Best 20 AI Assistant Tools for Business and Personal Productivity in 2023

These top AI assistant tools for home and work are capable of understanding and interpreting human language, allowing users to communicate with technology in a more intuitive and conversational manner. They can perform tasks such as answering questions, providing recommendations, and even controlling smart devices, making them an invaluable tool in today’s digital landscape.

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This guide provides an in-depth look at the top 20 AI assistant tools today based on capabilities and value.

1. Alexa

Alexa is the pioneering cloud-based conversational AI assistant developed by Amazon. It powers the company’s popular Echo smart speakers and other Alexa-enabled devices. Alexa allows users to interact through voice requests using supported devices. The Alexa Skills Kit enables developers to expand Alexa’s capabilities by building custom skills that add new functions. There are over 100,000 skills available that allow Alexa to do everything from control smart home devices to stream music and audiobooks. 

Alexa can also make calls, send messages, set reminders, provide weather forecasts, answer general questions, and more. Alexa gets smarter continuously with new features and is the most widely adopted AI assistant with broad consumer recognition. It offers an extensive ecosystem of compatible smart home devices and skills to enhance functionality. Alexa excels at automating home tasks and delivering information on-demand using voice.

Integration and Implementation

• Works out of the box with Alexa-enabled devices like Echo.
• Alexa Smart Home Skills Kit enables appliance makers to integrate Alexa control.
• Alexa Voice Service enables developers to integrate Alexa into their own devices and apps.
• Skills can be built via Alexa Skills Kit and published on the Alexa Skills Store.

Pros

• Most popular and widely adopted assistant
• Large ecosystem of Skills and smart home devices
• Easy to setup and use

Cons

• Privacy concerns around data collection
• Requires Amazon devices or account integrations
• Quality of Skills varies significantly

2. Siri

Siri is Apple’s pioneering AI assistant built into iPhone, iPad, Mac, Apple Watch, HomePod and more. It features intuitive natural language processing for voice or text interactions. Siri is deeply integrated with Apple devices and apps to enable handsfree control. Users can get information like sports scores, weather, and stock prices simply by asking. Siri can also handle media playback, messaging, reminders, calendar management, and smart home device control. Processing sensitive requests on-device helps maintain privacy.

The assistant personalizes responses over time based on usage patterns. Siri is designed for convenience and accessibility exclusively for Apple device owners. The seamless integration across Apple’s ecosystem is a key strength.

Integration and Implementation

• Pre-installed on Apple devices.
• Accessible via voice, text, or gestures like holding home button.
• APIs available for app integration under Apple’s MFi Program.
• HomeKit enables smart home device integration.
• Auto manufacturers can integrate via CarPlay.

Pros

• Intuitive conversational interface
• Tight integration across Apple devices
• Processes sensitive data on-device
• Personalizes based on usage patterns

Cons

• Limited to Apple ecosystem
• Less capable than full AI assistants
• Not customizable or configurable

3. Google Assistant

Google Assistant is Google’s conversational AI helper available across smartphones, smart speakers, displays, TVs, headphones and more. It can understand natural language voice and text interactions. Google Assistant is optimized to tap into Google’s vast search knowledge graph to provide information like weather, translations, calculations, and definitions. It also offers personalized responses tailored to the user’s Google account and data.

The assistant maintains context during multi-turn conversations to continuously refine responses. It also provides native integration with Google Home and Nest devices for smart home control. As a versatile cross-platform assistant, it can be used for media playback, daily organization, and mobile device control.

Integration and Implementation

• Pre-installed on Android smartphones and tablets.
• Built into Google Home smart speakers and displays.
• Available on 100s of millions of devices with Google Play Services.
• Actions on Google development platform enables third-party integrations.
• Works with Nest devices after migration to Google accounts.
• Integrates with Chromecast devices.

Pros

• Broad availability across devices
• Powerful knowledge graph
• Personalized based on Google account

Cons

• Privacy concerns around Google data collection
• Responses inconsistent due to search reliance
• Less customization than some platforms

4. Cortana

Cortana is Microsoft’s AI-powered virtual assistant available across Windows, Android/iOS, and the Harman Kardon Invoke speaker. It features a conversational interface with the ability to understand natural language voice and text input. Cortana is focused on productivity scenarios. It integrates tightly with Microsoft products like Office 365, Outlook, and LinkedIn to assist with email, calendar management, documents, and business searches. Cortana can also handle basic smartphone commands, music playback, and home automation when paired with Invoke speakers.

