The Gist
AI leaders raise the bar. Anthropic, Intercom, Ada and Forethought are pushing AI beyond scripted chatbots into agentic, multimodal customer experiences. Smarter support, faster service. From predictive copilots to GPT-4 chatbots, AI is resolving inquiries, boosting productivity and delivering personalized interactions at scale. Success depends on integration. Real-world AI performance requires backend access, data orchestration and human oversight—not just plug-and-play tools.
AI-powered customer interactions are rapidly evolving, with businesses using advanced models to enhance support, personalize experiences and improve operations.
Industry leaders such as Anthropic, Intercom, Ada, and Forethought are leading this transformation, using AI to automate responses, assist human agents, and deliver more intuitive customer engagement.
This article explores how these companies are pushing the boundaries of customer AI technology, shaping the future of frictionless, intelligent interactions.
Table of Contents
Introduction to AI in Customer Experience
AI is fundamentally changing how businesses look at customer interactions. Instead of relying solely on human agents, companies are taking advantage of AI to automate support, analyze customer sentiment, and provide real-time assistance across multiple channels. From chatbots handling routine inquiries to AI-driven systems predicting customer needs, artificial intelligence is enhancing efficiency while improving the customer experience.
Investing in the future of CX are Anthropic, Intercom, Ada and Forethought. And they are pushing the boundaries of what AI can do in customer service. Anthropic develops advanced AI assistants that emphasize safety, reasoning and reliability. Intercom integrates AI into customer support platforms, helping businesses automate responses and improve agent productivity. Ada specializes in AI-powered chatbots that provide personalized, scalable support. And Forethought applies AI to optimize workflows, using automation to optimize customer interactions.
Together, these brands are shaping the next generation of AI-driven customer engagement.
The Rise of AI in Customer Engagement
AI-driven customer support is no longer a luxury for enterprise businesses—it’s a necessity. As customer expectations for instant, personalized service continue to rise, businesses are turning to AI to deliver pain-free, scalable interactions.
Why Traditional Support Models Fall Short
Traditional support models, reliant on human agents, struggle to keep up with demand, especially during peak times. AI-powered solutions offer a way to bridge this gap, providing 24/7 availability, faster response times, and more consistent service quality.
Four Key AI Trends Driving Better Engagement
These trends show how AI is elevating the customer experience through smarter, more personalized automation.
TrendDescription Automation Enhances routine inquiries by enabling AI chatbots and virtual assistants to handle common questions, freeing human agents to focus on complex issues. Personalization Uses AI to analyze behavior, preferences and sentiment, delivering tailored responses in real time to improve engagement. AI copilots Support human agents with suggested responses, real-time data retrieval and historical context, boosting agent productivity and consistency. Generative AI Creates dynamic, context-aware responses that feel more natural and human-like than traditional scripted bots.
From Automation to Collaborative Intelligence
While many brands are rushing to adopt AI chatbots, the most effective use of AI isn’t just in automation—it’s in orchestrating consistent, end-to-end experiences that involve both self-service and assisted support.
Rahul Garg, VP of product, AI and self-service at Genesys, an AI-powered CX cloud services provider, told CMSWire that generative AI powered copilots surface real-time knowledge or next best actions so that agents can quickly help answer questions and resolve issues.
“Over the next few years, organizations will increasingly shift from their legacy chatbots to more sophisticated virtual agents that can understand and complete more complex conversations on their own,” he said. Garg emphasized that AI’s role is evolving—from basic automation to collaborative intelligence that supports both customers and contact center agents. As businesses modernize their support strategy, these copilots will optimize service and enhance personalization.
From Chatbots to Multimodal, Human-Like Interactions
AI-powered customer engagement is moving rapidly from scripted chatbots to natural-sounding, multimodal conversations. Voice- and video-capable AI is already starting to reshape expectations around what human-like support can feel like, and emerging tools are introducing powerful assistive features for both consumers and agents.
Connor Heaton, director of AI at tech consultancy Strategic Resource Management (SRM), told CMSWire that generative AI chatbots across text, voice, and (soon) video channels will likely become the norm.
