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Virtual Personal Assistants (VPA) and Smart Advisors: Autonomous Agent and Smart Machine Technology and the Market for Ambient User Experience

Virtual Personal Assistants (VPA) and Smart Advisors: Autonomous Agent and Smart Machine Technology and the Market for Ambient User Experience

Virtual Personal Assistants (VPA) and Smart Advisors use Autonomous Agents and Smart Machine technology to enable an Ambient User Experience for applications and services. The Internet of Things (IoT) intensifies this need as machines interact with other machines and humans autonomously.

In keeping with the theme of communications enabled applications, we also see VPA enabled apps becoming widespread to the point that they are embedded within most services. The preferred user interface for many Internet and wireless apps will ultimately become integrated with smart advisors and rely upon next generation interactions such as Haptic UI and other dynamic and contextual actions and interfaces.

This research evaluates the technologies, solutions, companies and market for Virtual Personal Assistants (VPA) and Smart Advisors. The report includes a market assessment and forecast to 2025. All purchases of Mind Commerce reports includes time with an expert analyst who will help you link key findings in the report to the business issues you're addressing. This needs to be used within three months of purchasing the report.

Target Audience:

Big Data and Cloud companies
Artificial Intelligence companies
Communication service providers
Internet and mobile app developers
Machine Language based app providers
Enterprise, SMB, and companies of all types

Companies/Solutions in Report:

24ME
AIVC
ALFRED
AMAZON ECHO
ANDY
APPLE SIRI
ASSISTANT.AI
AWESOME
BLACKBERRY ASSISTANT
BRAINA
BUDDY
CHARLIE
CLARA
CLOE
CUBIC
DENARRI
DRAGON GO
EASILYDO
EVA
EVI
FACEBOOK M
GOBUTLER
GOOGLE NOW
HELLO ALFRED
HOUND
HTC HIDI
IBM WATSON
INDIGO
JARVIS
JEANNIE
JIBO
JULIE DESK
MAGIC
MALUUBA
MICROSOFT CORTANA
MOTION.AI
MYCROFT
MYWAVE
NUANCE
OPERATOR
PENNY
POSTMATES
QUIP
RESERVE
RILEY
ROBIN
S VOICE
SILVIA
SIRIUS
SKYVI
SPEAKTOIT
UBI
VLINGO
VOICE ASSISTANT
VOICE MATE
VOKUL
WONDER
WUNDERLIST
X.AI
ZIRTUAL

General Methodology

Mind Commerce Publishing's research methodology encompasses input from a wide variety of sources.

We rely heavily upon our Subject Matter Experts (SME) in terms of their market knowledge, unique perspective, and vision. We utilize SME industry contacts as well as previous customers and participants in our market surveys and interactive interviews.

In addition, we rely upon our extensive internal database, which contains modeling, qualitative analysis, and quantitative data. We review secondary sources and compare to our primary sources to update previous findings (for prior version reports) and/or compile baseline information for technology and market modeling.

We share preliminary models with industry contacts (select previous clients, experts, and thought leaders) to verify the veracity of initial modeling. Prior to final report production (analysis, findings, and conclusions), we engage in an internal review with internal SMEs as well as cross-expertise, senior staff members to challenge results.

We believe that forecasts should be prepared as part of an integrated process which involves both quantitative as well as qualitative factors. We follow the following 3-step process for forecasting.

Forecasting Methodology

Step 1 - Forecasts Input: The inputs for the present and historical revenues are derived from industry players. Financial and other quantitative data for individual sub-market categories are derived from original research and tested with interviews with major industry constituents.

Step 2 - Forecasting of Future Years: Mind Commerce extends forecasts based on a variety of factors including demand drivers as well as supply side data. Key success factors and assumptions are considered.

Step 3 - Validation of Data: The final step is to validate projections, which is accomplished in consultation with both internal and external industry experts, including both topic and regional experts. Adjustments are made to the forecasts based on factors identified throughout this process.


