigned a probation period and a mentor. The AI (under supervision) must be allowed time to learn its role and accumulate skills from the existing workforce. Human ingenuity and intelligence are keys to unlocking the hidden value in a business.

For CSPs seeking hidden value in their service assurance processes and functions, the AI must be an enabler of human intelligence rather than an alternative or rival to people.

AWTG’s Service Correlation and Assurance Platform

The Service Correlation and Assurance Platform is a centralised network management platform with an AI-assisted network operations engine at its heart. The platform uses advanced analytics and automated performance management to consolidate and correlate information from all sources of network operations-related data. Applications are created to help users establish their unique version of an AI/automation entity that may execute actions in line with their job/task objectives. It is a hybrid solution that builds on the interaction between human intelligence and artificial intelligence.

The hybrid AI solution offered via AWTG’s Service Correlation and Assurance Platform helps a CSP establish a semi-supervised AI. It supports human intelligence by orchestrating several automated entities in charge of sub-processes to address a particular business objective (e.g., Customer experience improvement initiative, Benchmark position improvement). The platform allows supervision and in-house development of automation and solutions for service assurance.

The Service Correlation and Assurance platform is vendor agnostic, information type neutral, and affords an organisation service assurance insight that facilitates a higher layer overview of service assurance management information. The platform provides a central node correlating and analysing data from all network management information sources to manage service assurance.

The platform establishes real-time service insight by enabling collation and correlation of all network operation functions, systems, customer data and market data. The correlation of configuration management, performance management, and fault management data using advanced analytics is automated. Automated service quality level KPI management has also been implemented.

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