Every month, G2's Market Research team adds five to ten new categories to the platform, and this month's batch captures a market in the middle of a real inflection point. Across nearly every new category introduced, the same underlying story shows up: AI is no longer a feature bolted onto existing software, it's becoming the operating layer itself.
Take conversational AI. What used to mean a narrow customer-service chatbot or a simple FAQ tool has evolved into something far more foundational. The new Enterprise AI Chatbot category recognizes platforms that ground conversations in organizational knowledge, connect to internal systems, and operate within enterprise-grade security and governance frameworks, spanning IT, HR, legal, finance, and operations.
That same shift from passive assistant to active collaborator shows up in how people browse the web. The new Agentic AI Browser category reflects a move from AI as something you chat with to AI as something that acts on your behalf, summarizing content, navigating sites, and completing multi-step workflows directly inside the browser.
The same transformation is reshaping how software itself gets built. AI Engineering Accelerators represent a new class of delivery partner that doesn't just hand AI tools to individual developers, but builds AI into the structure of delivery itself: how teams are organized, how work is sequenced, and how reusable engineering assets compound value across projects. It's a meaningful departure from traditional IT services and staff augmentation, and a signal that some firms are rebuilding their delivery models around AI from the ground up rather than layering it on top.
Even categories that aren't AI-native are being pulled into this orbit. The Databricks Services Ecosystem category, for instance, reflects how AI/ML workloads have become central to data platform consulting, not a side practice, as organizations migrate legacy systems into lakehouse architectures built for AI at scale.
Legal work is getting pulled into the same current. SoftwareAdvice's new AI Legal Assistants market, the platform’s first entry into this space, points to growing demand for AI tools purpose-built for legal teams rather than general-purpose assistants stretched to fit legal workflows, a sign that even traditionally conservative, compliance-heavy functions are starting to carve out dedicated AI tooling of their own. Below, we break down what's driving each one and the top products leading the way at launch.
1. Enterprise AI Chatbot
About this category: Enterprise AI chatbots are AI-powered conversational platforms that help organizations automate, manage, and govern interactions across employees, customers, and partners. These tools use large language models, natural language processing, retrieval-augmented generation, and enterprise knowledge integrations to deliver context-aware responses, complete tasks, and support conversations across business functions.
Why it was introduced: “As AI transforms how organizations communicate, operate, and deliver services, the conversational interface has become a critical layer of enterprise infrastructure. Organizations are managing growing volumes of interactions across employees, customers, and partners, but many still rely on fragmented tools that create inconsistency, inefficiency, and compliance risk.
G2 created this category to recognize AI-powered conversational platforms built specifically for enterprise deployment. These tools go beyond general-purpose consumer chatbots or simple FAQ bots by grounding conversations in organizational knowledge, connecting to internal systems, and operating within enterprise-grade security, governance, and compliance frameworks.
Unlike traditional chatbot tools, enterprise AI chatbots are designed to support dynamic, context-aware conversations across the organization. They can retrieve relevant information in real time, reason over enterprise knowledge, automate workflows, and provide consistent, governed responses across functions such as IT, HR, legal, finance, customer service, and operations.
This category reflects a broader market evolution: conversational AI is no longer a novelty or a narrow customer service tool. It is becoming a horizontal capability that shapes how work gets done, how knowledge is accessed, and how organizations manage interactions at scale. As large language models become more deeply embedded in enterprise workflows, organizations need conversational AI platforms that can deliver intelligent experiences without compromising security, governance, or auditability.
Enterprise AI chatbots represent the conversational backbone of the modern enterprise. They help organizations move from fragmented, reactive interactions to continuous, intelligent, and governed conversational experiences across the enterprise lifecycle.
– Bijou Barry, AI Principal Analyst
The top three products in this category, ranked by popularity at the time of launch, are:
2. Agentic AI Browser
About this category: Agentic AI browser software combines traditional web browsing with AI-powered agents that can understand user intent, automate browser-based tasks, and execute workflows across websites and business applications. These platforms enable users to summarize content, extract data, complete multi-step actions, and interact with web applications using natural language commands, all within the browser environment. By integrating with productivity tools, enterprise systems, and AI models, agentic AI browsers help teams streamline repetitive work, improve research efficiency, and enhance productivity while maintaining governance and human oversight for sensitive actions.