“Beyond basic interactions, AI chatbots will increasingly provide deep, personalized sales assistance, guiding purchasing decisions through tailored recommendations on virtually every page or customer touchpoint,” said Heaton, who added that trends such as live accent removal, real-time translation, and digital avatars are technologies that are being explored to improve the quality of outsourced support, and predicted a future in which AI assistants are able to deliver personalized sales guidance across digital touchpoints, with sentiment-aware copilots providing live suggestions and collaborative routing assistance for human agents.
Together, these advancements are reshaping customer engagement, making interactions more efficient, intuitive, and personalized. As AI continues to evolve, businesses that adopt these technologies will effectively gain a competitive edge by delivering superior customer experiences while optimizing operational costs.
Related Article: AI in Customer Experience Works Best With a Human Heart
How Anthropic Is Elevating AI for Customer Interactions
Anthropic’s Claude is quickly becoming a standout in the realm of AI-driven customer engagement, offering a more conversational, context-aware experience than many of its peers. Built on Constitutional AI principles, Claude is designed to be helpful, honest, and harmless—prioritizing safety and transparency while delivering nuanced, natural dialogue. Its ability to retain context over longer conversations and interpret subtleties in language makes it especially well-suited for complex customer service scenarios that go beyond simple FAQ-style exchanges.
Businesses are integrating Claude into a range of customer-facing applications. As an AI chatbot, Claude delivers high-quality support in real time, handling everything from product recommendations to troubleshooting, all while maintaining a friendly and human-like tone. In customer service assistant roles, Claude can work alongside human agents, summarizing customer histories, suggesting responses, or escalating issues when needed—reducing average handling times and improving resolution rates.
At the enterprise level, Claude powers support tools that can interpret large knowledge bases, analyze documents, and respond to technical queries with impressive accuracy, making it extremely useful as a backend assistant for IT support, B2B sales, and more.
Claude Capabilities Supporting Customer Engagement
This table outlines key features of Claude that enhance support, automation and enterprise use cases.
Feature or CapabilityDescriptionLong-Context UnderstandingRetains information across multi-turn conversations for coherent responsesConstitutional AI DesignBuilt for helpfulness, honesty and safetyCode GenerationConverts natural language into functional code for dev and IT supportDocument ComprehensionAnalyzes complex documents (e.g., clinical reports, legal docs)Enterprise Use CasesSupports customer service, IT, sales and compliance teamsReal-World ApplicationsPowers Alexa+, assists tax professionals, accelerates clinical writingImpact on Support TeamsReduces handling times, improves resolution rates, boosts satisfaction
Claude’s Growth Signals the Future of Enterprise AI
With Claude, customers benefit from faster, more intelligent responses that feel less robotic and more human. Businesses, in turn, reduce support costs, improve first-contact resolution, and build stronger relationships with users through more personalized, trustworthy interactions. As Claude continues to improve, it’s a great example of what AI-powered support can look like—smart, scalable and genuinely helpful.
Anthropic’s momentum continues to accelerate following its $3.5 billion Series E funding round, which brought the company’s valuation to $61.5 billion. In a recent announcement, Anthropic emphasized its commitment to building “next-generation AI systems” with advanced capabilities in reasoning, code generation, and real-world collaboration. Though best known for foundational research, Anthropic’s Claude is increasingly being embedded into real-world CX systems, from enterprise backend tools to consumer applications such as the new Alexa+.
“We’re focused on developing systems that can serve as true collaborators,” the company said in the announcement, “working alongside teams to tackle complex projects, synthesize information across fields, and help organizations achieve outsized impact.” As Claude continues to evolve, Anthropic underscored that its mission remains centered on “deepening our understanding of frontier AI systems and ensuring that artificial intelligence advances human progress.”
Related Article: AI Personality as CX Strategy: Inside Claude’s Disposition
How Intercom Uses AI to Enhance Customer Support
Intercom has positioned itself at the forefront of AI-driven customer support, combining intelligent automation with human-assisted service to create a frictionless, efficient experience. Its AI-powered chatbots and automation tools help businesses scale support operations by instantly handling routine inquiries, qualifying leads, and directing customers to the right resources—all without requiring human intervention.
