Jeff Orr's Analyst Perspectives

Conversational automation leverages artificial intelligence (AI)-powered agents, chatbots and virtual assistants to automate both customer interactions and internal processes. These systems understand natural language, sentiment and intent, generating relevant responses and executing actions based on user input. The software provider landscape is analyzed in the ISG Buyers Guide for Conversational Automation. Through 2026, one-half of enterprises will realize that digital experiences are neither intelligent nor automated and that they fail to meet enterprise readiness requirements. This analyst perspective will delve into the two pivotal use cases driving the revolution: self-service employee tools and customer-facing chatbots. By enhancing operational efficiency and improving customer satisfaction, conversational automation is positioned to generate significant value for medium to large enterprises, thereby reshaping the way organizations engage with both customers and employees. Self-service employee tools powered by conversational automation have emerged as vital assets for enterprises. In the 2024 ISG Market Lens for Generative AI (GenAI) Use Cases, internal employees (34%) were identified as the ultimate end user for GenAI initiatives. These tools streamline internal communication, enabling employees to access information and support autonomously, freeing the workforce for more strategic tasks. By integrating AI-driven chatbots into onboarding and learning and development processes, organizations are witnessing improvements in efficiency. In the 2024 ISG Market Lens for Generative AI Use Cases, 35% of participating enterprises have already invested in GenAI technology for HR support and 24% have invested for personalized learning. For instance, self-service chatbots facilitate onboarding by providing new hires with immediate access to essential resources, answering frequently asked questions about company policies and benefits. This capability not only reduces the time it typically takes to onboard new employees but also enhances the overall experience for newcomers. Organizations that adopt these tools report a reduction in onboarding time, allowing new employees to contribute more quickly to their teams. Moreover, self-service employee tools enhance HR query management. By automating responses to common inquiries, such as leave requests or payroll questions, HR teams can focus on higher-value strategic initiatives instead of being bogged down by repetitive tasks. Enterprises that are able to decrease average response times for HR-related questions are bolstering employee satisfaction and retention rates. However, despite these benefits, businesses may face obstacles when implementing self-service employee tools. Concerns regarding data security and compliance remain paramount, as enterprises must ensure that sensitive employee information is adequately protected. Additionally, some employees may resist adopting new technologies, preferring traditional modes of communication that they are more familiar with. To overcome these challenges, enterprises must engage in change management and provide robust training to staff that embraces innovation. As customer expectations continue to evolve, the role of customer-facing chatbots has become indispensable in enhancing customer experience and driving competitive advantage. In the 2024 ISG Market Lens for Generative AI Use Cases, customer service chatbots were ranked the most beneficial GenAI use case prioritized by enterprise participants. These AI-driven tools provide 24/7 support, addressing customer inquiries in real time. By handling routine requests and frequently asked questions, chatbots not only reduce customer wait times but also enhance overall satisfaction. Generational differences in the use of technology-enabled communications channels suggests that some consumers prefer interacting with chatbots for quick responses, underscoring the importance of integrating these systems. Enterprises leveraging customer-facing chatbots can streamline customer support operations through a reduction in average handling times. This efficiency translates into resource savings and allows human agents to devote their attention to more complex and nuanced customer needs. Additionally, customer-facing chatbots play a crucial role in lead generation and qualification. By engaging with website visitors in real-time, these chatbots can initiate conversations, gather essential information and qualify leads based on user interactions. This capability to increase lead conversion rates makes the technology it a compelling proposition for sales-driven enterprises. Nevertheless, the journey toward implementing customer-facing chatbots is not without challenges. Enterprises often grapple with the limitations of chatbots when it comes to handling complex customer queries or providing empathetic responses. This limitation can lead to frustration among customers, resulting in potential damage to brand reputation. Furthermore, employees may harbor concerns about the potential job displacement that comes with automation. Addressing these objections involves promoting a hybrid approach, where chatbots complement rather than replace human agents, ensuring that customers receive the best of both worlds. A third use case for conversational automation technologies is customer experience management (CXM), the focus of the ISG Buyers Guide for CXM, which encompasses enhanced customer engagement, streamlined issue resolution and comprehensive analytics and insights. For a deeper exploration of this topic, please see our separate analyst perspective on conversational automation for CXM in contact centers. Across both external and internal use cases, ISG Research envisions that conversational automation will progressively integrate with process orchestration and management platforms in the coming years. By connecting with existing systems and leveraging repositories of structured, semi-structured and unstructured data, intelligent automation will not only provide actionable business process insights but also underpin innovation and agility. This evolution positions enterprises to respond more quickly to market demands and customer needs, ensuring sustained competitive advantage. AI using GenAI and large language model (LLM) technologies offer valuable capabilities in natural language understanding and processing, content generation and task automation, potentially streamlining operations and enhancing decision-making processes. It is crucial to understand the potential and challenges of these technologies. GenAI and LLMs are elevating conversational automation through: More natural and context-aware interactions. LLMs enable chatbots and virtual assistants to understand and respond to queries, maintaining context over longer, multi-turn conversations. Dynamic response generation. Instead of relying on pre-scripted responses, systems can generate unique, contextually appropriate responses in real time, including contact summaries for customer engagement emails and knowledge management. Multilingual support. LLMs provide interactions across multiple languages without the need for separate models for each language. As organizations navigate digital transformation initiatives, embracing conversational automation is an essential component. By implementing self-service employee tools and customer-facing chatbots, enterprises can unlock new levels of efficiency, enhance their customer experience and drive sustained growth. The journey toward automation to create business value is just beginning. Regards, Jeff Orr

The State of Conversational Software Using Automation and AI

Unlocking Success with Enterprise GenAI Tools

ServiceNow Platform Automates Optimal Workforce Experiences

Our Analyst Perspective Policy

Our Analysts

David Menninger

Jeff Orr

Keith Dawson

Mark Smith

Matt Aslett

Matthew Brown

Robert Kugel

Stephen Hurrell

ISG Software Research

Subscribe to Email Updates

Posts by Month

Posts by Topic

Analyst Perspectives Archive