As the market maturity of AI-based solutions proliferates, global SaaS vendors vie for the attention of the B2B and B2C enterprise marketplace. This new C-AI market with over 1,000 vendors in the space competes on varying capabilities, applications, and market niches. It includes simpler FAQ chatbots and more sophisticated, trained virtual agents (VA)s.
As of January 2022, Gartner Research has now placed a number of these vendors in their “Magic Quadrant” Analysis, enabling some level of discernment for enterprises shortlisting a CAIP partner. However, the level of complexity and differentiation between these vendors’ varying capabilities and fit warrant situational discretion. Factors include use case-based research, capabilities analysis, overall deployment (design, build & run) considerations, and a robust ROI analysis.
By not performing a turnkey analysis, an enterprise could end up with a platform/technology that’s much more expensive than needed — not only in terms of cost but resourcing and time investments. This is complicated by the fact that enterprises can sometimes learn very little from proofs of concepts (POCs) since the POC is done at a lower level of sophistication than the target, production-level implementation. Figuring all this out is where Conversense Consulting can make a difference. Conducting qualitative and quantitative research of service providers, vendors, and technology fit, we investigate the factors that impact success, such as competitive forces, growth drivers, risks, issues, and trends. For example, in a C-AI Vendor and use case analysis, we can help with advisement on vendor selection weighting criteria including:
The sophistication of the underlying customer has an impact on the overall complexity of implementing and running a successful use case.
The number and complexity of integrations to back-end or external systems, such as authentication services, customer relationship management (CRM) systems, and support ticketing systems must be considered.
The number and types of channels and modalities to implement and support.
An accurate assessment of the use case to be implemented, associated risks, and possible pitfalls to success.
For sophisticated virtual agent deployment, the number of utterances or intents to support and the related tasks of configuring, tuning, and managing the training data also adds to the complexity.
For a look at Gartner Research’s 2022 C-AI Vendor evaluation, please see the below Link: