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AX Consulting
AI Transformation Consulting (AX Consulting)

​​Across industries, companies are evolving from the stage of Digital Transformation (DX), which transformed enterprise-wide digital environments with AI, cloud, and big data, toward AI Transformation (AX). This shift prioritizes intelligent automation of business processes, data-driven decision-making, and enhanced customer experiences. By leveraging AI, big data, and cloud, businesses strive to strengthen their digital capabilities, applying advanced AI technologies across operations to drive automation and optimization. These efforts are intended to maximize the potential of Agentic AI, enabling intelligent, autonomous decision-making​.
AX Consulting provides the foundation for full automation of key business tasks through Agentic AI, reshaping how work is performed. By automating AI-driven data analytics, it supports more accurate and efficient decision-making. While early AI adoption was focused on isolated tasks, businesses are now transitioning toward process-wide AI integration. To facilitate this shift, LG CNS offers end-to-end AX support, spanning the development of AX Master Plan, AI Process Innovation (PI), Service Design, and AI Engineering Consulting, ensuring organizations adopt AI effectively at every stage.

* Agentic AI: An autonomous AI system that sets its own goals, perceives its environment, plans actions, and executes decisions without human intervention.

Strategic Navigation for AX Acceleration
How should companies prepare for AI adoption?

In the present era, companies are required to advance AI- and data-driven innovation continuously. The emergence and rapid evolution of Generative AI are transforming how businesses utilize AI, and the market is already anticipating Agentic AI taking over human tasks sooner than expected.

However, many businesses struggle to keep pace with these changes, finding it difficult to determine which AI solutions best fit their operations, how to ensure cost efficiency, and how to mitigate risks. Establishing a clear adoption strategy has become increasingly complex, making guidance from AI experts and strategic collaboration essential.

To unlock AI’s potential to the full extent, companies need a structured approach—identifying AI-driven opportunities, defining optimal implementation strategies, and developing an enterprise-wide adoption roadmap. AI readiness assessments, covering data, infrastructure, workforce capabilities, and corporate culture, are essential, as costs of AI adoption and business outcomes vary significantly based on an organization’s AX preparedness (maturity).

A precise AI readiness assessment enables companies to develop a results-driven AX strategy optimized for both internal and external AI environments. A comprehensive strategy is required to ensure clear prioritization, optimized allocation of resources, and effective risk management, supporting seamless AI transformation.

LG CNS AX Master Plan

AX Strategy Consulting

​LG CNS provides AX Strategy Consulting to help enterprises assess their AI adoption status and define a strategic direction, supporting C-level decision-making. By aligning AI strategies with the latest industry trends, businesses can establish a competitive, AI-driven business model and identify opportunities to enhance operational efficiency. Through AI-driven optimization, companies can reduce costs, enable data-driven decision-making, and enhance customer value to strengthen their market position.
​The AI transformation roadmap and long-term strategy developed through AX Strategy Consulting empower enterprises to gain a competitive edge, adapt to rapid market changes, and drive sustainable growth. LG CNS provides end-to-end support that integrates AI Governance, platform construction, AI ISP (Information Strategy Planning) Consulting, and AI Engineering Consulting, ensuring structured implementation of the AI roadmap.

AX Discovery: Discovering Use Cases, Customized AI Solutions, and Scope of AI Adoption

LG CNS AX Discovery helps businesses discover AI tasks that address their specific needs and pain points to create real business value. It provides strategic direction for companies considering AI adoption and offers tailored recommendations based on their current stage of AI maturity and readiness. For enterprises with clearly defined tasks, AX Discovery accelerates the validation of AI use cases, ensuring efficient deployment aligned with business goals. Additionally, for those looking to adopt AI at scale, it provides a structured adoption roadmap, from identifying tasks to expanding across the entire enterprise and value chain.

AX Master Plan Execution Strategy

AX Strategy and Master Plan (AI Transformation Strategy)

The AX Strategy presents AI-driven business models, process innovations, and workforce transformation strategies tailored to each company’s AI vision. It identifies key opportunities for AI adoption and establishes a short- and long-term roadmap. By advancing into the Master Plan phase, enterprises can outline the required AI capabilities, investments, and expected business outcomes in greater detail, ensuring a well-prepared and executable strategy.

