What is Conversational AI for CRM?

Conversational AI for CRM empowers staff with an intelligent personal assistant that helps them navigate their work day. Read on to learn more.

Artificial intelligence (AI) is redefining the workplace. Taking repetitive, time-consuming tasks away from employees so they can focus on customer service, creativity, and decision-making. As AI matures, it’s becoming more than just a tool. It’s an intelligent assistant that can guide us through our workday, suggest the next best action, and you can even have a chat with Conversational AI.

You’ve probably already interacted with Conversational AI. It’s been widely adopted to provide 24/7 first-line support that sounds human and goes beyond scripted answers. And for good reason — studies show that generative AI can help automate 30% of hours worked today by 2030, allowing more time to focus on increasing revenues and spending time with customers.

But did you know that combining Conversational AI with CRM is fundamentally changing how staff use applications? They’re happier and more productive, and businesses are reducing costs while improving operational efficiency. Up to 45% of executives are spending more on AI. But, many might not know where to invest.

Let’s take a look at conversational AI, how it evolved from chatbot to copilot, and how it works with your CRM platform. 

What is conversational AI?

In simple terms, Conversational AI is a technology that can talk to you — not just respond to you based on pre-programmed knowledge, but actually process what you say and reply in a way that sounds natural.

It’s often found in chatbots and virtual assistants and can respond to text or voice inputs. Unlike older AI chatbots, you can ask questions in natural language and get a relevant, trustworthy answer. 

Think of it as a helpful colleague. Looking at ‌data you don’t understand because it’s complex or not accessible enough (like almost half of the business leaders)? Ask it to tell you what the data means. Not sure how to respond to a customer? Get it to draft a response you can check and send. Need to message someone in a different language? It can automatically translate for you.

How AI evolved from chatbot to intelligent assistant

Chatbots have developed from simple rule-based systems that used pattern-matching to simulate conversation, into intelligent assistants capable of having full conversations. But the journey hasn’t stopped there.

Early conversational chatbots used scripts and templates to generate responses. These relied on FAQs or knowledge articles, which helped customers self-serve and freed up time for support staff. The next generation of chatbots was trained on billions of lines of data and used Machine Learning algorithms to continuously improve responses based on user feedback. We also saw the widespread release of personal AI assistants on our phones. These could recognise speech and talk back to us, but still sounded robotic.

When generative AI chatbots hit the market, it radically changed customer service and marketing. Here was technology that could create and understand natural language prompts. Conversational chatbots differ slightly from generative AI. They can’t create art or videos, but they can chat with you and create written content.

How does Conversational AI work?

Conversational AI uses Machine Learning and Natural Language Processing (NLP). It’s trained on large amounts of data — ideally, trusted internal data, so it will be perfectly tailored for your business. When the AI has learned to recognise words and phrases, it moves on to natural language generation — in other words, talking back.

Say you want to find out what happened during a meeting without reading a 40-page transcript. You’d drop the transcript into the AI tool and ask: “What were the outcomes of this meeting?”

Your query would be converted into machine-readable text, processed, and analysed by NLP, along with the transcript. Thanks to Machine Learning and its training data, the AI would scan the transcript and create a summary of the actions for you.

Once the AI tool sends your summary, it’ll respond: “Here are the outcomes.” If you want to know whether you have any actions, you can continue chatting to it without having to resend the original query. If you have any feedback on the AI response, you can share it, and it will use Machine Learning to provide improved answers to you and your colleagues in the future.

Why use Conversational AI?

Conversational AI helps your team ‌work faster, smarter, and to make more informed decisions. It has the potential to transform and modernise the workplace, and it’s flexible, so every team will get different benefits from it.

 1. Sales – help sales reps research accounts and prepare for meetings, keep records up to date, and summarise outcomes. Conversational AI can extract customer sentiment and suggest the next best steps from video calls and transcripts. Reps can also use it to generate sales emails in the right tone, and to add causes to personalise customer contracts.

2. Service – 78% of agents say it’s difficult to balance speed and quality. Conversational AI can help them meet customer expectations 24/7. It can be rolled out across multiple channels, including social media, to provide out-of-hours help. It can also write personalised, relevant responses grounded in trusted company knowledge, helping your agents to solve cases faster and summarise outcomes so your team can learn from previous cases.

3. Marketing – get help creating copy for campaigns and use AI to improve segmentation and optimise the audience for every email. You can also ask it to create personalised landing pages for customers based on their preferences and browsing data and save time by pre-populating forms and generating feedback surveys. An AI marketing assistant can also help you make sense of metrics – 72% of high-performing marketers use real-time analytics to optimise campaign performance.

4. Commerce – empower your staff with step-by-step guidance to create digital storefronts that convert. Conversational AI for commerce can also automate tasks such as populating product catalogue data, writing product descriptions in multiple languages, SEO optimisation, and creating personalised promotions and ads for customers.

5. Developers – help developers write more effective and accurate code that’s proactively scanned for vulnerabilities. This significantly speeds up time to market, while improving quality. 

These are just a few examples. Conversational AI can help everyone ‌turn data into insight faster, automate tasks, write copy, and summarise outcomes. But you can also use it to address industry-specific pain points. When it comes to AI, you’re only limited by your imagination.

Using Conversational AI responsibly

If you’re planning any new project with AI, you need to do it responsibly. That means finding out how your customers and staff feel about AI and addressing any concerns. Trust is a big one. Users can be wary of sharing sensitive information with a machine. They need to know that their data is secure.

Make sure the AI product that you use has a secure AI architecture. We developed the Einstein Trust Layer to implement enterprise security standards. It allows companies to benefit from conversational AI without compromising customer data.

When you’re training your AI, make sure you’re aware of bias and toxicity. If you’re using skewed datasets that aren’t representative of company values, there’s a risk of AI learning and replicating societal bias or harmful stereotypes.

Another common worry is that people will lose their jobs to AI — according to our State of IT report, 64% of IT leaders are concerned about the ethics of generative AI, and 62% are worried about the impact on their careers. Reassure your team that Conversational AI is there to help, not to replace them. It’s good practice to always have a human in the loop when using AI, to check how it responds.

What’s next for Conversational AI?

If you’re excited about Conversational AI, get ready for copilots. AI copilots are integrated with platforms such as your CRM and use Large Language Models (LLMs) to help users with various tasks related to their roles. They supercharge productivity and efficiency by proactively supporting users with the right help at the right time. They automate dull tasks, analyse large amounts of data quickly, streamline communication between multiple stakeholders, and connect multiple platforms and tools.

An AI copilot for CRM is a powerful assistant that can do the work of hundreds or thousands of individual applications, making every aspect of your business more efficient. You can find out more about AI copilots for CRM here, how to design your own here, and Einstein Copilot, our own Conversational AI assistant, here.