The Forrester Wave™: Conversational AI Platforms For Employee Services, Q3 2026

Conversational AI Platforms For Employee Services Vendor Product Comparisons 2026

Key features and pros and cons of top Conversational AI Platforms For Employee Services products:

Atlassian - Leaders

Pros:

Context capabilities through Teamwork Graph that bridges employee context across tools
Ability to embed Rovo into key collaborative surfaces, including multiuser chat channels
Offers out-of-the-box agents for IT, HR, and more
Solid build and test capabilities
Committed significant resources to innovation and customer success with universal technical adoption success personnel

Cons:

Cloud SLA doesn't cover Rovo
Governance engine missing native real-time PII flagging/redaction for artifacts like transcripts
Agent generation functions still focus on prompts and aren't fully agent, tool, and knowledge aware
Prebuilt Rovo automations are entrenched in and depend on Atlassian tools
Pricing doesn't yet charge for consumption but there are limits that organizations can hit

Kore.ai - Leaders

Pros:

Agent management system with context engine supporting multiple context graphs and behavioral enrichment
Robust functionality for guardrails and enforcement delivering better answers and control over agent behaviors
Facilitates building agents using repeatable patterns with proactive skill suggestion
Analytics translate agent impact into dollars saved
Pricing is supremely flexible, supporting multiple consumption models (per user and outcome based)
Agent blueprint language approach to improve agent predictability

Cons:

Small, rapidly growing provider with less mature partner ecosystem than some others
Platform is extremely flexible but customers had to work closely with Kore.ai to accomplish complex automations
Lacks proactive knowledge gaps reporting

Salesforce - Leaders

Pros:

Context layer bridges employee context silos and provides enrichment with behavioral data like decision traces and Slack context
Script approach blends deterministic and model-driven decisions
Enforceable testing and builder that can use existing skills/tools to improve governance
Multiple domain agents out-of-the-box including incident swarming collaborator
Vision focused on unified context layer and proactive support with smart enhancements

Cons:

Short and long-term roadmap is limited, with most updates focused on ESM parity
Pricing has fluctuated and is a noted customer pain point
Conversational traces lack decision reasoning
Platform doesn't include dollar savings in business metrics
Platform experiencing growing pains

ServiceNow - Leaders

Pros:

Commitment to ensuring customers see value with large prebuilt platform, out-of-the-box integrations and actions
Dedicated people resources to drive success with noteworthy approach to customer success
Excellent guardrails enforcement and reasoning capabilities
Vision to serve as organization's front door wherever you want to work
Recently released EmployeeWorks product integrating Moveworks and Now Assist

Cons:

Pricing is complicated and often expensive, combining per user, ingested knowledge, and connectors
ServiceNow services consumption may be challenging to track
Application development, testing, and lifecycle management capabilities are limited in evaluated version
Platform lacking for those looking to build their own agent
Only provided one reference customer for evaluation

Automation Anywhere - Strong Performers

Pros:

Excellent AI observability with reasoning information for why certain tools or agents were called
Knowledge gap analytics complete with knowledge drafting to rapidly fill identified gaps
Strong governance controls and support for legacy systems including mainframes
Rapid and sustained innovation with continuous introduction of new features to fit user asks
Focus on adopter success

Cons:

Smaller-than-average partner network and fewer additional offerings
Can be stretched when accommodating emergent customer needs
Rapid and continuous developments mean not all pieces connect seamlessly
Lacks standard way to integrate with external agents
Only one reference customer responded to Forrester's outreach

BMC Helix - Strong Performers

Pros:

Approach to AI agent value with broad test suite to ensure agents work
HelixGPT Agent Outcomes dashboards help tie agents to dollars
Vision leaning into proactive support and meeting users and builders where they are
Planned analytics to help business proactively find value-generating AI use cases
Customers report easy time getting started with platform, particularly out-of-the-box features

Cons:

Pricing below par with customers needing to bring own language model and pay for model consumption separately
Guardrails and data security lack out-of-the-box PII flagging/redaction for artifacts like transcripts
Lacks user-facing reasoning
AI agent setup more akin to setup wizard than tools in most agent builder platforms
Agentic engine management and orchestration are responsibility of customer
Platform still being actively developed and changes rapidly

Glean Technologies - Strong Performers

Pros:

Outstanding context layer with some of strongest complex answering capabilities of all vendors evaluated
One of only few providers to support truly multiplayer interactions
Build and automation tooling are intuitive
History of proven innovation with forthcoming Waldo system genuinely differentiating for agentic planning
Offers per-user or consumption-based agent pricing

Cons:

Lacks universal customer success approach which is point of concern
Forward-deployed engineers and implementation services aren't the default AI motion
Lacks ability to test against batches of conversations (synthetic regression testing)
Doesn't yet have out-of-the-box knowledge gap analysis
Reference customers did not respond to Forrester's outreach

