ISG Buyers Guide for Intelligent Automation Classifies and Rates Software Providers

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 Intelligent 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.

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. We assert that by 2026, one-half of enterprises will use intelligent automation technologies to interconnect disparate applications and systems across public and private cloud computing environments to optimize digital efficiencies.

For chief information officers and IT leaders, intelligent automation represents a strategic investment in digital transformation, offering the potential to advance business processes, improve customer experiences and create new opportunities for technology-business alignment.

Intelligent automation encompasses four primary enterprise software categories, each addressing specific aspects of operations, such as:

• Process automation platforms, which form the foundation of intelligent automation, automating repetitive, rule-based tasks across various applications and systems. Originally designed using robotic process automation, they emulate human actions to perform high-volume, transactional activities efficiently and without error. ISG Research anticipates that RPA and Generative AI (GenAI) will remain integral to process automation and that the software segment will soon focus on process orchestration and management.
• Conversational automation, which uses AI-powered chatbots and virtual assistants to automate customer interactions and internal processes. These systems can understand natural language, sentiment and intent, producing relevant responses and executing 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.
• Intelligent document processing, which focuses on the automated extraction, classification, analysis and processing of information from various document types, including structured, semi-structured and unstructured formats. It combines optical character recognition, natural language processing (NLP) and ML to understand and act upon document content. ISG Research predicts the core functions of IDP will assist process orchestration and management systems in refining automation workflow that adapts to increasingly unstructured document sources.
• Process discovery and mining, which analyze event logs and system data to provide insights into business processes, identify inefficiencies and recommend change. They offer a data-driven approach to process optimization and continuous improvement. ISG Research predicts that this software segment will evolve into enterprise-wide process intelligence. Once enterprise process improvements are identified, process intelligence will coordinate with process orchestration and management to develop the most effective automation workflow.

The intelligent automation software category integrates these four product types to create an ecosystem that can:

• Automate simple and complex tasks across departments and the entire enterprise.
• Continuously learn and adapt to changing business conditions.
• Augment human capabilities and shift focus to higher-value activities.
• Improve decision-making through data-driven insights.
• Enhance operational efficiency, reduce errors and drive enterprise change.

Intelligent 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 intelligent automation capabilities to handle complex cognitive tasks.

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, intelligent 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 intelligent automation software, the choice between process automation platforms, intelligent document processing, conversational automation and process discovery should correlate to the organization’s specific objectives, goals and desired outcomes. These options support varying needs, such as:

• Process automation platforms, which support an enterprise’s goal to increase operational efficiency, reduce errors in repetitive tasks and free up human resources for more strategic work. These platforms are particularly beneficial for organizations looking to streamline high-volume, rule-based processes across multiple departments or legacy systems. They offer quick wins in cost reduction and productivity gains, making them suitable for businesses seeking rapid return on investment from automation initiatives.
• Intelligent document processing, which benefits enterprises dealing with a large volume of documents. It accelerates document-centric processes, improves data accuracy and enhances compliance. This technology is especially valuable for enterprises in document-intensive industries like finance, healthcare or legal services. It also benefits companies looking to digitize operations, reduce manual data entry and gain faster insights from document-based information.
• Conversational automation, which 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.
• Process discovery and mining, which helps organizations identify deep insights into existing processes, pinpoint inefficiencies and drive continuous improvement. This technology is crucial for enterprises undergoing digital transformation, those looking to optimize complex business processes or organizations aiming to ensure compliance with industry regulations. It is particularly beneficial for businesses with intricate, multi-step processes that span various systems and departments.

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 enhancing process automation platform software in several ways, including:

• Automated code generation, with LLMs generating code snippets or entire scripts based on natural language descriptions of desired automation tasks. This speeds the development of automation workflows and reduces the technical expertise required to create automations.
• Natural language process design, which allows users to describe complex processes in plain language and generates a visual flowchart or process map, making it easier for non-technical staff to contribute to automation projects.
• Intelligent decision-making, using LLMs to analyze vast amounts of historical data and current content to make more granular decisions within automation workflows, handling exceptions and edge cases more effectively.
• Dynamic process optimization, using GenAI to suggest process improvements by analyzing execution data and identifying inefficiencies or bottlenecks on a continuous basis.

GenAI and LLMs are revolutionizing IDP software by:

• Enhancing the understanding of unstructured data. LLMs can better interpret context and intent in unstructured documents, improving extraction accuracy for complex or ambiguous information.
• Adaptive template generation. Instead of relying on pre-defined document structure templates, GenAI creates and refines document templates on the fly, allowing for processing of unfamiliar document formats.
• Content summarization and analysis. LLMs can generate concise summaries of lengthy documents, extract key insights and even provide a side-by-side comparison of information across documents.
• Automating document generation. Based on extracted data and predefined rules, GenAI can create new documents, reports or responses.

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.

GenAI and LLMs are enhancing process discovery and mining capabilities through:

• Automated process narrative generation. LLMs can generate detailed, narrative descriptions of discovered processes, making it easier for stakeholders to understand complex process flows.
• Intelligent anomaly detection. By understanding the context and purpose of process steps, LLMs can identify anomalies that go beyond simple statistical deviations.
• Predictive process modeling. GenAI can create predictive models of how processes might evolve under different scenarios, aiding in strategic planning. Digital “process twins” are applied in simulations without impacting operational conditions.
• Automated improvement suggestions. Based on discovered processes and best practices, GenAI can propose specific process improvements or redesigns that affect a department or the entire enterprise organization.

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 Intelligent 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 business processes and tasks. As such, the Intelligent Automation Buyers Guide includes the full breadth of services and functionality. Software providers that provide process automation platforms, intelligent document processing, conversational automation or process discovery capabilities are represented in separate Buyers Guide research reports.

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 Intelligent Automation Buyers Guide evaluates products based on three software segments, including process automation platforms, intelligent document processing and process discovery and mining. Conversational automation is evaluated in a separate Buyers Guide. Capabilities evaluated for intelligent automation include enterprise system integration, natural language, workflows, AI and cognitive technologies, balancing workloads, performance monitoring and analysis, citizen developer support, error handling, data extraction, document classification, human-in-the-loop validation, use of low-code/no-code/code-first tools, user access controls, flow testing, simulations and scenario planning, multilingual support, voice enablement, omnichannel support, business rules and compliance, risk mitigation and collaborative features. To be included in this Buyers Guide, software providers must meet or exceed the inclusion criteria and have commercially available products in these three intelligent automation segments.

This Buyers Guide report evaluates the following software providers that offer products addressing key elements of process automation, intelligent document processing and process discovery and mining for inclusion in intelligent automation: Appian, Automation Anywhere, IBM, Microsoft, ProcessMaker, ServiceNow, Tungsten Automation and UiPath.

This research-based index evaluates the full business and information technology value of intelligent 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 intelligent 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 Intelligent Automation in 2024 finds ServiceNow first on the list, followed by UiPath and Microsoft.

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
• UiPath
• Microsoft

The Leaders in Customer Experience are:

• ServiceNow
• UiPath
• IBM

The Leaders across any of the seven categories are:

• ServiceNow and UiPath, which has achieved this rating in seven of the seven categories.
• Appian in three categories.
• Automation Anywhere in two categories.
• IBM and ProcessMaker 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 intelligent 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 intelligent 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.