Conversational AI Platform providers includes intelligent platforms and bots that can understand and generate spoken or written text using NLP, NLU, ML and integration with enterprise systems. Gartner defines it as the set of platforms for managing, orchestrating and maintaining automated conversations.
Updated on: June 6th 2025
Estimated reading time: 9 minutes
Table of Contents
- Growth and Diffusion of Conversational AI Platform providers
- Benefits for organizations
- HOW TO IDENTIFY CONVERSATIONAL AI PLATFORM providers
- How to Implement Conversational AI Solutions in Your Business
- How to choose the right Conversational AI Platform Provider
- Conclusions: the value of a strategic partner
Growth and Diffusion of Conversational AI Platform providers
The global Conversational AI Software market is experiencing a rapid expansion. According to a recent report by MarketsandMarkets, the market is expected to grow from $17 billion in 2025 to approximately $49.8 billion by 2031, with a compound annual growth rate (CAGR) of double digits. This trend is being driven by increasing adoption in customer service, retail, healthcare, banking, and telecommunications, where advanced chatbots and virtual assistants are now key tools to automate and personalize customer interactions.
At the same time, global spending on generative artificial intelligence (GenAI) is experiencing a surge. According to forecasts cited by VentureBeat and RCRWireless, investments are expected to reach $644 billion in 2025 alone, with a growth of 76.4% compared to 2024. This acceleration is the result of the transition from experimental use of GenAI to a phase of widespread implementation in business processes, ranging from customer support to content automation, from internal training to decision support.
McKinsey’s The State of AI in 2024 report confirms this scenario: 78% of companies globally have already integrated at least one form of operational AI. Among the areas where artificial intelligence is being adopted most intensively are customer service, where chatbots and virtual assistants manage millions of interactions per day, and IT management, where AI supports automation, cybersecurity and predictive monitoring.
Finally, another significant figure comes from a recent survey published by Deloitte: 24% of workers declare they use GenAI tools for professional purposes, a significant leap compared to only 6% recorded in 2023. This growth signals a cultural change within companies, where tools such as ChatGPT, Claude and Copilot are becoming increasingly familiar in daily work flows, from writing emails to programming, from project management to content creation.
Benefits for organizations
The adoption of Conversational AI Software and artificial intelligence technologies more generally is generating tangible impacts on efficiency, costs and productivity in organizations of all sizes and sectors. Here are the main benefits observed to date, according to the most recent data:
Reduction of operating costs and increase in efficiency
According to research conducted by Vention Teams, 42% of companies say they have already achieved significant cost savings thanks to the implementation of solutions based on AI and data analysis. In particular, the automation of first-level interactions with customers (FAQ, order management, helpdesk) via chatbots allows to:
- lighten the load on contact centers,
- reduce the number of operators dedicated to standard requests,
- reduce the average management time (AHT – Average Handling Time).
Improving the customer experience
One of the main advantages of Conversational AI Software is the ability to guarantee immediate and personalized responses 24/7. This translates into:
- increased customer satisfaction (increased CSAT),
- reduction of abandonment rate (churn),
- increased loyalty thanks to continuous and consistent experiences.
- Advanced conversational solutions not only respond, but learn from data and adapt to user behavior, offering an increasingly precise and empathetic service.
Large-scale adoption and technological maturity
A Deloitte analysis reveals that over 75% of companies have already increased their investments in data cycle management to support AI. This means that organizations are building more robust infrastructures to:
- manage automated conversations at scale,
- train models in a secure and GDPR-compliant way,
- monitor and improve the performance of conversational systems.
Growth of autonomous agents (Agentic AI)
According to The Australian, more than 25% of companies are experimenting with forms of Agentic AI, that is, autonomous agents with the ability to:
- make decisions,
- complete multi-step tasks autonomously,
- interact with other company software.
This is an evolution compared to classic chatbots, which opens up advanced automation scenarios in areas such as project management, document research, report generation and operational planning.
Increased productivity in audit and control teams
A case in point comes from Deloitte UK, where 75% of internal auditors regularly use internal AI-powered chatbots to obtain assistance in audit processes. These tools help to:
- retrieve regulations and procedures in real time,
- verify inconsistencies in data,
- accelerate document control activities.
The introduction of AI solutions is therefore freeing up human resources from repetitive tasks and improving the quality and speed of checks.
HOW TO IDENTIFY CONVERSATIONAL AI PLATFORM providers
Gartner distinguishes 3 ways of categorizing vendors:
1) WHO WILL TAKE CARE OF THE CONSTRUCTION AND MAINTENANCE OF THE SOLUTION?
Conversational AI Platform providers are divided into three macro-categories:
Application development: define whether CAIPs require NLP-level development skills or make connection APIs available to developers.
and large-scale implementations require constant monitoring, so dedicating internal development figures could be prohibitive in terms of scalability and maintenance.
