Software Provider and Product Assessment

AI Agents

The shift toward artificial intelligence (AI)-driven software in enterprises and workforce processes has generated a rising demand for more intelligent applications and systems across enterprises. However, integrating and utilizing decades of accumulated knowledge and data presents a significant challenge due to the complexity of legacy systems and existing business practices. Embedding intelligence through AI necessitates software components—known as agents—that can operate autonomously without constant human interaction or oversight. With the emergence of AI platforms that integrate agentic design, generative AI (GenAI) and conversational interfaces for worker engagement, the foundation has been established for the rise and adoption of AI agents.

ISG Research defines AI agents as autonomous software entities that perceive their environment, make context-aware decisions and take actions based on perception and reasoning. While many AI agents rely on simple rule-based logic and are primarily reactive, agentic AI expands on more advanced platforms that enable self-directed behavior. These agents can operate across multiple processes and systems, focusing on specific goals without requiring constant oversight. In many instances, AI agents can run independently or coordinate across different software providers and enterprise environments. Although workers can initiate or interact with these agents, they are designed to function autonomously and engage only as needed to achieve desired outcomes.

AI agents have evolved from simple rule-based programs into intelligent, autonomous components capable of reasoning, decision-making and acting within complex business and digital environments. Initially
characterized by reactive behavior, they progressed to multi-agent systems, leveraging machine learning (ML) to operate more independently and interactively with both workers and machines. Today, with the power of large language models (LLMs) and GenAI, software-based AI agents can perform a wide range of tasks across departments and teams, from retrieving knowledge to orchestrating actions across enterprise systems. Consequently, AI agents are emerging as a foundational layer in modern software architecture, driving new levels of productivity, adaptability and intelligence in enterprise applications. By 2028, software providers will blend agentic AI with collaboration and communications software to provide digital assistants that increase productivity by guiding actions.

Enterprises need AI agents that can reliably support a wide range of activities and tasks, understand context, operate independently and integrate seamlessly with existing systems. These AI agents should function autonomously across workflows, engage with humans as necessary and adapt based on situational context and knowledge so that it can take appropriate actions while efficiently utilizing context and data. Key requirements include operating in a secure and governed manner, with clear limits on their functionality. Most importantly, AI agents must deliver tangible business value by improving efficiency, reducing manual effort and continuously learning in order to enhance performance over time. Ultimately, AI agents save time and resources, reducing costs associated with tasks that would otherwise require manual intervention from workers.

To succeed with AI agents, enterprises must have both the necessary skills and resources to support agentic AI platforms and autonomous capabilities that can be invoked by applications or through conversational AI software. Thorough ingestion and preparation of data from existing applications is critical, as decades of customized systems and "dirty cores" can pose significant challenges in terms of resources and time. The AI agent software must also integrate and interoperate with other applications and systems to achieve intended goals, unless they operate exclusively within the environment and data of the software providers. Additionally, there is a growing need to address privacy and security concerns associated with AI operating autonomously, as well as ensuring compliance with digital sovereignty regulations across different countries and regions.

Effective AI agents need to perceive their environment, reason about goals and determine appropriate actions—operating across both pre-built and custom applications.

The rapidly evolving GenAI market is increasingly focusing on agentic AI as enterprises aim to incorporate generative capabilities into business processes and workflow automation. While LLMs excel at generating content such as text, images and videos, they are not inherently designed to generate actions. To address this limitation, foundation models need to be trained on specific actions and outcomes to foster goal-oriented behavior. This has given rise to large action models (LAMs) in some agentic AI systems, while in others, LLMs are being enhanced with training data that includes actions and results. Consequently, modeling and evaluation tools must evolve to support agents and their associated behaviors. Effective AI agents need to perceive their environment, reason about goals and determine appropriate actions—operating across both pre-built and custom applications. Unlike traditional GenAI, which is prompt-driven, AI agents must also be capable of executing tasks autonomously.