Third-party skills are available to enhance Cortana’s capabilities further. It maintains context during conversations to continuously improve responses tailored to user preferences. This personalization and Microsoft ecosystem integration make Cortana a uniquely specialized assistant.

Integration and Implementation

• Pre-installed on Windows 10 devices and available via app on iOS/Android.
• Harman Kardon Invoke speaker discontinued in 2020 but works where available.
• Communicates with Windows 10 apps via unified Cortana core.
• Skills can be built via Cortana Skills Kit and Microsoft Bot Framework.

Pros

• Productivity focused for business
• Tight Microsoft integrations
• Third-party skills expand capabilities

Cons

• Limited availability beyond Windows ecosystem
• Less investment by Microsoft lately
• Not as capable for general use cases

5. IBM Watson Assistant

IBM Watson Assistant is an enterprise-grade conversational AI platform offering sophisticated natural language capabilities. It is cloud-based with processing on IBM servers. Watson Assistant offers robust natural language understanding using machine learning and neural networks. It caters to structured conversations for business use cases like customer service, employee help desks, and conversational commerce workflows.

Prebuilt domains for industries like banking, retail, and hospitality accelerate development. Custom conversational solutions can also be built tailored for unique needs. It also includes visual dialog tools, integration with business systems, and analytics dashboards.

Integration and Implementation

• IBM Cloud hosted – requires account and instance deployment.
• API integration or web chat embed for front-end deployment.
• IBM Watson Assistant for Voice Agents adds telephony.
• Prebuilt enterprise connectors and ecosystem of Watson services.
• Advanced customization requires Node.js or Python coding expertise.

Pros

• Robust NLP capabilities
• Enterprise-scale deployment
• Prebuilt domains available
• Security and compliance controls

Cons

• Steep learning curve
• Expensive without high volume
• Better for structured conversations

6. Nuance Mix

Nuance Mix is an omnichannel virtual assistant designed to automate customer and employee support conversations across voice, web, mobile, and SMS. It provides a visual tool to build and optimize dialog flows without coding.

Nuance Mix offers prebuilt conversational modules for common service scenarios like tech support, appointment scheduling, order status, voice biometrics, and more. It has tools to easily integrate with back-end systems along with conversation analytics.

As an established leader in speech recognition and AI, Nuance Mix enables companies to create unified customer and employee support experiences across channels. The straightforward drag-and-drop conversation designer is a key strength.

Integration and Implementation

• Cloud-based for scalability.
• Deploy via web or mobile SDKs for digital channels.
• Nuance Voice Channels for telephony integration.
• Customer authentication and SSO integration.
• Conversational components customized in Mix tool.

Pros

• Unified omnichannel conversational experiences
• Drag-and-drop conversation designer
• Leader in speech recognition space
• Prebuilt modules available

Cons

• Steep learning curve beyond basic features
• Requires Nuance for full capabilities
• Less flexible for complex conversations

7. Amelia

Amelia is an AI-powered IT service desk assistant created by IPsoft to understand and resolve employee tickets automatically. It utilizes natural language processing for text and voice interactions. Amelia is specialized for IT help desk and HR contexts with the ability to understand issues across IT domains and handle common questions. It offers self-learning capabilities to continuously improve through machine learning.

As an enterprise-focused solution, Amelia provides capabilities like analytics dashboards, omnichannel interfaces, and easy agent training tools. It aims to offload repetitive tasks rather than serve general purposes. The IT and HR specializations are unique strengths.

Integration and Implementation

• Available on-premise or IPsoft cloud.
• API based integration with backend systems.
• Messaging platform integrations – Slack, Skype, Facebook.
• Easy drag-and-drop dialog creation.
• Advanced training requires IPsoft professional services.

Pros

• Specialized for IT help desk
• Improves with machine learning
• Enterprise-focused solution
• Omnichannel conversational interfaces

Cons

• Narrow focus beyond IT help desk
• Expensive professional services often needed
• Steep learning curve for customization

8. Clara

Clara is an AI assistant created by Anthropic to be helpful, harmless, and honest using Constitutional AI, a technique to limit harmful responses. It is currently in limited beta testing with general availability expected in 2023.

