Start talking: The true potential of conversational AI in the enterprise

That context allows for a much more personalised and efficient exchange, which makes things smoother for both sides. The market for conversational AI is starting to mature, especially in the banking, insurance, and health care industries. Bank of America’s Erica and Capital One’s Eno are examples from leading banks that have built large teams to develop conversational AI. Challenger startups like Lemonade and N26 are on the path to building autonomous organizations, which becomes possible as the industry moves from level three conversational AI to level five.

IBM Watson Assistant: Best for advanced features

By adopting some thoughtful practices, enterprises can improve their conversational AI outcomes. From a smart assistant that helps you increase your credit card limit, to an airline chatbot that tells you if you can change your flight, to Alexa who operates your household appliances on command, conversational AI is everywhere in daily life. Now, less than two years later, 100,000 bots litter the Facebook messenger landscape.

Over the last decade, it has become hard to imagine retail without e-commerce, thanks to the endless digitalization of everyday activities and the unprecedented use of mobile devices. Further enhancing agent expressiveness, Conversational AI 2.0 allows multi-character mode, enabling a single agent to switch between different personas. This capability could be valuable in scenarios such as creative content development, training simulations, or customer engagement campaigns.

How Slack’s AI strategy compares to Microsoft Copilot and Google Workspace

However, Slack’s conversational-first approach may offer advantages for organizations where informal communication drives decision-making. “Slack’s conversational interface and rich context make it a very natural home for AI agents,” Agarwal noted. These early results, while promising, should be viewed with appropriate skepticism. Productivity measurements in enterprise software often suffer from selection bias, where only the most successful implementations generate public case studies. The true test of Slack’s AI capabilities will come as adoption scales beyond early adopters to mainstream enterprise customers with more complex, less standardized workflows. Slack’s new capabilities depart from traditional AI assistant models that require users to actively prompt for help.

Features

Certainly, but only if you plan on overcoming the challenges and limitations that prevent it from reaching its full potential. For those interested in learning more, ElevenLabs encourages developers and organizations to explore its documentation, visit the developer portal, or reach out to the sales team to see how Conversational AI 2.0 can enhance their customer experiences. In addition to these core features, ElevenLabs’ new platform supports multimodality, meaning agents can communicate via voice, text, or a combination of both. This flexibility reduces the engineering burden on developers, as agents only need to be defined once to operate across different communication channels. The feature caters to global enterprises seeking consistent service for diverse customer bases, removing language barriers and fostering more inclusive experiences. The true power of conversational AI lies not in its ability to mimic human speech but in how it reshapes decisions, builds trust and adapts to complexity.

• The result was a system that provides its customers, who live in six countries, with a broad and rich data set across several channels, including home devices, mobile devices and social media.
• The ability to reach, engage, and enable empowered B2B audiences — whether buyer, customer, or employee — means something different to every firm based on what they offer, how buyers buy, and how customers adopt the solution and engage post-sale.
• CallMiner continues to set the industry standard through sustained innovation and platform expansion.
• For premium brands, an AI can verify identity and route calls, yet every interaction ultimately connects the customer with a human expert.

Questions, such as what kind of experience to provide to customers, employees, and partners, and how to align conversational AI with organizational goals, will help to identify the right purpose. It informs them on what documents they must submit and even makes preliminary selection of resumes. Beyond chatbot capabilities, conversational AI should understand complex sentences of human speech in the same way humans do. Real human conversation is never straightforward — it is full of imperfections consisting of slang, multi-string words, abbreviations, fragments, mispronunciations and a host of other issues. Conversational AI is a form of technology that can be used to both navigate and comprehend these give-and-take interactions.

Use conversational AI to handle repetitive tasks while reserving complex interactions for human agents. The new AI features will be included in all paid Slack plans, with advanced capabilities reserved for higher-tier subscriptions. Enterprise+ customers will receive the full AI experience, including enterprise search and governance controls designed for large-scale deployment. Early customer results suggest meaningful productivity gains, though the sample size remains limited. Salesforce’s internal engineering team reports that its AI agent has handled over 18,000 conversations across 3,500 users in six months, potentially saving the equivalent of eight full-time employees worth of work annually. Salesforce has built its AI capabilities around what it calls “the Einstein Trust Layer,” emphasizing that customer data never leaves the company’s infrastructure or trains external AI models.

What is a good example of how a company is using your AI solutions to benefit their business?

Here is a head-to-head comparison summary of the best conversational AI platforms. As adoption of conversational AI spreads and companies become more aware of its benefits and limitations, finding the right balance between AI and the humans will become more critical, Sutherland says. For example, a biotech firm that’s developing a conversational AI system to assist with the development of novel compounds will likely much more specific data than, say, a mattress store would need, Sutherland says. Assuming your firm’s data is as safe as possible, give your AI systems unhindered access to every database that they need to perform tasks successfully. No one wants to be on an airliner that is short of jet fuel, and companies can’t afford to be in the same disastrous situation with their AI systems. This capability ensures that the agent can recognize the language spoken by the user and respond accordingly within the same interaction.

Enterprises must invest in diverse, high-quality datasets and perform regular testing to ensure outputs are inclusive and accurate. I expect this domain expertise to turn conversational AI into a strategic asset—enhancing precision, reducing errors and saving time. Explainable systems can also ensure AI remains accountable, making it easier to detect errors, manage risks and build user confidence. According to a MarketsandMarkets report, the conversational AI market—valued at $13.2 billion in 2024—is expected to expand to $49.9 billion by 2030, growing at 24.9% CAGR. OpenTable handled 73% of restaurant web queries using Salesforce’s Agentforce AI in just three weeks, while payment processor Engine reduced average handle time by 15% and projects $2 million in annual cost savings. Perhaps more intriguingly, Slack will introduce contextual message explanations that activate when users hover over unfamiliar terms, acronyms, or project references.