 

Development of AI Vision and Transformation Strategy

  • AI Maturity Assessment*
  • Analysis and Benchimarking of Leading AX Trends**
  • Indentifying and Defining Opportunities for AI Adoption
  • Development of AI Strategy Tasks and Roadmap

    *, ** Available as seperate offerings

AX Discovery: Discovering AI Use Cases, Customized AI Solutions, and Implementation Scope

LG CNS AX Discovery identifies AI use cases best suited to a company’s environment while assessing associated risks and expected business impact comprehensively. By leveraging over 120 validated AI use cases, LG CNS conducts specialized AI workshops that incorporate user insights and ideas to develop Agentic AI scenarios—where AI autonomously perceives its environment and interacts with systems and tools. Additionally, through the rapid development and validation of Minimum Viable Products (MVPs) via prototype projects, LG CNS accelerates AI adoption in the field.


Agentic AI Use Case Discovery and Validation of PoC (Proof of Concept)

  • Identifying Common and Specialized Use Cases
  • Defining (Agentic) AI Use Cases
  • Assessing Expected Business Impact and Risks
  • Evaluating AI Feasibility (PoC, MVP)
FAQ
  • AI Strategy Consulting focuses on establishing an AI roadmap and long-term vision to drive business value through strategies for adoption and expansion of AI. In contrast, AI Discovery helps companies identify AI initiatives tailored to their level of AI understanding and readiness, supporting the validation of clearly defined AI use cases.

  • Once an AI transformation roadmap is developed, companies can proceed with follow-up processes tailored to their specific needs. If process optimization or service planning is required for the adoption of Agentic AI, AI PI or Service Design is implemented for AI adoption. If defining AI adoption areas and technologies is necessary, AI Discovery is conducted. Subsequently, AI Engineering Consulting supports the development, implementation and operation of AI platforms and environments. While a step-by-step approach is recommended for AI transformation consulting, companies can selectively implement services based on their roadmap and business environment.

  • Yes. Even without a clearly defined adoption strategy, AI Discovery provides structured guidance. Through interviews and ideation workshops, LG CNS analyzes internal requirements and business contexts to identify the most suitable AI tasks, and proposes an effective adoption strategy.

The Future of Work and Services Shaped by AI Agents
How will AI change work and services?

To implement and utilize Agentic AI—AI that autonomously sets goals, perceives its environment, plans, and executes actions— successfully, companies must first ensure ① integrated data management, ② the accuracy and relevance of managed data, and ③ enhanced visibility into business processes.
However, in most enterprises, data remains fragmented across legacy systems such as Enterprise Resource Planning (ERP), Manufacturing Execution Systems (MES), and Customer Relationship Management (CRM). This fragmentation prevents organizations from utilizing real-time insights and analytics to the full extent. Additionally, without enhanced visibility into areas where Agentic AI can take over tasks, businesses struggle to maximize the benefits of AI adoption. For process automation, companies must first analyze their current workflows (As-Is process) to identify areas for AI adoption, and then establish a future-state workflow (To-Be process) optimized for automation.

How can AI adoption performance be measured?

​Before adopting AI—which often requires significant upfront investment—companies must conduct a thorough evaluation of Return on Investment (RoI), business impact, and ease of adoption. It can be challenging to measure AI-driven business and process enhancement quantitatively, as initial AI adoption may not yield expected outcomes immediately. To ensure successful AI transformation and performance measurement, businesses should establish clear, data-driven enhancement goals based on Key Performance Indicators (KPI) before adoption. Additionally, they must implement a structured system to validate expected outcomes with data and maintain continuous monitoring post-implementation.​

LG CNS’s AX PI & Service Design

AX PI: AI-Based Process Innovation

​LG CNS’s AI PI enhances and optimizes business processes with the adoption of Agentic AI. Rather than focusing on individual functions, LG CNS identifies and connects AI-driven enhancement opportunities across entire workflows, maximizing tangible business impacts. Through data-based analysis, AX PI establishes quantifiable enhancement goals and enables precise measurement of performance. From the initial engagement, LG CNS works closely with clients to define clear enhancement objectives, analyze entire business workflows, and align AI-driven process innovations with overall business strategies.

