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Evaluating The IDC Conversational AI Platforms 2021 Vendor Assessment

And How Does It Compare To The Gartner Report on Conversational AI

Cobus Greyling
5 min readApr 11, 2022

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IDC MarketScape: Worldwide Conversational Artificial Intelligence Software Platforms for Customer Service 2021 Vendor Assessment

Introduction

The IDC & Gartner reports are about 3 months apart…The IDC report:

  1. Uses a different set of criteria for qualification and assessment.
  2. Shows the market size as part of their graphic representation, which is extremely insightful.
  3. The graph has two axes, Capabilities & Strategies.

Vendors On The IDC & Gartner Reports

The Gartner report has a total of 21 vendors, while IDC report has a total of 15.

Below, the platforms marked in red are exclusive to one of the reports. The platforms marked in green are on both reports.

The Gartner report has a total of 21 vendors, while IDC report has a total of 15. The platforms marked in red are exclusive to one of the reports. The platforms marked in green are on both.

Platforms glaringly absent from the IDC report are AWS & Rasa. As mention in the review of the Gartner report, the criteria for excluding Microsoft & NVIDIA from their report is well defined, but a bit harsh.

It’s good to see Microsoft in the IDC report. It would have been insightful if NVIDIA was included.

IDC Report Observations

  1. The size of the individual vendor markers in the IDC MarketScape represents the market share of each individual vendor within the specific market segment being assessed. This gives a good indication of market share in relation to strategy & capabilities.
  2. The market share of a product versus their placement indicates on how well they are leveraging their platform capabilities. Hence it is clear platforms like Cognigy & Kore.ai need to work on market exposure and awareness.
  3. It is good to see Nuance in the mix, with their considerable market share, on par with IBM & Microsoft.
  4. Amelia has a substantial market share.
  5. Google & Nuance should have been further up the chart, considering their time in market and market share.
  6. IDC ranks Microsoft fairly high. Microsoft has good individual solutions for TTS, STT, NLU, Bot Framework and Power Virtual Agents.
  7. Gartner placed emphasis on voice integration, which some platforms lack.
  8. It would make for interesting analysis if Gartner added market share to their report.
IDC MarketScape: Worldwide Conversational Artificial Intelligence Software Platforms for Customer Service 2021 Vendor Assessment

Above, the IDC MarketScape: Worldwide Conversational Artificial Intelligence Software Platforms for Customer Service 2021 Vendor Assessment.

As a reference, below is the Gartner Magic Quadrant for Enterprise Conversational AI Platforms.

Magic Quadrant for Enterprise Conversational AI Platforms

With the growing Conversational AI landscape, the threshold for innovation and differentiation are set increasingly higher as the table stakes increase. The market share of the smaller companies leading strategy and capability will invariably grow.

The Conversational AI Landscape

The conversational AI landscape is expanding, and not all platforms are complete chatbot or voicebot solutions. What we are seeing in the IDC & Gartner reports is a proliferation of Category 3 platforms, leading the way with low code/no code, cloud solution.

The Conversational AI landscape broken down into four categories.

The systems in Category 2 holds most of the market share, although not leading in capability and strategy. There should be a normalization at some time, where the Category 3 environments grow substantially in market share, or the Category 2 players improve on capability and strategy.

Category 3 is also very crowded.

There could also be a scenario where Category 2 players continue leveraging their market share by just maintaining parity with the Category 3 players.

Category 1 often forms the underlying engine for other environments. Like NVIDIA Riva, Hugging Face or Rasa.

Category 4 is a niche market with various Conversational AI tools, most notably here is HumanFist with their complete environment to manage NLU data. Ranging from Intent detection, to disambiguation, labeling and much more.

Conclusion

Organizations will have to be very discerning in their technology choices to ensure that their Conversational AI environment is able to scale well. Which will be sprawling into different mediums with disparate conversational affordances.

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Cobus Greyling

I explore and write about all things at the intersection of AI & language; LLMs/NLP/NLU, Chat/Voicebots, CCAI. www.cobusgreyling.com