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ISG Research is happy to share insights gleaned from our latest Buyers Guide, an assessment of how well software providers’ offerings meet buyers’ requirements. The Conversational Automation: ISG Research Buyers Guide is the distillation of a year of market and product research by ISG Research.
Enterprises face a perfect storm of challenges and opportunities. The pace of digital transformation, coupled with increasing customer expectations for personalized 
experiences, has applied pressure on enterprises to innovate and optimize. Simultaneously, the rapid expansion of data from diverse sources presents an opportunity for insight-driven decision-making and a challenge in processing and analysis. Enterprises that are grappling with legacy systems struggle to keep up with today’s demands while navigating complex regulatory environments that require detailed compliance and reporting. The global talent shortage, particularly in technology and IT-related fields, makes it difficult for enterprises to scale operations effectively. Moreover, the need for business agility and resilience, along with these converging factors, has created an urgency to automate routine tasks, but also enhance decision-making capabilities, improve customer interactions and accelerate continuous process improvement. In this context, intelligent automation has emerged as a transformative force.
ISG Research defines intelligent automation as an advanced approach to business process optimization that utilizes artificial intelligence (AI), machine learning (ML) and automation technologies. Intelligent automation enhances efficiency, reduces errors and improves decision-making across the enterprise. It shifts human resources from simple, repetitive tasks to more complex problem-solving activities while augmenting their capabilities through human-AI collaboration that embraces continuous learning systems and improves over time. ISG Research segments intelligent automation into four areas: Process Automation Platforms, Conversational Automation, Intelligent Document Processing and Process Discovery and Mining.
Conversational automation uses AI-powered agents, chatbots and virtual assistants to automate customer interactions and internal processes. These systems can understand natural language, sentiment and intent,
producing relevant responses and execute actions based on user input. Regardless of external or internal use cases, ISG Research believes that in the coming years, conversation automation will have greater integration with process orchestration and management platforms. By integrating with existing systems and software tools and accessing large repositories of structured, semi-structured and unstructured data, intelligent automation can lead to business process insights that contribute to innovation and competitive advantage. Through 2027, enterprises that have not embraced voice and chat conversational computing to simplify business application interactions will be at a competitive disadvantage.
For chief information officers and IT leaders, intelligent automation represents a strategic investment in digital transformation, offering the potential to enhance customer engagement, reduce the workload on human agents and gather insights from customer interactions to drive efficiency, agility and innovation.
Conversational automation has become a focal point in enterprise technology discussions, driven by the convergence of several critical factors. The acceleration of digital transformation, catalyzed by the COVID-19 pandemic, has increased the need for operational agility and modernization of legacy systems. This urgency, combined with advancements in AI and ML, has expanded conversational automation capabilities to handle complex cognitive tasks that benefit both the workforce and customer engagement.
The explosion of data across enterprises has further amplified the importance of this technology, as it offers powerful tools for processing and deriving insights from vast amounts of information, enabling data-driven decision-making at scale. Additionally, conversational automation addresses the evolving workforce landscape by automating routine tasks and augmenting human capabilities, allowing workers to focus on higher-value, strategic activities.
When an enterprise CIO or IT leader considers conversational automation software, the choice should correlate to the organization’s specific objectives, goals and desired outcomes. Conversational automation supports enhanced customer and worker experiences, provides 24/7 support and reduces the workload on customer service teams. This technology is particularly useful for enterprises with high customer interaction volumes, those looking to scale customer service operations without proportionally increasing costs or organizations aiming to provide personalized interactions at scale. It is also valuable for enterprises seeking to improve internal support functions such as IT helpdesks or HR services.
The choice of intelligent automation software should align with the enterprise’s strategic objectives and operational needs. It is also important to consider factors such as the current process landscape, compatibility and 
integration with the technology infrastructure, data availability and quality, ROI and financial impact and organizational readiness. A well-chosen automation strategy can drive operational excellence, improved customer experiences and enhanced decision-making.
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. We assert that through 2026, only 1 in 5 enterprises will analyze patterns and generate insights from GenAI software that empower data-driven decision-making and lead to improved business outcomes.
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.