AX SAI: AI-Based Service & Application Innovation

LG CNS’s AI-based service innovation applies AI to enhance existing services and introduce new AI-driven solutions based on clients’ needs and pain points. By utilizing both classic AI and Generative AI, LG CNS develops AI functionalities tailored to specific business scenarios and compiles industry-relevant AI use cases as references. It also provides a framework for key AI functionalities, user-system interactions, and service flows, enabling businesses to measure AI service performance and define strategies for AI-driven service innovation.

AI-Driven Process & Service Innovation Framework

AX PI: AI-Powered Process Innovation

AX PI supports AI-driven process innovation from goal setting and analysis of current state to identification of opportunities and execution of enhancements. LG CNS integrates AI and data-based process monitoring to identify areas for optimization and enables E2E process enhancement. To transition to an AI-powered workflow where Agentic AI replaces manual tasks, AX PI follows a structured approach, including Development of PI Strategy, Preliminary PI Concept Design, Detailed PI Design, and Implementation through a Project Management Office (PMO), tailored to ERP, HR, and SCM system characteristics.

 

(Agentic) AI-powered E2E process enhancement

  • AI tool-based process analysis
  • Identification of (Agentic) AI adoption enhancement tasks
  • Design of AI-adopted To-Be processes
  • Establishment of a process KPI and AI-driven monitoring framework (Continuous PI system)

AX SAI: AI-Powered Service & Application Innovation

To accelerate the adoption of new services and enhance existing services, AX SAI develops AI service scenarios that incorporate complex multi-step reasoning and autonomous execution by Agentic AI. LG CNS defines AI technologies suited to specific business needs and maps user-system interactions and UX/UI frameworks. AX SAI has core competencies in identifying individual services as Agents and structuring E2E services through multi-agent collaboration.

 

Planning & Design of AI Service & Application

  • Service & application planning
  • Scenario-based detailed service design
  • Connected data & system definition
FAQ
  • Unlike traditional qualitative PI approaches that rely on employee interviews and workshops, AI-based PI is data-driven, enabling objective analysis and measurable outcomes. It allows businesses to quantify process enhancement and validate business impacts based on real-time data.

  • One effective method for quantifying AI’s business impact is the QCD (Quality: Customer Satisfaction; Cost: Efficiency; Delivery: Speed & Visibility) framework. Feature-driven tasks are categorized based on the QCD framework, and businesses can define KPIs for each enhancement task. AI performance is then measured using formulas.

  • AI is simplifying and optimizing various processes and work, enhancing work efficiency significantly. Agentic AI, in particular, enables Autonomous Workflows—enhancing workflow autonomy and execution capabilities. This transformation introduces a new paradigm for business processes and services.

  • AI service planning is heavily dependent on technological readiness. The scope and structure of AI service planning vary based on the level of AI commercialization. AI service planning often requires more detailed processes than conventional services. Silos may also emerge between developers and designers. If not managed carefully, the balance between planning and technology may become reversed, making it critical to clearly define the concept and business goals from the outset.

Orchestrating the Latest Technologies for the Agentic AI Era
What AI technologies and infrastructure are required?

As companies strive to accelerate AI transformation to enhance business competitiveness, many face challenges in building effective AI platforms. To establish a successful AX platform, businesses need structured Information Strategy Planning (ISP) and a systematic deployment plan tailored to their business goals and current operational environment. By defining an implementation framework, companies can translate their AI strategy into actionable IT elements. This includes creating service planning inputs, defining models and outputs, and selecting channels for service utilization—all of which are incorporated into a Reference Architecture-based platform construction.

How should AI platforms be implemented and managed?

Once an AX platform is constructed, maintaining stable operations and ensuring reliable AI services becomes a key concern. AI governance plays a critical role in addressing these challenges. Organizations are required to implement risk management strategies and ensure continuous security monitoring and system enhancement while upholding principles of ethical AI, transparency, and fairness. A well-defined governance framework enables businesses to maximize the value of AX while executing Agentic AI.

LG CNS’s AI Establishment & Operations Consulting

AX ISP & ITMP (Information Technology Master Plan) Consulting

LG CNS’s AX ISP Consulting develops a master plan for AI adoption based on a company’s existing IT environment and strategic AI roadmap. This includes defining requirements of IT system transformation for the execution of AI services, identifying the necessary data elements and models, and establishing a structured implementation roadmap to ensure scalable and reliable AI adoption.