1.0 Introduction
1.1 Technology Trend And Virtual Private Assistants (Vpa)
1.2 Enterprise Intelligent Assistants And Vpa
1.3 What Is Vpa?
1.4 Benefits Of Vpa
1.5 Potential Risks
2.0 Vpa Technology Drivers
2.1 Digital Mesh And Ambient User Experience
2.2 Smart Machine Implementations
2.3 Autonomous Agents And Advisors
2.4 Autonomous Robots
2.5 Social Robots
2.6 Natural Language Processing
2.7 Speech Recognition
2.8 Information Of Everything
2.9 Machine Reading Comprehension (Mrc)
3.0 Vpa Growth Drivers
3.1 Friendly Assistance
3.2 Quality Lives
3.3 Customer Managed Relationship (Cmr)
3.4 Personal Cloud
3.5 Contextual Actions
3.6 Api And Mobile Apps
4.0 Vpa Ecosystem Impact
4.1 Ecosystem Analysis
4.2 Master Controller
4.3 Corporate Advertising
4.4 Customer Care
4.5 Online Advertising
4.6 Online Payment
4.7 Augmented Human Reality
4.8 Business Model
4.9 End Users
4.10 Intelligent Agents
4.11 Audiences
5.0 Vpa Solutions And Use Cases
5.1 Google Now
5.2 Apple Siri
5.3 Microsoft Cortana
5.4 Facebook M
5.5 Mywave
5.6 Nuance
5.7 Motion.Ai
5.8 Indigo
5.9 Dragon Go
5.10 Vokul
5.11 Robin
5.12 24me
5.13 Quip
5.14 Wunderlist
5.15 Speaktoit
5.16 Amazon Echo
5.17 Braina
5.18 S Voice
5.19 Assistant.Ai
5.20 Voice Mate
5.21 Blackberry Assistant
5.22 Silvia
5.23 Htc Hidi
5.24 Ibm Watson
5.25 Cubic
5.26 Hound
5.27 Jibo
5.28 Maluuba
5.29 Mycroft
5.30 Sirius
5.31 Ubi
5.32 Vlingo
5.33 Skyvi
5.34 Jeannie
5.35 Easilydo
5.36 Voice Assistant
5.37 Evi
5.38 Operator
5.39 Charlie
5.40 Wonder
5.41 Magic
5.42 Alfred
5.43 Reserve
5.44 Penny
5.45 Clara
5.46 Postmates
5.47 Jarvis
5.48 Awesome
5.49 Cloe
5.50 X.Ai
5.51 Riley
5.52 Julie Desk
5.53 Zirtual
5.54 Denarri
5.55 Aivc
5.56 Eva
5.57 Andy
5.58 Hello Alfred
5.59 Buddy
5.60 Gobutler
6.0 Vpa Market Projections Through 2025
6.1 Global Market Value
6.2 Market Value By Region
6.3 Market Value By Core Technology
6.4 Market Value By End User
6.5 Market Value By Autonomous Agents
6.6 Market Value By Ecosystem Players
6.7 Market Value By Business Model
6.8 Enterprise Vpa Adoption
7.0 Appendix Artificial Intelligence And Machine Learning
7.1 Artificial Intelligence
7.2 Machine Learning
Figures
Figure 1: VPA Ecosystem
Figure 2: Google Now Card
Figure 3: Apple’s Siri Voice Control
Figure 4: Microsoft Cortana Usage Diagram
Figure 5: Facebook M Interface and Tests
Tables
Table 1: VPA Market Value by Geographic Region 2025
Table 2: VPA Market Value by Core Technology 2025
Table 3: VPA Market Value by Types of End User 2025
Table 4: VPA Market Value by Types of Autonomous Agents 2025
Table 5: VPA Market Value by Ecosystem Participants 2025
Table 6: VPA Market Value by Business Model 2025

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