Why it was introduced: “As AI moves from simple chat interfaces to action-oriented agents, browsers are becoming the new operating layer for work. Agentic AI Browsers signal a broader shift from AI as an assistant to AI as an active collaborator capable of understanding context, navigating systems, and completing tasks across the web. This category highlights the growing demand for AI-native browsing experiences that improve productivity while maintaining enterprise-grade control and security.”
- Neeraja Prakash, Market Research Analyst
The top three products in this category, ranked by popularity at the time of launch, are:
3. AI Engineering Accelerators
About this category: AI engineering accelerators are AI-embedded software delivery partners that use proprietary frameworks, automation agents, reusable engineering assets, and AI-native delivery workflows to help organizations design, build, modernize, and maintain software faster. These providers apply artificial intelligence across the software development lifecycle, from product discovery and architecture to code generation, testing, modernization, DevOps, and sustained engineering operations.
Why it was introduced: “As AI reshapes how software is designed, built, and maintained, engineering delivery itself is undergoing a fundamental transformation. Organizations are under growing pressure to ship faster, modernize legacy systems, and scale product development, but traditional delivery models are often too slow, too costly, and too disconnected from the realities of AI-driven software development.
G2 created this category to recognize a new class of AI-embedded delivery partners that systematically operationalize artificial intelligence across engineering workflows. These providers go beyond using AI as a productivity tool for individual developers. They build AI into how delivery teams are structured, how work is sequenced, and how reusable assets compound value across engagements.
Unlike traditional IT services, outsourcing, or staff augmentation providers, AI engineering accelerators are built around acceleration as the delivery model. They bring proprietary AI frameworks, reusable automation agents, and proven workflows to complex engineering challenges, helping organizations compress timelines, reduce manual engineering lift, and create durable AI-enabled patterns inside their teams.
The rise of this category reflects a broader shift in the engineering services market. Some firms are adding AI features to legacy delivery models, while others are rebuilding delivery around AI from the ground up. AI engineering accelerators create a clearer home for the latter: providers that do not fit neatly into software product categories, but represent one of the most consequential emerging markets in enterprise technology services.
As CTOs, VPs of Engineering, and technology-forward investors seek partners that can deliver measurable acceleration rather than simply more headcount, AI engineering accelerators are becoming a critical category for modern software delivery.
– Bijou Barry, AI Principal Analyst
The top three products in this category, ranked by popularity at the time of launch, are:
4. Analyst Relations (AR) Agencies
About this category: Analyst Relations (AR) Agencies help B2B technology companies build and manage relationships with industry analysts who shape market perception and influence buying decisions. Analyst relations services include identifying relevant analysts, building structured AR programs, coordinating analyst briefings, and guiding companies through report evaluations published by major research analyst firms.
Why it was introduced: G2 created this category to recognize agencies whose primary focus is helping companies build and manage relationships with industry analysts. AR agencies specialize in analyst relations strategy, analyst engagement, category positioning, market narrative development, and evaluation readiness, while broader PR, marketing, and communications firms may (or may not) address these areas as part of a wider service offering. Creating a dedicated Analyst Relations (AR) Agencies category reflects this distinction, and makes it easier for buyers to find agencies with specific analyst relations expertise.
– Julie Jung, Senior Research Analyst, Sales and Marketing
The top three products in this category, ranked by popularity at the time of launch, are:
5. Product Engineering Services
About this category: Product engineering services providers help organizations design, develop, test, and industrialize physical products across the product lifecycle. These services include product design, engineering validation, manufacturing engineering, and production optimization.
Key capabilities include CAD and simulation, prototyping, design for manufacturability (DFM), production process engineering, industrial automation, and lifecycle engineering. These services accelerate time-to-market, improve product quality, and ensure efficient manufacturing readiness.
Unlike pure software or IT services, Product Engineering Services focus on end-to-end engineering of physical products, including both product development and manufacturing engineering.