Clara offers natural language processing for text conversations. The Constitutional AI approach restricts unethical, dangerous, or inappropriate responses. Clara is transparent about its capabilities and limitations to build user trust.

As it’s still in early development, capabilities remain restricted. It is intended for use cases like general information searches, task automation, customer service, and as a personal assistant. Ongoing beta testing will help refine capabilities further.

Integration and Implementation

• Currently invite-only beta via web chat interface.
• API access planned for integration into business applications.
• On-device processing for privacy – no data collection.
• Further platforms like mobile apps expected after beta period.

Pros

• Constitutional AI limits harm
• Transparent about capabilities
• Promising technical foundations

Cons

• Very limited capabilities currently
• Still in beta testing phase
• Long-term roadmap unclear

9. Ada Support

Ada Support provides an enterprise-focused conversational AI platform tailored for automating customer service workflows like FAQs, order tracking, reservation scheduling, and more. It offers a visual no-code bot builder enabling non-technical users to build assistants quickly. It also has enterprise-scale hosting, security, compliance features, platform integrations, and conversation analytics.

While Ada Support simplifies automating repetitive customer service conversations, it has more limited capabilities for handling complex free-form natural language interactions. But the easy visual design and prebuilt templates make it accessible.

Integration and Implementation

• Cloud-based with integrations via API.
• Web chat, mobile SDKs, messaging platform channels.
• Ada botstore offers prebuilt industry solutions.
• Custom components configured visually in Builder.

Pros

• No-code visual bot builder
• Enterprise-grade security
• Broad platform integrations
• Compliance controls

Cons

• Less capable for advanced conversations
• Steep learning curve past basic uses
• Limited prebuilt industry content

10. Interactions

Interactions provides enterprise-focused conversational AI solutions tailored for customer service, support, and sales scenarios. This includes both intelligent virtual assistants for common use cases as well as custom chatbot development.

It offers a conversational platform with robust natural language processing and dialog tools optimized for enterprises. Multimodal capabilities like voice, video, and visual bots are also available.

Interactions integrates with contact center, CRM, and other business systems. It focuses heavily on enterprise needs like security, scalability, governance, and analytics.

Integration and Implementation

• Cloud-based managed service – requires onboarding.
• Deploy through web/mobile SDKs, messaging, or voice channels.
• Over 50 out-of-the-box integrations with business systems.
• Dashboards for managing, monitoring, and optimizing.

Pros

• Strong focus on enterprise needs
• Multimodal voice, video, visual bots
• Prebuilt assistants and connectors
• Conversational platform optimized for business

Cons

• Steep learning curve for customization
• Expensive for smaller businesses
• Limited trial options

11. Active.ai

Active.ai provides conversational AI solutions tailored for the financial services sector. This includes banking, insurance, mortgage, lending, investments, and wealth management. It offers prebuilt banking bots and omnichannel deployment across messaging, voice, video, and IoT channels. Active.ai also has tools designed specifically to aid compliance with financial industry regulations.

As a vertically-focused provider, Active.ai delivers domain expertise in financial services conversational AI. But the specialized capabilities limit its usefulness beyond banking, insurance, and related financial use cases.

Integration and Implementation

• Cloud-based for scalability.
• Deploy via web, mobile SDKs, messaging, voice channels.
• Banking connectors and content packs.
• Compliance controls for financial industry.
• Ongoing professional services for training.

Pros

• Specialized for financial services
• Prebuilt banking bots
• Compliance controls
• Omnichannel delivery

Cons

• Narrow industry focus
• Steep learning curve past prebuilt features
• Requires professional services

12. Artificial Solutions

Artificial Solutions provides conversational AI solutions tailored for enterprise use cases like customer service, help desk, HR, sales, and marketing. It offers omnichannel deployment across apps, web, messaging and voice interfaces.

It features natural language processing powered by neural networks for text and voice. Prebuilt industry templates for verticals like banking, automotive, and telecom enable quick starts. Teneo Studio provides a graphical dialog editor to build conversational flows without coding.

