Report:
The Forrester Wave™: Conversational AI Platforms For Employee Services, Q3 2024
How does Forrester define the Conversational AI Platforms For Employee Services market in 2024?
Generative AI has aggressively disrupted the conversational AI for employee services market, resetting expectations on time to value and ease of implementation. However, organizations need more than just large language models (LLMs) for employee services - they require up-to-date knowledge, accurate documentation, end-to-end workflows, domain understanding, integration awareness, and governance controls. The market is solving this by pairing language models with automation platforms through mixed-model orchestration, which allows systems to dynamically turn user requests into smaller tasks. This improves action plan generation, enables better domain understanding, enhances context persistence, increases governance granularity, and enables capabilities like agentic systems and mid-flow retasking. The evaluation assessed 15 providers across 28 criteria to identify Leaders, Strong Performers, Contenders, and Challengers in this rapidly evolving market.
Key Facts for The Forrester Wave™: Conversational AI Platforms For Employee Services, Q3 2024 in 2024
- Publication Date: 25-Jul-2024
- Document ID:
- Summary: In our 28-criterion evaluation of conversational AI for employee services providers, we identified the most significant ones and researched, analyzed, and scored them. This report shows how each provider measures up and helps technology professionals select the right one for their needs.
- Authors: Will McKeon-White
How did the Conversational AI Platforms For Employee Services market evolve in 2024?
- Generative AI has aggressively disrupted the conversational AI for employee services market, resetting expectations on time to value and ease of implementation
- Organizations need more than just large language models (LLMs) for employee services - up-to-date knowledge, accurate documentation, end-to-end workflows, domain understanding, integration awareness, and governance controls are critical
- The market is solving challenges by pairing language models with automation platforms and doing more than just passing off to a genAI API
- Vendors are using LLMs to improve language processing and embedding them to accelerate use-case development
- Leaders are orchestrating mixed models to create surprisingly adaptable conversation engines with agentic capabilities
- Mixed-model orchestration allows systems to dynamically turn user asks into smaller tasks, improving action plan generation, domain understanding, context persistence, governance granularity, and enabling midflow retasking
- 15 providers were evaluated in this assessment
- The evaluation uses 28 criteria across current offering, strategy, and market presence
What product features are required to be included in this year's evaluation?
- A conversational AI product for employee services that can support and is actively employed for multiple common employee services workloads
- A solution that is available for purchase independent of services contracts, not contingent on an additional, existing, or standing services contract from the provider
- A solution that provides native advanced language processing capabilities included in the contract, such as an NLP engine or access to an LLM, with native support for English
- Product revenue of at least $15 million annually related to conversational AI for employee services and at least 30 active paying customers (including licensing, subscription, and maintenance, but not consulting services)
- Active interest among Forrester clients demonstrated through inquiry mentions and inclusion on shortlists
What are the common features of top products in the Conversational AI Platforms For Employee Services space?
No common features specified.
Scope Exclusions
- Solutions that require a services contract to purchase or use
- Products without native advanced language processing capabilities (NLP engine or LLM access)
- Vendors with less than $15 million in annual product revenue
- Vendors with fewer than 30 active paying customers
- Solutions that do not natively support English language
- Products not actively employed for multiple common employee services workloads
- Vendors without demonstrated active interest among Forrester clients
Inclusion Criteria
Vendors must, among other requirements:
- A conversational AI product for employee services that can support multiple common employee services workloads
- A solution available for purchase independent of services contracts
- A solution that provides native advanced language processing capabilities, including NLP engine or LLM access, with native English support
- Product revenue of at least $15 million annually with minimum 30 active paying customers
- Active interest among Forrester clients through inquiry mentions and inclusion on shortlists
Offering Strengths — Relative Weighting
- Multilingual support — 3%
- Advanced language facilities — 7%
- Omnichannel and voice support — 5%
- Automation facilities — 4%
- Agent augmentation — 4%
- Generative answers — 6%
- Integration development facilities — 5%
- Prebuilt integrations — 5%
- Generative orchestration — 6%
- Predefined models and language sets — 3%
- Workflow creation acceleration — 5%
- Development and deployment speed — 7%
- Model governance — 5%
- Development interface — 7%
- Language training — 5%
- Platform deployment and administration — 3%
- Privacy — 5%
- Success reporting and metrics — 5%
- Demand reporting and metrics — 5%
- Technical reporting and metrics — 5%
Strategy Strength — Relative Weighting
- Vision — 17%
- Innovation — 17%
- Roadmap — 17%
- Partner ecosystem — 17%
- Adoption — 17%
- Pricing flexibility and transparency — 17%
FAQs
Q: What does this research cover?