AI agents research is designed to assist enterprises in navigating the new era of agentic and conversational AI, which is driving innovation in intelligent business operations across the workforce and business processes. This comprehensive research evaluates the full spectrum of AI agent offerings and can be used in conjunction with studies on collaborative AI platforms, suites and conversational AI. Unlike separate evaluations that focus on individual categories, this research specifically examines how these technologies integrate to create a unified AI ecosystem—spanning conversations to agents—that enhances productivity and employee engagement. 

To prepare for AI agent software, enterprises should first ensure that their data infrastructure is well-governed, high-quality and seamlessly integrated across systems. This data needs to be accessible to LLMs and capable of supporting large-scale, action-oriented systems, often referred to as foundational models. Organizations should identify a portfolio of high-impact use cases where autonomy and intelligent decision-making can create value, such as in customer service, sales and marketing, finance, supply chain management and IT operations. Establishing strong AI governance frameworks for security, transparency and accountability is essential, as is equipping teams to collaborate effectively with AI agents. Finally, enterprises should adopt flexible platforms and methodologies that support stable operations while allowing for continuous experimentation to evolve AI agent capabilities over time.

The ISG Buyers Guide™ for AI Agents evaluates software providers and products in key areas: platform support, intelligence and workflow, analytic and insights, AI overall, communication administration and specific AI support with agentic AI.

This research evaluates the following software providers that offer products that address key elements of AI Agents: Appian, Automation Anywhere, AWS, C3.ai, Fractal, Google, Gupshup, IBM, Microsoft, Newgen, Oracle, Pega, Salesforce, SAP, ServiceNow, SS&C Blue Prism, UiPath, Verint, Zendesk and Zenvia.

Buyers Guide Overview

For over two decades, ISG Research has conducted market research in a spectrum of areas across business applications, tools and technologies. We have designed the Buyers Guide to provide a balanced perspective of software providers and products that is rooted in an understanding of the business requirements in any enterprise. Utilization of our research methodology and decades of experience enables our Buyers Guide to be an effective method to assess and select software providers and products. The findings of this research undertaking contribute to our comprehensive approach to rating software providers in a manner that is based on the assessments completed by an enterprise.

ISG Research has designed the Buyers Guide to provide a balanced perspective of software providers and products that is rooted in an understanding of business requirements in any enterprise.

The ISG Buyers Guide™ for AI Agents is the distillation of over a year of market and product research efforts. It is an assessment of how well software providers’ offerings address enterprises’ requirements for AI agent software. The index is structured to support a request for information (RFI) that could be used in the request for proposal (RFP) process by incorporating all criteria needed to evaluate, select, utilize and maintain relationships with software providers. An effective product and customer experience with a provider can ensure the best long-term relationship and value achieved from a resource and financial investment.

In this Buyers Guide, ISG Research evaluates the software in seven key categories that are weighted to reflect buyers’ needs based on our expertise and research. Five are product-experience related: Adaptability, Capability, Manageability, Reliability, and Usability. In addition, we consider two customer-experience categories: Validation, and Total Cost of Ownership/Return on Investment (TCO/ROI). To assess functionality, one of the components of Capability, we applied the ISG Research Value Index methodology and blueprint, which links the personas and processes for AI agents to an enterprise’s requirements.

The structure of the research reflects our understanding that the effective evaluation of software providers and products involves far more than just examining product features, potential revenue or customers generated from a provider’s marketing and sales efforts. We believe it is important to take a comprehensive, research-based approach, since making the wrong choice of AI agent technology can raise the total cost of ownership, lower the return on investment and hamper an enterprise’s ability to reach its full performance potential. In addition, this approach can reduce the project’s development and deployment time and eliminate the risk of relying on a short list of software providers that does not represent a best fit for your enterprise.