Artificial Solutions focuses heavily on enterprise needs like security, scalability, and analytics. However, customization capabilities are more limited compared to some alternatives.

Integration and Implementation

• Cloud-hosted for scalability and security.
• Custom components built visually in Teneo Studio.
• Connectors for integration with back-end systems.
• Deploy via API, SDKs, or embeddable web chat.
• Catalog of industry content and solutions.

Pros

• Long history developing conversational AI
• Prebuilt industry templates
• Graphical conversation designer
• Omnichannel flexibility

Cons

• Less customization than alternatives
• Steep learning curve past templates
• Very limited free trials

13. Cognigy

Cognigy provides an enterprise-focused conversational AI development platform for building voice and text-based virtual agents. It offers a visual drag-and-drop interface to design conversational flows without coding expertise.

The platform supports both cloud-based and on-premise deployment. It also enables omnichannel delivery over voice, text, web, and mobile apps. A marketplace provides connectors to accelerate third-party integrations.

While the visual design simplifies basic bot development, Cognigy has a steep learning curve for advanced customization. It also lacks prebuilt content for common use cases out of the box. But the flexibility is a key strength.

Integration and Implementation

• Cognigy.AI cloud or on-premise installation.
• Conversational flows configured visually via drag-and-drop.
• Deploy on website, mobile app, messaging, or voice channels.
• Marketplace connectors and REST API integration.

Pros

• Visual drag-and-drop bot designer
• Choice of cloud or on-premise
• Omnichannel delivery
• Integration marketplace

Cons

• Limited prebuilt content
• Steep learning curve past basics
• Smaller vendor than leaders

14. Replica

Replica provides tools to easily develop and deploy customized intelligent assistants for common business use cases like HR, IT help desks, customer support, and scheduling. It enables visually building, training and managing bots without coding expertise.

Key features include conversation AI, prebuilt templates, workflow automation, third-party integrations, and agent analytics. Replica aims to empower non-technical team members to build assistants tailored to their needs.

However, Replica offers limited customization capabilities compared to developer-centric platforms. It also has a smaller customer base than leading vendors. But the no-code approach provides accessibility.

Integration and Implementation

• Cloud-based delivery model.
• Deploy on web, mobile, messaging platforms
• Prebuilt templates and integrations accelerate development.
• Visual tooling enables non-technical users to build assistants.

Pros

• Visually build bots without coding
• Prebuilt templates and workflows
• Easy for non-technical users
• Usage analytics and monitoring

Cons

• Limited customization capabilities
• Less proven at large scale
• Key details gated behind sales

15. Otter.ai

Otter.ai provides an AI-powered intelligent assistant specifically designed for sales teams. It integrates with CRM, email, calendar, and communication tools to automate repetitive sales tasks and workflows.

Key features include conversational AI optimized for sales contexts, CRM data entry and updates, email automation, scheduling assistance, and alerts and notifications. It aims to save sales reps time on administrative work to focus on selling.

The highly specialized sales focus provides unique value but limits Otto.ai’s usefulness for other areas. It also offers very little flexibility to customize beyond the base sales productivity features.

Integration and Implementation

• Cloud-based delivery enables rapid rollout.
• Integrates with CRM, email, calendar, and communication tools.
• Available as web application with mobile access.
• Limited customization beyond base capabilities.

Pros

• Designed specifically for sales reps
• Prebuilt integrations with sales tools
• Email and calendar automation
• Cloud-based for quick deployment

Cons

• Extremely limited use cases beyond sales
• Little room for customization
• Premium pricing may limit adoption

16. Observe.AI

Observe.AI provides AI-powered analytics and assistant technology focused on improving customer service interactions within call centers. This includes features like call transcription, conversation analytics, agent guidance, and automated virtual agents.

It integrates natively with leading call center platforms to extract insights from customer calls using speech recognition and natural language processing. Observe.AI also offers tools to build automated conversational workflows for customer support.

But the sole focus on optimizing call center conversations limits its applicability beyond that use case. While powerful for call centers, customization options are limited.

Integration and Implementation

• Cloud-based delivery enables rapid deployment.
• Integrates with leading call center and CRM systems.
• Conversational assistant built visually with conversation builder.
• Limited trial options – contact sales.