A: This research evaluates the 15 most significant conversational AI platforms for employee services providers using 28 criteria grouped into current offering, strategy, and market presence. It analyzes how vendors are leveraging generative AI, LLMs, mixed-model orchestration, and agentic capabilities to help organizations provide better employee services through conversational interfaces.
Q: Who should use this research?
A: Technology professionals responsible for selecting conversational AI platforms for employee services should use this research. It helps organizations evaluate vendors based on their specific needs, compare provider capabilities across key criteria, and understand which vendors are best suited for different use cases - from rapid adoption solutions to highly configurable platforms requiring developer resources.
Q: What are the mandatory features of vendors included in this market?
A: To be included in this evaluation, vendors must have: (1) a conversational AI product actively employed for multiple common employee services workloads, (2) a solution available for purchase independent of services contracts, (3) native advanced language processing capabilities (such as an NLP engine or LLM access) with native English support included in the contract, (4) minimum annual product revenue of $15 million with at least 30 active paying customers (including licensing, subscription, and maintenance revenue, excluding consulting services), and (5) demonstrated active interest among Forrester clients through inquiry mentions and inclusion on vendor shortlists.
Q: What are some reasons for not being included in this report?
A:
- Solutions only available through services contracts rather than independent product purchase
- Lack of native advanced language processing capabilities (no NLP engine or LLM access included)
- Annual product revenue below $15 million threshold
- Fewer than 30 active paying customers
- No native English language support
- Product not actively used for multiple common employee services workloads
- Insufficient client interest demonstrated through Forrester inquiries and shortlist inclusions
- Vendor declined to participate in the evaluation process (these may still be scored as nonparticipating vendors if they meet inclusion criteria)
Q: What should buyers consider when evaluating products in this market?
A:
- Leverage agentic and mixed-model capabilities to create natural conversations - look for systems that can identify, interpret, and individualize workflows to provide significant troubleshooting enhancement and handle unexpected utterances
- Extend generative governance - prioritize vendors with layered controls that manage both inputs to models and assess outputs for appropriateness, accuracy, and coherence, which are critical for safe deployment
- Provide success assurance - despite advances in ease of consumption, AI is hard to manage, so prioritize vendors that help ensure customer success through managed services or dedicated support representatives
- Evaluate the vendor's approach to LLM integration - whether they provide managed LLMs, support bring-your-own models, or offer mixed-model orchestration capabilities
- Consider the configuration effort required - some platforms offer out-of-the-box capabilities while others require significant developer resources
- Assess domain focus on employee services - some vendors provide pre-built workflows and language models specific to employee services while others are more domain-agnostic
- Review integration capabilities - evaluate both pre-built connectors and the ease of creating custom integrations to your enterprise systems
- Understand the vendor's customer success strategy - whether they provide dedicated support, managed services, or rely primarily on self-service tools
Q: How has the Conversational AI Platforms For Employee Services market evolved in 2024?
A:
- GenAI has aggressively disrupted the conversational AI market, resetting expectations on time to value and ease of implementation
- The market is moving beyond simple LLM integration to mixed-model orchestration that coordinates multiple models and expert systems
- Vendors are embedding LLMs not just to improve language processing but to accelerate use-case development
- Agentic capabilities are emerging as a key differentiator, enabling systems to dynamically identify, interpret, and individualize workflows
- Organizations require layered governance controls that manage both inputs to models and assess outputs for appropriateness, accuracy, and coherence
- Success assurance and customer support have become critical differentiators as AI systems remain difficult to implement despite advances in ease of consumption
- The market is shifting from configuration-heavy approaches to more automated, self-developing conversational AI platforms
- Integration of conversational AI with broader automation platforms and enterprise systems is becoming essential for end-to-end workflow completion
Q: What differentiates Strength of Offering vs. Strength of Strategy?
A: Current Offering evaluates the strength of each vendor's existing product capabilities, features, and technical implementation across 20 weighted criteria including multilingual support, automation facilities, generative AI capabilities, development tools, governance, and reporting. Strategy evaluates the vendor's future direction and business approach across 6 equally-weighted criteria: vision for market evolution, innovation in product development, product roadmap, partner ecosystem strength, customer adoption support, and pricing transparency. Offering focuses on 'what the product can do today' while Strategy focuses on 'where the vendor is going and how they support customers.'
Reference
- Forrester, The Forrester Wave™: Conversational AI Platforms For Employee Services, Q3 2024, 25-Jul-2024, ID
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