ISG Research believes that an objective review of software providers and products is a critical business strategy for the adoption and implementation of AI agent software and applications. An enterprise’s review should include a thorough analysis of both what is possible and what is relevant. We urge enterprises to do a thorough job of evaluating AI agent systems and tools and offer this Buyers Guide as both the results of our in-depth analysis of these providers and as an evaluation methodology.

Key Takeaways

AI agents are emerging as a core part of today’s enterprise software, enabling systems to make decisions and take actions independently using technologies such as generative AI and large language models. Unlike traditional, rule-based tools, these agents understand context, reason about goals and operate across workflows with minimal human input. As businesses adopt AI agents, they must overcome challenges like legacy systems, data quality and integration. Success depends on secure, well-governed AI and data platforms with strong agentic and generative AI support, where agents can boost efficiency. With the right strategy, AI agents can drive smarter, faster and more adaptive business operations.

Software Provider Summary

The evaluation finds Oracle, ServiceNow and Salesforce as top-performing software providers, with Oracle leading across seven categories and others showing strength in both Product and Customer Experience. The Value Index categorizes providers into four groups—Exemplary, Innovative, Assurance and Merit—based on weighted scores in Product and Customer Experience. Exemplary providers deliver the most balanced performance. It's important to note that proximity in ranking does not imply identical capabilities.

Product Experience Insights

Product Experience accounts for 80% of the total evaluation and is assessed across Usability, Capability, Reliability, Adaptability and Manageability. Leaders like Oracle, ServiceNow and Salesforce demonstrate strength in core platforms and capabilities. Adaptability reflects how well software integrates and customizes to enterprise needs, while Capability focuses on AI agent depth, workflow, analytics and administration. Providers strong in Manageability and Usability stand out for governance and AI interface support. Together, these metrics identify platforms that perform across the product lifecycle—from onboarding to operations.

Customer Experience Value

Customer Experience comprises 20% of the evaluation, equally weighted between Validation and TCO/ROI. Leaders in this area, such as ServiceNow, Verint and Oracle, demonstrate strong customer commitment, documented case studies and tools to support business case development. Validation assesses a provider’s ability to support the customer journey across sales, onboarding, support and services. Meanwhile, TCO/ROI reflects how well providers help customers understand product value, investment returns and long-term support. Poor performance in this area often reflects a lack of transparency or inadequate information.

Strategic Recommendations

Enterprises evaluating AI agent software should focus not only on feature lists but on how the platform aligns with internal workflows and agentic and generative software. Choose providers with proven support in foundational categories like Adaptability and Reliability. Look for those offering actionable TCO/ROI tools and investing in continuous improvement with transparent customer engagement. Select an application that delivers measurable business value while supporting long-term innovation.  

How To Use This Buyers Guide

Evaluating Software Providers: The Process

We recommend using the Buyers Guide to assess and evaluate new or existing software providers for your enterprise. The market research can be used as an evaluation framework to establish a formal request for information from providers on products and customer experience and will shorten the cycle time when creating an RFI. The steps listed below provide a process that can facilitate best possible outcomes.

1. Define the business case and goals.
   Define the mission and business case for investment and the expected outcomes from your organizational and technology efforts. 
2. Specify the business needs.
   Defining the business requirements helps identify what specific capabilities are required with respect to people, processes, information and technology.
3. Assess the required roles and responsibilities.
Identify the individuals required for success at every level of the organization from executives to front line workers and determine the needs of each. 
4. Outline the project’s critical path.
What needs to be done, in what order and who will do it? This outline should make clear the prior dependencies at each step of the project plan. 
5. Ascertain the technology approach.
Determine the business and technology approach that most closely aligns to your organization’s requirements. 
6. Establish technology vendor evaluation criteria.
Utilize the product experience: Adaptability, Capability, Manageability, Reliability and Usability, and the customer experience in TCO/ROI and Validation. 
7. Evaluate and select the technology properly.
Weight the categories in the technology evaluation criteria to reflect your organization’s priorities to determine the short list of vendors and products.
8. Establish the business initiative team to start the project.
Identify who will lead the project and the members of the team needed to plan and execute it with timelines, priorities and resources. 
   