Why it was introduced: This category was introduced to help buyers identify providers delivering end-to-end product and manufacturing engineering services, distinct from IT services, consulting, or software engineering categories. Vendors in this space are currently fragmented across multiple categories that do not reflect their full engineering lifecycle capabilities. This category improves discoverability and enables more accurate comparison of engineering service providers.
– Sanjana V Prasad, Associate Market Research Analyst
The top three products in this category, ranked by popularity at the time of launch, are:
6. Weather Data
About this category: Weather data software delivers real-time, historical, and forecasted weather data through application programming interfaces (API), dashboards, and data feeds. These platforms help businesses monitor weather conditions, prepare for weather-related impacts, and make weather-informed decisions using features such as severe weather alerts, weather-triggered automation, and location-based weather data integrated within operational systems, applications, and analytics workflows.
Why it was introduced: As organizations increasingly rely on data-driven planning and risk management, Weather Data Software has seen growing adoption across industries—from transportation and agriculture to retail and energy. These platforms are helping teams anticipate weather-related disruptions, improve operational efficiency, and make more informed decisions by embedding weather intelligence directly into business workflows."
— Chitransha Joshi, G2 associate research analyst for Vertical Industry
The top three products in this category, ranked by popularity at the time of launch, are:
7. Databrick Services Ecosystem
About this category: Databricks consulting services providers are business service providers specializing in implementing, optimizing, and managing solutions on the Databricks Data Intelligence Platform. These providers offer services spanning data engineering, data warehousing, AI/ML, and analytics workloads, helping organizations migrate legacy systems, build lakehouse architectures, and operationalize AI on Databricks.
Why it was introduced: "Databricks has built one of the largest consulting partner ecosystems in the data and AI space, with over 1,500 C&SI partners. As more organizations migrate to the Databricks lakehouse for data engineering, warehousing, and AI workloads, finding the right implementation and optimization partner has become a critical buying decision. This category gives buyers a dedicated space to compare providers across specializations like data warehouse migrations, AI, and industry verticals, following the same model as our existing ecosystem categories for Salesforce, AWS, and Atlassian."
- Tian Lin, Senior Research Analyst
The top three products in this category, ranked by popularity at the time of launch, are:
Category Spotlight: AI Legal Assistants: Software Advice's New, Emerging Market
Software Advice hasn't launched a new market category in a decade. That alone makes AI Legal Assistants worth paying attention to, but the reason it broke a ten-year pattern is the more interesting part.
For years, legal teams adopting AI had to make do with tools built for someone else. A general-purpose AI assistant might draft a memo or summarize a document, but it wasn't built around privilege, citation accuracy, jurisdictional nuance, or the kind of audit trail a legal team actually needs to trust the output. Legal buyers were left translating generic AI capabilities into legal use cases themselves, with no dedicated category to compare vendors who'd actually solved for that problem.
That gap is exactly what this launch addresses. It's a recognition that legal work has specific enough demands, accuracy under scrutiny, defensibility, integration with case management and research systems, that it warrants tools purpose-built for the function rather than general AI stretched to fit. That distinction matters more in legal than almost anywhere else: a hallucinated citation or a misread clause doesn't just create inconvenience, it creates liability.
It's also a signal about where AI adoption is heading more broadly. Legal has historically been one of the more cautious, compliance-heavy functions when it comes to new technology, for good reason. The fact that it's the category significant enough to break a ten-year freeze on new markets suggests the tooling, and buyer confidence in it, has matured past the experimental stage. When a famously risk-averse function gets its own dedicated AI category it's a strong indicator that AI tooling is becoming infrastructure across the board, not just in lower-stakes functions.
For buyers, the practical upside is straightforward: a clearer way to evaluate and compare vendors actually built for legal workflows, instead of trying to reverse-engineer whether a general AI tool can be trusted with legal work.
Vendor Spotlight:
There’s always something new on G2!
On average, G2’s Market Research team adds 5–10 new categories per month, so we encourage you to review our research agenda and utilize the all-new G2.ai to leave a voice review on the software you recommend!
Come back next month to see additional new categories on G2! And, check out the new categories that went live last month.
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