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Generative AI (GenAI) is reshaping how businesses operate, innovate, and deliver value across industries. Defined by Gartner as technologies capable of generating unique content, strategies, and designs by learning from vast data repositories, GenAI has become a cornerstone for enterprises seeking to future-proof their operations. However, despite its potential, businesses often struggle with choosing the right platform, scaling use cases from pilot to production, and measuring ROI effectively.
Navigating the fast-evolving GenAI landscape is a daunting task for decision-makers. With hundreds of vendors and innovations emerging weekly, the risk of falling behind competitors is real. Waiting for a “perfect” solution can lead to stagnation, while acting too quickly may result in overlooking valuable opportunities.
To stay competitive, enterprises need a strategic approach: regularly updated market insights and a robust framework for evaluating vendors. The focus should be on asking the right questions about scalability, integration, and long-term value rather than simply chasing the latest trends. By balancing agility with due diligence, organizations can make informed decisions that align with their goals while staying ahead in this dynamic market.
In its latest Innovation Guide for Generative AI Technologies, Gartner provides a comprehensive framework for evaluating GenAI vendors in this dynamic and fast-evolving market. The report also provides a graphical representation of the vendor’s position in the Emerging Market Quadrant for specific categories. The Emerging Market Quadrants evaluate vendors on their features and future potential.
Kore.ai is positioned as a leader in two Emerging Market Quadrants by Gartner.
- Generative AI Engineering
- GenAI Applications (AI Knowledge Management and General Productivity Applications)
GenAI market segments
As Gartner defines it, generative AI refers to technologies that “can generate new derived versions of content, strategies, designs, and methods by learning from large repositories of original source content.” Its impact spans key areas such as content creation, discovery, and authenticity; automation of human tasks; and enhancements to customer and employee experiences.
Rather than being a standalone market, generative AI permeates the entire technology stack and transforms nearly every industry. This revolutionary approach to technology is reshaping how both consumers and employees interact with it. Gartner’s Emerging Market Quadrants™, introduced in June 2024 modeled after Magic Quadrants™, break the generative AI landscape into four submarkets:
- Infrastructure Providers: Deliver compute, storage, and networking support tailored to generative AI demands.
- Model Providers: Offer both commercial and open-source foundation models.
- GenAI Engineering Tools: Enable end-to-end lifecycle management, development, deployment, and orchestration of GenAI applications.
- GenAI Applications: Leverage generative AI to enhance user experiences and task execution for desired outcomes.
Generative AI Engineering as Defined By Gartner is vendors covering full-model life cycle management, specifically adjusted to and catering to developing, refining and deploying generative models (e.g., LLMs) and other GenAI artifacts in production applications as well as overall processes orchestration. GenAI-empowered agentic technology will shift architecture strategies to solutions toward markets in multiagent systems and simulation. The definition now covers the complete agentic application lifecycle: data pipelines, orchestration, observability, automation. Full stack. End-to-end.
Generative AI Applications subsegment as defined by Gartner is GenAI applications use GenAI capabilities for user experience and task augmentation to accelerate and assist the completion of a user’s desired outcomes. When embedded in the experience, GenAI offers richer contextualization for singular tasks such as generating and editing text, code, images and other multimodal output. As an emerging capability, process-aware GenAI agents can be prompted by users to accelerate workflows that tie multiple tasks together.
Kore.ai is positioned as a leader in two of the four categories of GenAI vendors
Gartner assessed vendors in the generative AI space based on their technical capabilities, product features, and future potential in GenAI Engineering and GenAI Applications. Kore.ai has been recognized as an emerging leader in two key Emerging Market Quadrants (EMQs):
- GenAI Engineering
- GenAI Applications, specifically in AI Knowledge Management and General Productivity Applications.
June 2025 - Generative AI Engineering Quadrant
June 2025 - AI Knowledge Management Apps Quadrant
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Access the full report here.
Our integrated approach, combining an agent platform with a search AI platform, is precisely what positioned us for recognition in this segment.
The following excerpt from the report captures this evolution perfectly: "Vendors who provide platforms that orchestrate the entire model and application life cycle, especially when models power the intelligence underneath apps, are emerging to help enterprises move quickly from ideation to development, testing, deployment, monitoring and optimization."
This recognition highlights Kore.ai’s ability to anticipate evolving market needs, deliver enterprise-ready innovations, and maintain a leadership position in the generative AI space through cutting-edge solutions.
"Being named an emerging leader in these key categories reflects our deep expertise in understanding evolving market needs and delivering cutting-edge AI innovations. This recognition reinforces our mission to help enterprises reimagine with AI across workplace operations, business processes, and customer support" - Raj Koneru CEO & Founder, Kore.ai
Kore.ai’s approach to Generative AI engineering
Our enterprise customers are eager to harness advanced AI technologies to transform workplace operations, streamline business processes, and enhance customer service. Kore.ai enables this transformation through our Agent Platform, which functions as AI for Work, AI for Process, and AI for Service. Our offerings include a robust agent platform and no-code tools designed to help enterprises derive tangible value from AI.
What sets Kore.ai apart is our model-agnostic, cloud-agnostic, and infrastructure-agnostic approach, allowing enterprises to seamlessly integrate best-of-breed solutions. The platform provides end-to-end capabilities to experiment, design, build, test, deploy, and scale AI Agents, Agentic workflows, and GenAI applications. With features like visual drag-and-drop builders, a prompt library, AI agent templates, an extensive LLM library, customizable templates, robust security measures, AI transparency, and over 180 prebuilt integrations tailored to various industry domains, Kore.ai ensures enterprises have everything they need to innovate and succeed with AI.
Two important engineering capabilities - Observability and Orchestration - stand out in the report. Elements such as loss of context, factual accuracy drift, hallucination or tone alteration (abusive/rude), reasoning and decision making are part of an automated monitoring and observability capability. Also, vendors that offer GenAI platforms to orchestrate the entire model and application life cycle, especially when models power the intelligence underneath apps, are emerging to help enterprises move quickly from ideation to development, testing, deployment, monitoring and optimization.
Key considerations for implementing GenAI successfully
To successfully implement and scale GenAI, enterprises should focus on reducing technical debt, leveraging enterprise knowledge assets, and ensuring responsible AI practices. It’s vital to evaluate both existing application roadmaps and vendor solutions to design a cohesive AI architecture while anticipating the rapidly evolving AI landscape.
Recommended Reading:
10 Best Practices to Scale Generative AI Across Enterprises - Gartner
Way Forward:
The path to GenAI success lies in making informed decisions, scaling strategically, and measuring impact effectively. Whether you’re starting your journey or looking to scale existing initiatives, Gartner’s report and Kore.ai’s resources can provide the guidance you need.
Ready to navigate the GenAI revolution?
If you have questions or would like to strategize your GenAI implementation,
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