   

The Findings

All of the products we evaluated are feature-rich, but not all the capabilities offered by a software provider are equally valuable to types of workers or support everything needed to manage products on a continuous basis. Moreover, the existence of too many capabilities may be a negative factor for an enterprise if it introduces unnecessary complexity. Nonetheless, you may decide that a larger number of features in the product is a plus, especially if some of them match your enterprise’s established practices or support an initiative that is driving the purchase of new software.

Factors beyond features and functions or software provider assessments may become a deciding factor. For example, an enterprise may face budget constraints such that the TCO evaluation can tip the balance to one provider or another. This is where the Value Index methodology and the appropriate category weighting can be applied to determine the best fit of software providers and products to your specific needs.

Overall Scoring of Software Providers Across Categories

The research finds Oracle atop the list, followed by ServiceNow and Salesforce. Providers that place in the top three of a category earn the designation of Leader. Oracle has done so in seven categories; ServiceNow in six categories; Salesforce and Verint in two categories; and AWS, IBM, Microsoft and UiPath in one category.

The overall representation of the research below places the rating of the Product Experience and Customer Experience on the x and y axes, respectively, to provide a visual representation and classification of the software providers. Those providers whose Product Experience have a higher weighted performance to the axis in aggregate of the five product categories place farther to the right, while the performance and weighting for the two Customer Experience categories determines placement on the vertical axis. In short, software providers that place closer to the upper-right on this chart performed better than those closer to the lower-left.

The research places software providers into one of four overall categories: Assurance, Exemplary, Merit or Innovative. This representation classifies providers’ overall weighted performance.

Exemplary: The categorization and placement of software providers in Exemplary (upper right) represent those that performed the best in meeting the overall Product and Customer Experience requirements. The providers rated Exemplary are Appian, Automation Anywhere, AWS, Google, IBM, Microsoft, Oracle, Pega, Salesforce, SAP, ServiceNow, UiPath, Verint and Zendesk.

Innovative: The categorization and placement of software providers in Innovative (lower right) represent those that performed the best in meeting the overall Product Experience requirements but did not achieve the highest levels of requirements in Customer Experience. The provider rated Innovative is SS&C Blue Prism.

Assurance: The categorization and placement of software providers in Assurance (upper left) represent those that achieved the highest levels in the overall Customer Experience requirements but did not achieve the highest levels of Product Experience.

Merit: The categorization of software providers in Merit (lower left) represents those that did not surpass the thresholds for the Assurance, Exemplary or Innovative categories in Customer or Product Experience. The providers rated Merit are C3.ai, Fractal, Gupshup, Newgen and Zenvia.

We warn that close provider placement proximity should not be taken to imply that the packages evaluated are functionally identical or equally well suited for use by every enterprise or for a specific process. Although there is a high degree of commonality in how enterprises handle AI agents, there are many idiosyncrasies and differences in how they do these functions that can make one software provider’s offering a better fit than another’s for a particular enterprise’s needs.

We advise enterprises to assess and evaluate software providers based on organizational requirements and use this research as a supplement to internal evaluation of a provider and products.

Product Experience

The process of researching products to address an enterprise’s needs should be comprehensive. Our Value Index methodology examines Product Experience and how it aligns with an enterprise’s life cycle of onboarding, configuration, operations, usage and maintenance. Too often, software providers are not evaluated for the entirety of the product; instead, they are evaluated on market execution and vision of the future, which are flawed since they do not represent an enterprise’s requirements but how the provider operates. As more software providers orient to a complete product experience, evaluations will be more robust.

The research results in Product Experience are ranked at 80%, or four-fifths, of the overall rating using the specific underlying weighted category performance. Importance was placed on the categories as follows: Usability (5%), Capability (40%), Reliability (10%), Adaptability (15%) and Manageability (10%). This weighting impacted the resulting overall ratings in this research. Oracle, ServiceNow and Salesforce were designated Product Experience Leaders.