Pros

• Specialized for call center needs
• Conversation intelligence analytics
• Guidance and automation for agents
• Call center platform integrations

Cons

• Very limited use cases beyond call centers
• Transcription accuracy rates unclear
• Less flexibility customizing conversations

17. Kasisto

Kasisto provides conversational AI solutions tailored for the financial services industry, including banking, insurance, wealth management, and mortgage interactions. This includes the KAI Banking virtual assistant leveraging natural language processing optimized for finance. 

Prebuilt solutions accelerate deployment for common financial service scenarios. Kasisto also offers omnichannel delivery, compliance features, and analytics. It partners directly with major banks and financial service providers. Like others in the space, Kasisto’s focused vertical approach limits its usefulness beyond financial services. But its banking expertise makes it a leader in that domain.

Integration and Implementation

• Cloud-based for efficient rollout to banks.
• KAI Banking and other assistants pre-built for banking.
• Compliance controls tailored for banking industry needs.
• Omnichannel deployment flexibility.

Pros

• Focused specifically on financial services
• Prebuilt banking content
• Designed for industry compliance needs
• Trusted by major banks

Cons

• Applicability limited beyond finance
• Professional services required for customization
• Less transparency into product roadmap

18. SoundHound

SoundHound provides technology to power the voice interface and interactions for custom AI assistants. This includes speech recognition, natural language processing, conversational commerce tools, and global language support.

It enables brands to build tailored voice assistants for products, devices, applications, and vehicles. SoundHound focuses more on the speech recognition capabilities versus a full end-to-end conversational solution.

The platform flexibility allows companies to create customized voice assistants aligned to their brand. But significant development work is required to build on top of the speech recognition foundations.

Integration and Implementation

• Cloud-based APIs enable integration into third-party products.
• Edge computing options also available.
• Custom conversational interfaces configured through platform.
• Limited trial – contact sales to get started.

Pros

• Strong legacy in speech recognition
• Flexibility for custom assistants
• Broad global language support
• Conversational commerce enablement

Cons

• Not an end-to-end assistant platform
• Significant development expertise needed
• Most details gated behind sales

19. Lola.com

Lola.com offers an AI-powered travel service assistant designed specifically for business travel. It provides natural language conversational interfaces for activities like travel research, booking, modifying, and managing trips.

The assistant is customized with deep travel industry expertise and integration with core booking capabilities. It proactively recommends personalized money-saving options aligned to company travel policies. However, Lola.com has extremely limited applicability outside corporate travel booking and management. It is purpose-built for that singular use case.

Integration and Implementation

• Cloud-based with web and mobile apps.
• Integrates with corporate travel systems and policies.
• Limited trial – contact sales to get started.
• Limited flexibility beyond travel focus.

Pros

• Specialized for business travel needs
• Integrated booking capabilities
• Ensures compliance to company policies
• Proactively recommends savings

Cons

• Extremely narrow focus beyond travel
• Direct booking limited to business users
• No public API or integration options

20. Aivo

Aivo provides an enterprise-focused conversational AI platform tailored for customer service process automation use cases like FAQs, account lookups, appointment booking, lead qualification, and more.

It combines natural language processing with tools like pre-built bots, a visual dialog editor, third-party integrations, conversation analytics, and omnichannel delivery support. These capabilities help streamline repetitive customer service interactions. However, Aivo has limited applicability beyond automating structured customer service conversations. It does not offer more advanced natural language capabilities.

Integration and Implementation

• Cloud-based delivery enables quick rollout.
• Pre-built bots and templates accelerate development.
• Conversational flows configured visually.
• Deploy across messaging, voice, web, etc.

Pros

• Streamline automating repetitive customer service processes
• Prebuilt bots and templates
• Visual dialog editor for straightforward customization
• Omnichannel delivery

Cons

• Less capable for unstructured conversations
• Key details gated behind sales contacts
• Smaller vendor than leaders in market

