The advent of natural language processing (NLP), machine learning (ML), and AI has transformed chatbots, remaking how we interact with software, work, search, and information processing.

What is an AI chatbot?

AI chatbots are software that simulate human-like conversations, engaging users through text and speech. Using advanced natural language processing and machine learning algorithms, they can understand and process complex user queries with increasing accuracy.

Chatbots can handle tasks like customer service, booking reservations, providing recommendations, and assisting with sales. They’re used across websites, messaging apps, and social media, and include standalone chatbots like OpenAI’s ChatGPT, Google’s Gemini, Microsoft’s Copilot, and more.

How do chatbots work?

While basic chatbots rely on scripts and decision trees, modern AI-powered chatbots use sophisticated NLP and ML to understand context and nuances of human language. This evolution has improved their performance, addressing previous limitations that led to poor customer experiences.

AI chatbots analyze user inputs to determine intent, generate relevant and personalized responses, and learn from interactions. This involves linguistic rules, pattern recognition, and sentiment analysis, enabling natural and complex conversations.

AI chatbots by the numbers

As chatbots’ applications in marketing and commerce evolve, their impact on industry is wide and varied. Here are a few stats to consider:

  • By the end of 2026, 35.1% of US adult consumers will use AI-enabled banking chatbots, according to EMARKETER forecasts.
  • 38% of marketers worldwide cite chatbots as the most impactful AI use case for enhancing the digital experience, according to a September 2024 survey by Advanis and Sitecore.
  • ChatGPT reached 300 million weekly active users near the end of 2024.
  • In the US, 27% of B2B marketers are using chatbots as part of their marketing strategies, according to Sagefrog Marketing Group.

What is ChatGPT?

ChatGPT is the chatbot that started the AI race with its public release on November 30, 2022. Created by OpenAI, GPT stands for “generative pre-trained transformer.” It’s designed to answer user questions, including simple queries for facts or complex instructions for generating content and communications.

ChatGPT uses generative AI to produce content like text, images, music, and code. While trained on existing data, it generates real-time responses to user queries.

OpenAI launched GPT-o3, its latest reasoning model, in April 2025. The new model enhances its Deep Research mode, which lets users generate reports by browsing the web for source material. That followed its January release of Operator, its AI agent.

In March 2025, ChatGPT significantly updated its image generation ability, allowing users to create more realistic images and to create graphics with text. Previously, the tech struggled to generate graphics with text without distorting the words.

AI chatbots: The competition

ChatGPT may have started the AI race, but its competitors are in it to win, which isn’t surprising since many are top tech companies. Here are a few competing chatbots.

Google Gemini (formerly Google Bard)

Google has rapidly evolved its AI offerings to compete with ChatGPT. In March 2025, Google introduced Gemini 2.5, its most advanced model to date, with advanced reasoning capabilities.

Gemini 2.5 features a 1 million token context window and native multimodality that allows it to comprehend vast datasets across text, audio, images, video, and code repositories.

Claude

Anthropic released Claude 3.7 Sonnet in January 2025 and has since added several new features, including a “computer use” feature, allowing Claude to interact with a computer’s desktop environment, mimicking human actions.

Claude 3.7 Sonnet showcases improved performance in coding, multistep workflows, chart interpretation, and text extraction from images. It introduced Artifacts for real-time output preview as well as Projects for building a knowledge base for select projects. It also recently added Web search and a research mode to compete with ChatGPT’s Deep Research feature.

DeepSeek

Chinese startup DeepSeek upended AI markets when it launched its open-source R1 model in January. At the time, it matched OpenAI’s performance at just 3-5% of the cost, triggering an 18% Nvidia stock plunge that erased $589 billion in value. DeepSeek’s AI assistant also quickly topped Apple’s App Store charts. Since then, DeepSeek released a new model dubbed V3, though upgrades to models like Gemini, Claude and ChatGPT have taken back the spotlight. Still, DeepSeek’s efficiency raised serious questions about the compute-intensive approaches of major AI companies.

Chatbot web search experiences

The rise of AI chatbots is set to change how consumers search for information online. In addition to offering a more natural interface, AI chatbots can summarize information and create original responses based on internet sources without the usual list of links from today’s search engine results. Here are a few emerging options.

Google’s AI Overviews

Google has integrated Gemini into its search experience through AI Overviews. Offering conversational responses to queries, AI Overviews gather information from multiple sources and present it in a detailed, human-like format. This feature transforms search results into a more interactive experience, particularly for complex queries.