Adaptability of the Product

This category assesses the degree to which products and technology can be adapted to an enterprise’s specifications via configurability and customization while still maintaining integrity of integration across the worker, device, business, processes, application and data. Adaptability is also related to the ability to readily integrate with other internal and external systems—for example, integrate data and information securely across processes and systems—and support bidirectional data flows to support synchronization and migration. It also examines the investment by the software provider in resources and improvements.

The research weights Adaptability at 15% of the overall rating. Oracle, ServiceNow and Microsoft are the Leaders in this category. While not Leaders, Appian and Salesforce were also found to meet a broad range of enterprise Adaptability requirements.

Adaptability is an essential evaluation metric as it determines the flexibility and interconnectivity of the software provider’s product related to enterprise requirements. It also enables enterprise software to operate across the variety of platforms and cloud computing environments that exist today and in the future.

Software providers that evaluated well in the Adaptability category understand the criticality of preparing and using information to optimize business execution. These providers meet the specific customization and integration support requirements in these areas, enabling enterprises to process data across business processes, workflows and applications as they operate.

Capability of the Product

The Capability criteria are designed to assess the products and features across a broad range of AI agent capabilities that support key areas such as platform support, intelligence and workflow, analytics and insights, AI overall, communication administration and specific AI support for agentic AI.

ISG Research evaluated more than 100 different function points in 11 sections to assess the full scope of AI agent capabilities. It also examined the investment by the software provider in resources and improvements.

The research weights Capability at 40% of the overall rating. Oracle, Salesforce and ServiceNow are the Leaders in this category.

The significant, in-depth Capability evaluation framework for AI agents provides a substantive challenge for many software providers. The research largely focuses on how providers apply AI agents and the specific processes where some specialize on the application platforms, such as Microsoft, Oracle and Salesforce. Others specialize with automation platforms, such as Appian, Pega, ServiceNow and UiPath.

Software providers that have more breadth and depth across and support the entire set of needs fared better. Providers specializing in AI but without depth in agentic and generative AI platforms did not perform as well. The varying levels of specialization and capabilities for business found across software providers give enterprises a significant choice in AI agent products.

Reliability of the Product

For AI agent processes to operate efficiently and for workers to engage the applications, the software on which they run must reliably deliver the necessary performance and scalability using the existing architecture operating across the enterprise and cloud computing environments. The criteria include depth in the performance and scalability of a software provider’s products and architecture, including the metrics to ensure operations and configurability across data, users, instances, activities and tasks. It also examines the investment by the provider in resources and improvements.

The research weights Reliability at 10% of the overall rating. Oracle, IBM and AWS are the Leaders in this category. While not a Leader, ServiceNow was also found to meet a broad range of enterprise reliability requirements.

Reliability is an essential evaluation metric as it indicates the product’s ability to perform and scale to the defined enterprise requirements and how well it supports the continuous processing required for business continuity and operational resilience today and into the future.

Evaluating the performance and scalability readiness of software is not always easy as it depends on the type of computation and processing and the volume at which the data is being updated and used by processes and systems. Software providers that did not perform well in this category were not able to provide this level of information at any depth, even though it is necessary to establish the confidence required for provider selection.

Customer Experience

The importance of a customer relationship with a software provider is essential to the actual success of the products and technology. The advancement of the Customer Experience and the entire life cycle an enterprise has with its software provider is critical for ensuring satisfaction in working with that provider. Technology providers that have chief customer officers are more likely to have greater investments in the customer relationship and focus more on their success. These leaders also need to take responsibility for ensuring this commitment is made abundantly clear on the website and in the buying process and customer journey.

The research results in Customer Experience are ranked at 20%, or one-fifth, using the specific underlying weighted category performance as it relates to the framework of commitment and value to the software provider-customer relationship. The two evaluation categories are Validation (10%) and TCO/ROI (10%), which are weighted to represent their importance to the overall research.