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A key strength of Intercom’s platform is its “copilot” approach—AI that doesn’t just assist customers, but also actively supports human agents during live interactions.
This AI-human synergy is delivering measurable results. Intercom is continuing to evolve its platform, with plans to integrate even deeper analytics and real-time performance data.
Key Intercom AI Capabilities for Customer Support
This table highlights the AI features that help Intercom enhance customer service performance and agent efficiency.
Feature or CapabilityDescriptionAI-Powered CopilotSuggests responses and retrieves information for human agents in real timeAutomated AgentResolves 40–50% of customer inquiries without human interventionAI-Assisted HandoffSmoothly transitions complex cases from AI to human agentsConversational AIEnhances customer engagement with natural, context-aware interactionsReal-Time AnalyticsAnalyzes customer interactions and agent performance for optimizationBusiness ImpactBoosts efficiency, improves response times and reduces agent workload
How Ada Automates and Personalizes Customer Support
Ada’s latest evolution of its AI agent highlights how generative AI is reshaping automated support—not by mimicking human agents, but by operating as a true digital counterpart. The company rebuilt its platform from the ground up using GPT-4, combining it with historical data and a multi-agent architecture that dramatically improves how customer inquiries are interpreted, resolved, and personalized.
“We got really excited by OpenAI and what was happening in the industry,” said Mike Gozzo, chief product and technology officer at Ada, in an OpenAI press release. “In 2022, we decided to go all in and rebuild the product using the reasoning capabilities of LLMs.” The results have been striking.
Ada Capabilities Supporting Enterprise and Support Teams
This table outlines key features of Ada’s AI agent that strengthen automation, development and customer service across enterprise environments.
Feature or CapabilityDescriptionLong-Context UnderstandingRetains information across multi-turn conversations for coherent responsesConstitutional AI DesignBuilt for helpfulness, honesty and safetyCode GenerationConverts natural language into functional code for dev and IT supportDocument ComprehensionAnalyzes complex documents (e.g., clinical reports, legal docs)Enterprise Use CasesSupports customer service, IT, sales and compliance teamsReal-World ApplicationsPowers Alexa+, assists tax professionals, accelerates clinical writingImpact on Support TeamsReduces handling times, improves resolution rates, boosts satisfaction
“From one technology to the next, we’ve doubled the amount of conversations we can automatically resolve with a great experience,” Gozzo said. “For our customers, that translates into massive downstream ROI—FTE savings, higher CSAT, better retention, and more signups.”
Ada has also built an evaluation framework that is capable of rating conversations on accuracy, relevance, and safety—key factors for autonomous resolution. In internal testing, the system agreed with human reviewers 80–90% of the time. “Many solutions, including Ada, could easily deliver 80–100% containment rates,” Gozzo explained, “but if you actually opened up those conversation transcripts and read the experiences customers had, they were quite poor.”
To address that, Ada has focused on improving not just quantity, but quality. The platform’s Spring 2024 update added deeper reasoning capabilities, multilingual support, and improved skills development—allowing businesses to onboard, train, and coach the AI agent similarly to a human teammate.
“Ada’s AI Agent is the future of customer service,” Gozzo said in a 2024 announcement. “We’ve made onboarding, measuring, and coaching the AI agent as familiar and intuitive as managing a human.”
How Forethought Uses AI to Improve Ticket Resolution
Forethought is improving customer support by bringing AI-powered automation and predictive intelligence as a core element of ticket resolution. Its platform uses advanced natural language processing (NLP) and machine learning (ML) to optimize the entire support workflow—from ticket triage to final resolution—enabling faster, more accurate customer service with minimal human intervention.
At the heart of Forethought’s offering is Solve, an AI agent that provides instant answers to common inquiries by generating relevant help center content or automating responses based on historical ticket data. For more complex issues, Triage and Assist work together to prioritize, route, and recommend next steps for human agents by analyzing customer history and ticket context in real time. This intelligent orchestration reduces delays and ensures that high-priority or sentiment-sensitive tickets are addressed quickly and accurately.
Forethought Capabilities Driving Scalable Support
This table outlines how Forethought’s AI platform enhances ticket resolution, boosts CX outcomes and increases operational efficiency.