AI Overviews offer quick, factual answers to straightforward questions, allowing users to grasp essential information without clicking through multiple links. Of course, the downside is Google is expected to send far less web traffic to publishers as AI Overviews become more common.

Microsoft Copilot (formerly Bing Chat)

Microsoft’s Bing search engine launched a similar chat-based search experience. Microsoft initially launched its chatbot as Bing Chat before renaming it Copilot in November 2023 and integrating it across Microsoft’s software suite.

Though Microsoft released a chatbot search experience first, it hasn’t dented Google’s 90% market share compared with Bing’s 3.9% market share, according to November 2024 data from StatCounter.

Perplexity

Perplexity AI is a chatbot that is aimed at replacing traditional search. While similar to other chatbots, this “answer engine,” as the founders describe it, generates answers by searching the internet and presenting responses in concise, natural language. While the company initially said it planned to stay ad-free, it has since detailed plans to integrate advertising into the experience.

Arc Search

Launched in early 2024, Arc Search is a standalone mobile search app created by The Browser Company, which also owns the Arc browser. Its app can “browse” for users based on queries and generates unique results pages that act like original articles, linking to all sources used. Like Perplexity, the service has no ads, and the Arc browser connected to it blocks web trackers and on-page ads by default.

How marketers can use chatbots

Chatbot marketing uses AI-powered conversational interfaces across digital platforms to engage customers, sell products, and provide information. While many chatbots operate on messaging platforms like Facebook Messenger or WhatsApp, the rise of generative AI has expanded their capabilities and improved interactions.

“When we talk about chatbots now, I feel like we’re often talking about ChatGPT and things that are powered by generative AI. Siri, Alexa, Google Assistant, those have been around for years prior to the generative AI explosion,” EMARKETER analyst Jacob Bourne said on the “Behind the Numbers” podcast. “And those are AI-powered, but didn’t have the same kind of natural conversational abilities that chatbots have now.”

Engaging customers through chatbots generates important data since every interaction improves marketer understanding of user intent.

Here are ways marketers and retailers can use chatbots:

  • Use chatbots instead of online forms for lead generation. Chatbot follow-up questions can aid lead qualification by providing more customer information.
  • Generating content to engage customers about their loyalty programs, reminding users about their points and tallies.
  • Provide customers easy ways to get quotes for products and services and seamlessly transition to the order or reservation process.

Chatbots are also being integrated into the ad creation process. Google has released a Gemini-powered chatbot that assists advertisers in creating ad copy and creative through a conversational interface. Similarly, Taboola has launched an AI-powered advertising chatbot named Abby, aimed at helping small and medium-sized businesses navigate digital advertising on its platform.

Limitations and risks of chatbot marketing

Despite their potential, chatbots face several obstacles:

  • Consumer skepticism: Many consumers harbor negative perceptions of AI chatbots, particularly in customer service. Frustrations stem from lack of empathy, inability to understand complex issues, and difficulty reaching a human representative when needed.
  • Technical challenges: The high computational and power resources required to deploy advanced AI chatbots present a significant barrier. These limitations impact chatbot capabilities and speed, potentially hindering wider adoption.
  • Accuracy: Ensuring unbiased and brand-safe responses is essential, but chatbots struggle with delivering accurate information and are prone to “hallucinate,” making up false answers.

To mitigate these risks, retailers should implement strict guardrails. Over 80% of US consumers believe businesses should prioritize data privacy using robust data anonymization techniques, while 86% want regular internal audits to assess generative AI systems for biases, fairness, and security vulnerabilities, according to a January 2024 KPMG study.

Future chatbot applications

The next 12 months promise a wave of innovative chatbot applications:

  • AI-powered “digital twins:” Lifelike AI avatars of sales representatives could offer 24/7 availability and personalized interactions, potentially bridging the gap between AI and human-like engagement.
  • Enhanced personalization and customization: Advancements like those seen in Google’s Gemini are expected to make interactions more human-like and personalized. Users will have greater control over chatbot voices, conversation styles, and integration with other tools.
  • AI agents: Going beyond conversational AI, AI agents can automate complex business processes, acting autonomously on behalf of users. While risks exist, AI agents hold enormous potential to boost productivity and free up human workers for more strategic tasks.

EMARKETER Resources on voice assistants