AI Platform Planning & Architecture

When adopting an AX platform, companies often struggle to identify the right infrastructure and technology stack that best aligns with their AX strategy. LG CNS AI Platform Planning & Architecture Consulting provides businesses with a structured framework to deploy AI services efficiently. This ensures the construction of a stable platform for AI workflows, enabling successful implementation and execution.

AI Governance: Minimizing Risk, Ensuring Explainability, and Continuous Monitoring

​Businesses must comply with AI regulations and ethical standards. LG CNS’s AI Governance Consulting provides expert guidance on global and local requirements regarding AI compliance, security considerations, and best practices for AI adoption. Through stable operation and continuous enhancement, LG CNS ensures businesses can utilize Agentic AI effectively.​

AX Engineering Consulting Framework

AX ISP & ITMP Consulting

It develops a structured roadmap for AI strategy implementation. This includes integrating AI platforms with legacy IT systems, defining the scope of AI adoption within business processes, and structuring data models and engineering requirements. By executing defined implementation tasks, businesses can successfully establish customized AI platforms.

 

Enterprise AI Strategy & Deployment Planning

  • Defining AI adoption technology requirements
  • AI system & infrastructure architecture
  • AI system & infrastructure construction plan
  • Establishing AI governance framework* 
    (Regulations, risk management, performance monitoring)

AI Platform Planning / Design

To build the full AI Engineering Stack required for implementing planned Agentic AI services (applications), LG CNS offers AI Platform Planning/Design Consulting. The range of services includes defining input/output data, AI models (including LLMs), and interfaces with relevant systems and tools. Built on the LG CNS DAP solution’s reference architecture, LG CNS is built on a foundation of extensive experience in providing customized infrastructure, solutions, technologies, and deployment strategies across various industries. The Agentic AI solution 'Quick PoC' supports businesses in making a small but strategic start.

 

AI Platform Architecture & Implementation Framework

  • Benchmarking AI engineering technologies & leading platforms
  • Agentic AI platforms concept architecture
  • Analyzing & designing data pipelines
  • Designing the logic architecture of AI model & platform

AI Governance: Minimizing Risk, Ensuring Explainability, and Continuous Monitoring

Governance is essential for the safe and effective development and operation of AI services and systems under established principles of AI ethics. LG CNS provides comprehensive consulting on AI governance, covering AI strategy, security considerations, and compliance with domestic and international AI regulations. This includes organizational structuring, model management, oversight of the data pipeline, and infrastructure operations and management. Through this approach, businesses can minimize risks associated with AI service regulations while ensuring that their AI initiatives are aligned with societal and business demands, ultimately creating sustainable value.

 

AI Governance Framework

  • AI risk evaluation*
  • Analysis of domestic and international AI Regulations, policies, and corporate guidelines
  • Governance framework (rules, organization, process, IT) & corporate guidelines
  • Selection of AI governance solutions (a detailed construction plan to be executed in platform consulting)

    * Available as a separate offering
FAQ
  • For successful AI adoption, it is essential to establish an environment that enables rapid implementation of AI and adaptability. By leveraging the AX platform, businesses can achieve efficient AI adoption and flexible operations through integrated AI technology and data management. AI ISP Consulting facilitates organizations to develop a structured platform adoption strategy and construct a customized AI platform.

  • Yes. Companies without prior AI adoption experience often struggle with data utilization and adoption challenges. LG CNS’s AI Engineering Consulting helps businesses develop a master plan for AI adoption, transform their infrastructure, and establish AI/ML operational frameworks. This ensures a stable and scalable foundation for the adoption of Agentic AI.

  • Many companies experience service delays and prolonged PoC phases due to a lack of visible project management. LG CNS’s AI Establishment Consulting provides structured project management, clear reference architectures, and enhances AI resource efficiency, risk management, and communication clarity—ensuring successful AI adoption.

  • Ensuring reliability and transparency of the AI model is crucial for building trust in AI services while adhering to ethical standards and regulatory requirements. AI Governance Consulting provides comprehensive services encompassing strategy, security, and policy considerations for AI adoption. This includes model management, data governance, and infrastructure operations, ensuring the sustainable adoption of Agentic AI.

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