The software providers that evaluated the highest overall in the aggregated and weighted Customer Experience categories are ServiceNow, Verint and Oracle. While not a Leader, Salesforce was found to meet a broad range of customer experience requirements. These category leaders best communicate commitment and dedication to customer needs.

Software providers that did not perform well in this category were unable to provide sufficient customer case studies to demonstrate success or articulate their commitment to customer experience and an enterprise’s journey. The selection of a software provider means a continuous investment by the enterprise, so a holistic evaluation must include examination of how they support their customer experience.

Oracle

Company and Product Profile

OCI Agent Platform and Development Kit, released May 2025, Oracle Fusion Data Intelligence, version 25.R2, OCI Generative AI Agents, OCI Data Science, release 119 and Oracle AI Agent Studio 25c, released June 2025

“Oracle offers integrated suites of applications plus secure, autonomous infrastructure in the Oracle Cloud. The Oracle Cloud Infrastructure (OCI) Generative AI Agents platform provides a fully managed, cloud native solution that lets businesses build, deploy, and manage AI agents. By leveraging state-of-the-art large language models (LLMs), the AI agents you create can revolutionize the way you interact with customers, automate workflows, and approach business problems.” – Oracle

Summary

Oracle was recognized as Exemplary, excelling in both Product and Customer Experience—driven by top-tier capabilities and strong TCO/ROI performance—and was named an overall Leader across all categories.

Oracle Exemplary rating with its overall grade of A- with an 86.7% performance. Oracle's best grouped results came in Product Experience with an 87.3% performance and an A- grade, due in part to its A in Capability. In Customer Experience, Oracle received an A- grade with an 84.4% performance due to its 85.3% performance in TCO/ROI. Oracle was designated a Leader in all categories.

Challenges

Oracle's Customer Experience was affected by limited references and case studies, while its Product Experience was shaped by opportunities to enhance overall user experience. Oracle's A- in Customer Experience was impacted by its A- in Validation, where it could improve references and case studies. Product Experience was impacted by its A- in Usability, where it could improve user experience.

Strengths

Oracle performed strongest in Product Experience, particularly for its agentic and advanced AI capabilities, and high Customer Experience investments. Oracle performed best in Product Experience with an A- grade, notably in Capability, where it received an A due to agentic AI and overall AI features. Oracle received an A- grade in Customer Experience, with an A- in TCO/ROI due to breadth of description and documentation for identifying and quantifying achievable benefits. 

Appendix: Software Provider Inclusion

For inclusion in the ISG Buyers Guide™ for AI Agents in 2025, a software provider must be in good standing financially and ethically, have at least $200 million in annual or projected revenue verified using independent sources, sell products and provide support on at least two continents and have at least 50 customers. The principal source of the relevant business unit’s revenue must be software-related, and there must have been at least one major software release in the past 12 months.

The ISG Buyers Guide ™ for AI Agents requires software providers and products to have a platform that supports intelligence and workflow, analytics and insights, AI overall, communication administration and specific AI support for agentic AI.

The research is designed to be independent of the specifics of software provider packaging and pricing. To represent the real-world environment in which businesses operate, we include providers that offer suites or packages of products that may include relevant individual modules or applications. If a software provider is actively marketing, selling and developing a product for the general market and it is reflected on the provider’s website that the product is within the scope of the research, that provider is automatically evaluated for inclusion.

All software providers that offer relevant AI agent products and meet the inclusion requirements were invited to participate in the evaluation process at no cost to them.

Software providers that meet our inclusion criteria but did not completely participate in our Buyers Guide were assessed solely on publicly available information. As this could have a significant impact on classification and ratings, we recommend additional scrutiny when evaluating those providers.

Products Evaluated

Providers of Promise

We did not include software providers that, as a result of our research and analysis, did not satisfy the criteria for inclusion in this Buyers Guide. These are listed below as “Providers of Promise.”