AI Assistant Comparison

Assistant	Creator	Key Users	Primary Use Cases
Alexa	Amazon	Consumers	Smart home, entertainment, daily information
Siri	Apple	Apple device owners	Mobile device control, smart home, media
Google Assistant	Google	Android & smart device users	Daily information, smart home, media controls
Cortana	Microsoft	Windows users	Productivity, office work, business search
IBM Watson Assistant	IBM	Enterprises	Customer service, IT help desks, workflows
Nuance Mix	Nuance	Enterprises	Customer service automation, voice biometrics
Amelia	IPsoft	Enterprises	IT help desk, HR
Clara	Anthropic	TBD	Personal assistant, customer service
Ada Support	Ada	Enterprises	Customer service automation
Interactions	Interactions	Enterprises	Customer service, virtual agents
Active.ai	Active.ai	Financial services	Banking, lending, insurance
Artificial Solutions	Artificial Solutions	Enterprises	Customer service, sales bots
Cognigy	Cognigy	Enterprises	Customer service, voice agents
Replica	Replica	Enterprises	HR, IT help desks, scheduling
Otto.ai	Otto.ai	Sales teams	Sales productivity automation
Observe.AI	Observe.AI	Call centers	Call center optimization, analysis
Kasisto	Kasisto	Financial services	Banking, wealth management
SoundHound	SoundHound	Device makers	Custom voice assistant development
Lola.com	Lola.com	Business travelers	Corporate travel booking & management
Aivo	Aivo	Enterprises	Customer service process automation

FAQs

AI assistant tools, also known as virtual assistants, are software applications powered by artificial intelligence that can perform tasks, answer questions, and automate processes. They utilize natural language processing and machine learning to provide intelligent and human-like interactions.

AI assistant tools are crucial in 2023 because they streamline tasks, enhance productivity, and improve user experiences. They offer personalized assistance, make data-driven decisions, and help organizations stay competitive in a fast-paced digital world.

AI assistant tools can perform a wide range of tasks, including answering questions, scheduling appointments, sending reminders, providing recommendations, automating customer support, managing data, and much more. Their capabilities continue to expand with advancements in AI technology.

AI assistant tools benefit various industries, including healthcare, finance, e-commerce, education, customer service, and marketing. Their adaptability and versatility make them valuable in nearly any sector where automation and intelligent assistance are required.

While the specific rankings may change over time, some of the top AI assistant tools in 2023 include Google Assistant, Amazon Alexa, Apple’s Siri, Microsoft’s Cortana, IBM Watson Assistant, and more. The choice of tool often depends on the specific needs and preferences of users and organizations.

To choose the right AI assistant tool for your business, consider your objectives, industry, scalability, integration capabilities, and the tool’s ease of use. Evaluate factors like customization options, available features, and the compatibility of the tool with your existing software and systems.

AI assistant tools can raise concerns about data privacy and security. It’s essential to choose tools that prioritize data encryption, user consent, and compliance with data protection regulations. Implementing robust security measures within your organization is also crucial.

Yes, AI assistant tools are suitable for personal use. They can assist individuals with daily tasks, such as setting reminders, answering questions, and providing recommendations. Personal AI assistants are often integrated into smartphones, smart speakers, and other devices.

Many AI assistant tools offer customization options to tailor their functionality to specific tasks and industries. Some tools provide development platforms or APIs that allow organizations to build custom applications and workflows.

The future of AI assistant tools is expected to involve advancements in natural language processing, increased personalization, improved integration with Internet of Things (IoT) devices, and enhanced capabilities in various industries. As AI technology continues to progress, AI assistant tools will likely become more intelligent and versatile.

Conclusion

• Leading consumer AI assistants like Alexa, Siri and Google Assistant offer broad utility through easy voice access to information, media, and smart devices.
• Assistants like IBM Watson, Ada Support, and Nuance cater to enterprises by automating high volume customer service and IT support conversations.
• Vertical-specific assistants like Kasisto and Active.ai deliver prebuilt capabilities for industries like banking and insurance.
• Development platforms from Microsoft, Cognigy, and Replica enable custom assistants tailored to unique needs.
• As competition increases, differentiating through accuracy, intuitiveness, and integrated value will be key success factors.
• Privacy, transparency, and responsible AI will need to be top priorities as adoption grows.

Conversational AI assistants are transforming how consumers, employees, and businesses interact with technology and information. Leading platforms are driving efficiencies and making experiences more natural and personalized. This guide provides a comprehensive overview of the top 20 AI assistant tools today and key selection criteria based on use cases and capabilities. Comparing solutions across these dimensions enables finding the ideal assistant or development platform tailored to your specific needs.