Microsoft - Strong Performers

Pros:

Ecosystem strengths with full omnichannel and multiplayer usage support
Can take advantage of emergent AI features like computer use
Platform notably easy to use and get started on
Offers various templates to help users get started
Significant partner network to make agents a reality for customers

Cons:

Vision is limited, lacking proactive position on employee services and more integrative or headless approach
PII redaction only supported for voice use cases
Doesn't have native version control for agents, instead recommends setting up own git
Lacks depth of functionality for any specific employee services use cases
Pricing unpredictable using combination of platform and consumption costs
Did not provide reference customers for evaluation

SoundHound AI - Strong Performers

Pros:

Commitment to adopter success with effective support throughout building journeys
Platform's support of AI-to-human handoffs allowing humans to act as bot unblockers
Builder has partial agent, tool, and knowledge aware alignment
Can ensure needed skills and knowledge are built out in platform
Willing to assist however possible

Cons:

Limited vision lacks emphasis on proactive employee services, cross-platform knowledge, or platform decomposition
Smaller partner program can reduce assistance available
Most planned enhancements remain focused on closing capability gaps
Platform missing basic capabilities like agent memory, user-facing reasoning, and sandbox testing
Pricing is mix of platform fee and consumption

EasyVista - Contenders

Pros:

Ability to operate alongside human agents with humans acting as expert bot unblocker
Humans can provide real-time direction to AI agent to resolve ticket or incident
Customers report quick start with the platform

Cons:

Vision missing focus on ability to embed it or build out employee context layer
Smaller provider with much of innovation and roadmap attempting to catch up with larger platforms
Customer success motion is basic and lacks adoption and deployment success assurances
Missing basic capabilities like support for Slack and basic voice
Extending platform outside premade plug-ins requires heavy configuration
Platform lags in agent process improvement analytics reducing proactivity
Needed care when converting existing services requests and knowledge to support self-service

HCLSoftware - Contenders

Pros:

Effective IT automation
Fairly straightforward to configure for IT assistance
Agent builder interface has significantly improved
Enables bringing in managed AI agent deployment with HCL BigFix AEX portfolio

Cons:

Still adapting to agentic orchestration with innovation and roadmap playing catch-up
Configuration-heavy approach requiring customers to bring, manage, and pay for own agentic model
Missing expected capabilities like support for contextualization layers like knowledge graph
Lacks end-user-facing decisioning reasoning
Limited native agent version control
Pricing not inclusive as customers must pay for own language model separately
Requires significant labor (usually from HCLSoftware) to make it work
Did not provide reference customers for evaluation

IBM - Contenders

Pros:

Agent orchestration engine base allows building wide range of use cases
Agent templates help jump-start efforts
Significantly improved build interface
Superior partner network
Expanding to support broader agent interoperability and decomposing into headless orchestrator

Cons:

Focuses primarily on providing broad platform and less on supporting specific use cases like employee services
Public roadmap is fairly basic
AI products often require heavy configuration and watsonx Orchestrate continues this trend
Guardrails and governance require specific configuration and management
Knowledge requires explicit designation and manual agent-by-agent assignment
Platform lacks proactive improvement analytics
Did not provide reference customers for evaluation

SymphonyAI - Contenders

Pros:

Managed approach to building, deploying, and managing AI agents results in impressive deployment success
Context graph that can bridge tooling silos
Provides out-of-the-box AI agents for employee IT automation
Noteworthy commitment to clients' adoption success

Cons:

Smaller provider with smaller partner network than others in evaluation
Most innovation and upcoming features are to fill gaps in functionality
More advanced use cases like telemetry processing using AI agents still on roadmap
Platform missing most administrator controls, no-code agent builders, observability, and advanced analytics
Lacks source citation enforcement for answers
Other domain support beyond IT and HR is limited
Lack of configuration/control can frustrate expansion
Reference customers did not respond to Forrester's outreach

FAQs

Q: Which vendors are Leaders in 2026?

A: Atlassian, Kore.ai, Salesforce, ServiceNow

Q: What does "Leader" mean in Forrester Wave terms?

A: Leaders are vendors that demonstrate the strongest current offering and strategy in the market. They have proven capabilities across the evaluation criteria and a clear vision for the future of conversational AI platforms for employee services.

Q: How do I interpret a Forrester Wave?

A: https://www.forrester.com/policies/forrester-wave-methodology/

Report:

Top Vendor Products for Conversational AI Platforms For Employee Services in 2026

Conversational AI Platforms For Employee Services Vendor Product Comparisons 2026

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FAQs

Q: Which vendors are Leaders in 2026?

Q: What does "Leader" mean in Forrester Wave terms?

Q: How do I interpret a Forrester Wave?

Reference