Artificial Intelligence Software Resources
Articles, Glossary Terms, and Discussions to expand your knowledge on Artificial Intelligence Software
Resource pages are designed to give you a cross-section of information we have on specific categories. You'll find articles from our experts, feature definitions, and discussions from users like you.
Artificial Intelligence Software Articles
20 Revolutionary AI Applications in 2025: Real-World Examples
What Is Image Annotation? Types, Use Cases and More
What Is Machine Learning? Benefits And Unique Applications
10 Best Data Labeling Software With G2 User Reviews
AI In Music: Benefits, Challenges, and Tools for Musicians
Brief History of Artificial Intelligence - From 1900 till Now
What Is Artificial Intelligence (AI)? Types, Definition And Examples
What Is TinyML? A Brief Introduction And Benefits
History Of Computers: Timeline, I/O Devices and Networking
The Rise of AI-Generated Art: From Algorithms to Aesthetics
AI Image Generation: The Science Behind How It Works
What Is Artificial General Intelligence (AGI)? The Future Is Here
Mastering ChatGPT: Behrang Asadi on the Growing Effect of Generative AI
Top Digital Transformation Trends in 2021
Innovation in Artificial Intelligence [INFOGRAPHIC]
When Platforms Collide, Analytics Evolves
Tech Companies Bridging the Gap Between AI and Automation
The Industry Impact of AI Regulations in the EU
The Things Have Eyes: An Introduction to IoT
The Data Toolbox: The Expanding Domain of AI & Analytics
CX Tech: Artificial and Intelligent
G2 on Enterprise AI & Analytics: What is It Really & Why Does It Matter?
AI in Retail: How It’s Being Used (+ 4 Brand Examples)
Embedded AI: Embedded Systems Trends for 2019
Artificial Intelligence Software Glossary Terms
Artificial Intelligence Software Discussions
We’ve been in the market the best voice-activated AI tools for customer service. After looking at the AI Voice Assistants category on G2, a couple factors that made our decision tricky is choosing a strategy around containment vs. escalation, knowledge reliability, agent coaching, and whether automation should sit inside an existing service stack or become the front door for service itself. Here are the top tools we are considering:
- Genesys Cloud CX stands out when the priority is handling customer conversations across voice and digital channels with bot support, analytics, and clean routing to human agents for complex issues.
- Kore.AI is a strong contender when enterprise security, model flexibility, and prebuilt customer-service use cases matter as much as conversational quality.
- Dialpad Support fits teams that want AI agents, real-time guidance, and coaching inside the inbound contact center rather than a separate automation layer.
- Retell AI is interesting for teams building custom phone agents for FAQs, qualification, scheduling, or repetitive support interactions where speed to production matters.
- Smith.ai AI Receptionist makes sense when callers still expect a professional human fallback and the business wants AI to reduce missed opportunities without over-automating.
- Voiceflow is useful when product or support teams want to design and test more tailored service journeys rather than accept a one-size-fits-most bot.
For teams that have deployed these tools, where do the biggest trade-offs show up: containment rate, CSAT, knowledge freshness, agent trust, or the quality of human handoff when the AI reaches its limit?
Dialpad feels especially interesting if the real value is not full automation, but making human agents better in real time. That seems like a very different bet from tools that are trying to maximize containment up front.
We’ve been digging into the best AI voice platforms for field service teams. The difficult part is that field service teams usually care less about flashy voice demos and more about whether the platform can handle missed calls, after-hours booking, reschedules, dispatch questions, and urgent escalation without creating more admin work. That is where a lot of tools start to separate.
Looking at the AI Voice Assistants category on G2, here are the AI voice platforms that seem best suited for field service teams:
- Synthflow looks strong for service businesses that want automated appointment scheduling, call routing, lead qualification, and 24/7 answering without needing a large technical team.
- Smith.ai AI Receptionist is a good fit when every missed call matters and the team wants AI handling intake while human receptionists cover urgent or messy conversations.
- Retell AI is compelling for teams that want to build custom voice flows for reschedules, reminders, FAQs, and follow-up messaging tied to field operations.
- Voiceflow is worth considering when service teams need more control over triage logic, testing, and analytics before automating dispatch-heavy or branded call experiences.
- Jotform AI Agents can work well when intake depends on FAQs, service policies, forms, or document-based knowledge that needs to be reflected in the conversation.
- Genesys Cloud CX makes more sense for larger service organizations that need omnichannel support, stronger routing, and a clearer path from automation to live-agent handoff.
For teams already using voice AI in field service, what has been hardest to automate well: emergency escalation, scheduling around changing technician availability, or syncing conversation outcomes back into the system of record?
If you’re trying to figure out the best AI writing tool for company blogs, there are a few platforms that consistently come up in this space. From generating full-length articles to maintaining a consistent brand voice across posts, these tools are helping teams scale blog production without slowing down on quality.
Here are some top-reviewed AI writing tools commonly used for blog content:
- Grammarly (G2 rating: 4.7⭐, 13,000+ reviews): Grammarly is widely used as a final editing layer for blog content, helping teams refine tone, clarity, and readability before publishing.
- Notion AI (G2 rating: 4.6⭐, 10,000+ reviews): Notion AI works well for drafting blogs within collaborative workflows, especially when multiple contributors are involved in content planning and writing.
- Jasper (G2 rating: 4.7⭐, 1200+ reviews): Jasper is commonly used for generating structured long-form blog drafts, making it easier to scale content production across topics and campaigns.
- Wordtune (G2 rating: 4.6⭐, 120+ reviews): Wordtune is useful for rewriting and improving clarity within blog sections, especially when refining tone or simplifying complex ideas.
- Writer (G2 rating: 4.3⭐,100+ reviews): Writer helps maintain consistent brand voice across blog content, which is particularly valuable for teams with multiple writers or strict editorial guidelines.
These tools are being used by content teams to handle both the speed and volume that blog production demands today. Depending on your workflow, some are better for drafting, while others help more with consistency and refinement.
Have you used any of these tools for company blogs? Which one actually helped you scale content without increasing editing time?
Also, do you rely on a single tool for blog writing or does your workflow usually involve switching tools between outlining, drafting, and refining?















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