Feature or CapabilityDescriptionSolve AI AgentProvides instant answers by surfacing relevant help center contentTriage & AssistPrioritizes and routes tickets based on context and urgencyPredictive AIForecasts customer intent and resolution paths to prevent escalationsAgentic AIMoves beyond simple automation to autonomous task executionCustomer Experience ImpactReduces response times, improves resolution accuracy and enhances CXBusiness Efficiency GainsLowers support costs, increases agent productivity and scales operations
Forethought’s Predictive AI adds to this capability by forecasting customer intent and resolution paths, enabling businesses to preempt issues and optimize resource allocation before problems escalate. Looking ahead, Forethought is leaning into a future powered by agentic AI—a new phase of automation where AI agents can plan and execute tasks independently, rather than waiting for specific prompts.
Founder Deon Nicholas told CMSWire that to meet rising customer expectations, businesses must go beyond retrieval-based approaches.
“Adopting agentic AI allows CX AI to plan, reason and execute tasks,” Nicholas said. “These solutions foster brand loyalty and accelerate companies’ growth and profitability.”
By embracing this shift, Forethought is positioning its platform not just as a tool for efficiency, but as a strategic driver of long-term customer loyalty and service transformation. Through agentic capabilities and predictive insight, it was designed to enable businesses to deliver more consistent, context-aware support at scale.
While many vendors still rely on information-retrieval approaches to support automation, Nicholas explained that Forethought is building solutions that go beyond answering questions—they act.
Nicholas said that businesses looking to scale personalized, high-quality service must evolve past static, FAQ-style bots. Instead, agentic AI enables dynamic problem-solving, adapting to complex customer needs in real time without requiring tightly scripted workflows.
The Challenges of Implementing AI-Driven Support
One of the most overlooked realities in AI implementation is the level of effort needed to tailor solutions for meaningful outcomes. Businesses that rely solely on off-the-shelf AI without integration or oversight may struggle to meet the performance that vendors promise.
Heaton said that for an AI agent to be more than an FAQ bot, it has to be hooked into a brand’s systems. “That means API and integration work by giving the AI agent ‘limbs’ to be able to take actions.” Heaton emphasized that relying exclusively on generative AI vendors often leads to mediocre results. True impact comes when businesses invest time and resources into tightly integrating AI with internal systems, building secure workflows and establishing guardrails to minimize or eliminate data leakage and reputational risks.
Integration and Data Fragmentation Remain Top Challenges
Another major hurdle in adopting effective AI tools lies not in the technology itself, but in how customer data is organized and accessed across touchpoints. As such, Garg emphasized that one of the biggest organizational challenges is fragmented, siloed data. “A rushed or botched roll-out of new AI capabilities that leaves consumers frustrated…could be costly.” According to Garg, the real power of AI lies in its ability to orchestrate experiences across the entire journey—but only if brands take the time to unify data and avoid rollout missteps that frustrate customers.
In addition, data privacy remains one of the most pressing risks in customer AI. Even enterprise AI tools may fine-tune on user data, requiring safeguards to prevent potential violations.
Yelena Ambartsumian, founding attorney at AI and privacy law firm AMBART LAW PLLC, told CMSWire that using customer support tickets and conversations for training can be done, but it requires stripping out personally identifiable information. “Otherwise, it may constitute a ‘sale’ of personally identifiable information, which must be disclosed,” Ambartsumian said.
Why Human Oversight Still Matters in the Age of AI
Even with mature AI systems, human oversight remains essential—especially for edge cases, training, and accountability.
“With more advanced AI and sufficient documentation, many contact centers may get to a point where there are few escalations and one human oversees many AI agents,” said Heaton, who envisions a future in which humans act more as supervisors than front-line responders, conducting random quality checks and refining models. Still, rare or emotionally charged interactions will always require a human touch.
Similarly, Forethought’s founder, Nicholas, emphasized that while AI may eventually handle more frontline tasks, the most effective solutions will still require human oversight—for empathy, edge cases, and continuous improvement. “AI should empower people, not necessarily replace them. Ironically, AI may prove to be more empathetic and patient than humans, especially in addressing complex and ambiguous customer support issues.”