Line of business (LOB): check whether CAIPs provide low-code/no-code tools for training and maintenance of intent and dialogue design that enable front-line staff to be autonomous in management and maintenance.
Managed by vendor: If the development and maintenance of the platform is managed by the vendor. An appropriate positioning could be one in which the development and maintenance activity of the vendor overlaps with the management autonomy of the business people.
2) WHAT IS THE OBJECTIVE OF USE?
Cost reduction: reduce the number of resources allocated to particular processes as a function of cost cutting policies.
Enhancement of resources: increase the level of quality of work, using conversational AI to support people, decision making strategies and compliance.
Growth and innovation: increase business opportunities through innovation and the opening of previously non-existent channels, for example by integrating a bot into the messaging management of social platforms such as Whatsapp, Telegram or Facebook Messenger.
3) WHAT IS THE TARGET OF THE conversational AI PLATFORM SOLUTION?
Customers: conversational AI solutions for the end customer must take into account the wide variety of language, the potential use of colloquial words, different vocabulary and phonetic spelling used in the description of products and services.
Employees: business partners and other users who require specific tasks. The language in this case will include specific terms, acronyms and abbreviations, in a more transactional level of interaction.
Consumers: Usually the words consumers and customers are synonymous, but in sectors such as the media, for example, customers are the buyers of advertising space, while consumers are the target audience. In this case, integrations with products used by consumers are typical, such as web and mobile applications, speakers, etc.
How to Implement Conversational AI Solutions in Your Business
Successfully implementing a Conversational AI Software requires a well-structured strategy that integrates technical, organizational and regulatory aspects.
- Define use cases and key objectives
The first step is to identify pain points along the customer journey and translate them into concrete use cases: for example, reducing the load on customer service, improving the purchasing experience or automating the management of HR requests. For each case, it is essential to associate measurable KPIs, such as the rate of completion of conversations, the reduction of the average response time or the increase in customer satisfaction (CSAT).
- Prepare a solid data infrastructure
To work effectively, conversational AI solutions need to integrate with your existing systems. You need an efficient data pipeline to feed the model with up-to-date and relevant data, and a backend structure with robust APIs to connect CRM, ERP, knowledge bases, and other business tools.
- Adopt an omnichannel strategy
Customers expect to be able to interact with your company on any channel: website, mobile app, voice assistants, social media, WhatsApp. A good Conversational AI Software must be designed to offer a consistent and continuous experience across all these touchpoints, thanks to a centralized management of conversations.
- Monitor performance and improve iteratively
Implementation doesn’t end with go-live. It’s essential to have continuous monitoring tools in place to analyze conversation logs, gather feedback, and iteratively update models. Continuous improvement ensures greater accuracy and relevance over time.
- Ensure compliance and security
Finally, conversational AI must be secure and compliant. Make sure the solution is GDPR compliant, has well-defined data access policies, authentication and authorization systems, and that sensitive data is treated with maximum protection.
How to choose the right Conversational AI Platform Provider
Choosing Conversational AI platform providers is a crucial decision that goes beyond purchasing a technology: it means finding a partner capable of accompanying you throughout the digital transformation journey, with advanced solutions, solid governance and focus on business results.
Relying on a vendor also means carefully evaluating the return on investment and potential risks. According to Corporate Compliance Insights, 66% of companies that use AI have not yet implemented complete governance procedures, exposing themselves to risks related to bias, uncontrolled automated decisions and poor transparency.
A good supplier helps you:
- structure clear policies for AI control, access management and human supervision,
- enhance data quality, a critical lever according to Deloitte for the effectiveness of algorithms,
- implement advanced cybersecurity measures, to protect sensitive data and models from attacks, in a context in which AI-powered cyber threats are growing exponentially.
Conclusions: the value of a strategic partner
A reliable vendor does not simply “sell a bot”, but offers a scalable platform, constant consulting support and an evolutionary plan consistent with future innovations (such as autonomous agents or RAG – Retrieval Augmented Generation).
Ultimately, the right partner is the one that speaks the language of your business, integrates AI into your key processes and accompanies you in building an intelligent, secure and measurable customer experience.
Conversational AI Software Faqs
NLP/NLU based software solutions to automate conversations with users via chat or voice, integrating business systems.
To reduce costs, offer 24/7 support, improve CX and drive scalable digital transformation.
Generative AI, such as GPT or Claude models, enables chatbots and virtual assistants to produce more natural, complex and personalized responses than traditional intent-based models. In modern Conversational AI Software, these models are integrated to manage open conversations, dynamically understand context and access internal knowledge bases through technologies such as Retrieval Augmented Generation (RAG), improving the accuracy and relevance of responses.
Finance, healthcare and retail stand out for assistance, compliance and sales.
Updated on June 6th 2025