CIOs and IT leaders should approach intelligent automation software incorporating GenAI and LLMs with enthusiasm and caution. While these technologies offer significant benefits, they also come with unique challenges and prerequisites. A holistic evaluation must include technical aspects and also business, ethical and strategic considerations. Other areas of focus include risk awareness, critical infrastructure, organizational readiness, governance and compliance and a long-term perspective on sustainability and scalability of AI approaches.
Our Conversational Automation Buyers Guide is designed to provide a 360-degree view of a software provider’s ability to use enterprise data to standardize and optimize a variety of customer and workforce interactions. ISG believes a methodical approach is essential to maximize competitiveness. It is critical to select the right software provider and product to improve the performance of your enterprise’s people, process, information and technology components.
This Conversational Automation Buyers Guide evaluates products based on capabilities including natural language processing, natural language understanding, artificial intelligence and machine learning, dialogue management, channel integration, back-end system integration, access controls for platform users, life cycle management, implementation of no-code/low-code/code-first principles for citizen developers and traditional coders, analytics tools, intent and entity tuning, A/B flow testing tools, flexibility of intent models across industries and use cases, multilingual support, business customization options, voice enablement, omnichannel abilities beyond websites and mobile applications, and demonstrated investment in functionality. To be included in this Buyers Guide, software providers must meet or exceed the inclusion criteria and have commercially available products in conversational automation.
This Buyers Guide report evaluates the following software providers that offer products addressing key elements of conversational automation: [24]7.ai, Amelia, AWS, Engageware, Google Cloud, HCLSoftware, IBM, Kore.ai, LivePerson, Microsoft, Pegasystems, ServiceNow, Sinch, Sprinklr, Uniphore, Verint and Yellow.ai. Software providers that provide process automation platforms, intelligent document processing or process discovery capabilities are represented in separate Buyers Guide research reports.
This research-based index evaluates the full business and information technology value of conversational automation software offerings. We encourage you to learn more about our Buyers Guide and its effectiveness as a provider selection and RFI/RFP tool.
We urge organizations to do a thorough job of evaluating conversational automation offerings in this Buyers Guide as both the results of our in-depth analysis of these software providers and as an evaluation methodology. The Buyers Guide can be used to evaluate existing suppliers, plus provides evaluation criteria for new projects. Using it can shorten the cycle time for an RFP and the definition of an RFI.
The Buyers Guide for Conversational Automation in 2024 finds ServiceNow first on the list, followed by Verint and IBM.
Software providers that rated in the top three of any category ﹘ including the product and customer experience dimensions ﹘ earn the designation of Leader.
The Leaders in Product Experience are:
- ServiceNow
- Verint
- Sinch
The Leaders in Customer Experience are:
- ServiceNow
- Verint
- IBM
The Leaders across any of the seven categories are:
- ServiceNow, which has achieved this rating in six of the seven categories.
- Pegasystems in three categories.
- Amelia, Google Cloud, Sinch and Verint in two categories.
- MuleSoft and IBM in one category.
The overall performance chart provides a visual representation of how providers rate across product and customer experience. Software providers with products scoring higher in a weighted rating of the five product experience categories place farther to the right. The combination of ratings for the two customer experience categories determines their placement on the vertical axis. As a result, providers that place closer to the upper-right are “exemplary” and rated higher than those closer to the lower-left and identified as providers of “merit.” Software providers that excelled at customer experience over product experience have an “assurance” rating, and those excelling instead in product experience have an “innovative” rating.
Note that close provider scores should not be taken to imply that the packages evaluated are functionally identical or equally well-suited for use by every enterprise or process. Although there is a high degree of commonality in how organizations handle conversational automation, there are many idiosyncrasies and differences that can make one provider’s offering a better fit than another.
ISG Research has made every effort to encompass in this Buyers Guide the overall product and customer experience from our conversational automation blueprint, which we believe reflects what a well-crafted RFP should contain. Even so, there may be additional areas that affect which software provider and products best fit an enterprise’s particular requirements. Therefore, while this research is complete as it stands, utilizing it in your own organizational context is critical to ensure that products deliver the highest level of support for your projects.
You can find more details on our community as well as on our expertise in the research for this Buyers Guide.
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