The use of chatbot software to augment in-house tasks and customer service has been ascending the agenda of many enterprises and SMBs, due in part to the rise and acceleration of generative AI since OpenAI publicly released ChatGPT in November 2022. However, chatbot development history can be traced back to the 1960’s, and has gradually evolved over the decades in line with computing and the web.

While the development and deployment of chatbots has proved common across business websites, usually to answer selected customer queries, widespread investment in GenAI has opened up a new outlet for innovation. This has led to implementation in the form of browser search bots, office software digital assistants and third-party APIs. Here, we explore how chatbot innovations have evolved, and how its future could play out.

The history of the chatbot

The first chatbot was developed in 1966 at MIT — they called it ELIZA.

ELIZA, the mother of all chatbots, answered some very simple decision tree questions.

This first chatbot iteration has since evolved and developed, naturally. Through the 1980s and 1990s, the technology was deployed in automated telephone systems that used very simple decision trees, right through to MSN and AOL.

As we move further along the timeline, chatbot technology has exploded across social and business channels. Why are we so interested in them now? Why has so much attention been placed on the technology?

“It comes down to three main reasons,” says Howard Pull, executive director, CX strategy at Landor & Fitch.

1. Messenger apps and voice-assistance are both inductor bots

“If you think of the likes of Facebook Messenger, WhatsApp, LINE, they have really opened up their APIs, so brands can now launch and create e-services that do everything from product recommendations, booking and service through to FAQs within that.”

2. A change in a ability

“There’s also been a step change in chatbots’ ability to sense; the ability for these bots to recognise images and recognise voice, which has allowed us to essentially search using imagery. If you’re Amazon, for your parts service, you can search via that, or if you’re EasyJet, you can provide an image and let the bots search from that.”

3. The rise of AI

“Finally, there’s been a step change in the learning, and that’s where the question of AI fits in. The ability to appear human and deal with more human conversations has undergone a massive step change, in terms of the intelligence and the machine learning that sits behind the chatbot. It’s allowing brands and services to create an interface that feels human and interacts in a way that people expect to be spoken to and dealt with.”

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Chatbot misconceptions

Throughout the history of chatbots there’s been a misconception around the abilities of the bots. There’s a very high consumer expectation that a bot should be able to answer open-ended questions. However, this isn’t always the case and can be frustrating — as I’m sure many of you have experienced.

The quality of chatbots differs wildly, depending on how much the brand has invested in it, from a technology and operational perspective.

“I think the number one misconception surrounds the perceived role of a chatbot: to chat,” says Pull. “The actual goal is to solve a problem, to provide a service and give the customer that service in the quickest possible time.”

This isn’t an exercise in replacing humans; it’s about finding new places and new ways to interact with consumers. And, the better quality the bot, the more likely a brand is to attract and retain their audience.

It also not about creating something that is massively conversational. “People really want something that provides quick answers, connects them to a service, allows them to buy something, in the simplest way possible,” explains Pull.

The chatbot experience

Chatbots are going to play a massive role in improving the customer experience.

Looking at the customer service experience, there’s a huge amount of frustration with most brands when you try to contact them — waiting times, being put on hold etcetera. For a service brand, investment in chatbot technology is absolutely critical.

Moving beyond this into a brand that has purpose and is looking to change things in its sector, chatbots are also going to be critical for increasing engagement and retention levels.

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The internal chatbot

In recent times there has been an explosion of chatbots in the enterprise, internally. In this scenario, it’s about treating the employees similar to customers.

“A chatbot can be used in everything from room booking to IT,” says Pull. “In a large, mobile workforce, the tech can provide a simple, quick interaction for employees to engage with the business. That’s where you begin to see the big players, such as Microsoft and what they traditionally do with Office365: how can we put in that chat-based technology, open some of those services up and really reduce the need to call and give those employees a much simpler, more effective experience.”

At the moment, this type of service is emerging in brands that have big manufacturing or big workforces. But, it will begin filtering out into the mainstream, broader business world.

Going forward, chatbots for improving ’employee service’ in the enterprise are set to become even more commonplace.

The future of chatbots

As the generative artificial intelligence behind the most widely used chatbots continues to grow, businesses will be able to satisfy more specific and bespoke customer queries, using a range of capabilities including more human-like text, images and graphics.

They’re are going to get a lot smarter, so you’ll see brands invest a lot in new areas beyond service.

“If we look at where the main use cases are, customer service has been a traditional one, just because the money is there. So if you’re a brand like Amtrak, you can save $1m a year on customer service expenses, just by automating that,” explains Pull.

Pull went on to state that the focus of chatbots has been on customer service, purely because there has been a much clearer financial return. However, the value of chatbot software, powered by generative AI, for in-house duties and projects has grown exponentially, and will only continue over the next few years.

Chatbots will begin to solve new problems — and this surrounds the idea of choice.

“With companies such as Diageo, we’re looking at how we can pair a whisky to your personal tastes, and bring all that together through a chat interface — Diageo Whisky Matcher,” says Pull.  “So, we’re going to see chatbots provide more advice; I think that’s a great example of where the technology is going to move towards. Today, we’re still in that FAQ simple customer service stage.”

Bots like Cleo, for example, are helping people manage their money and providing personal financial advice. It offers pre-emptive nudges and gives straight forward answers to budget based questions

In the future, the technology will have the ability to recognise voice, and within that, tone — a capability already being explored across contact centres globally. Through this, it can recognise if a customer is happy or unhappy, and react accordingly. This will be a game changer from the customer-facing side. Indeed, chatbots and AI are going to integrate across channels.

“One of the things we’re advising a lot of brands to look at is how can they take the smarts that they’ve built into a bot and replicate that across their channels,” says Pull. “It’s not just about creating something for Facebook messenger or WhatsApp as a bot, it’s about taking that smart, taking the work you’ve done on that AI, and think how can we apply that to the voice service. How can we then apply that to the website, how can we then apply that in store?”

“Over the next few years, we’re going to see AI and bots packaged up and put into a lot of different channels, beyond text and voice.”

Chatbot examples

On top of the examples mentioned above, here are some other bots to look out for:

• Bard – the GenAI-powered chatbot developed by Google to compete with ChatGPT
• Lego gift bot called Ralph
• Visabot for Schengen Area immigration services
• DoNotPay – a bot designed to simplify the parking ticket appeals process. In its first 21 months the bot took on 250,000 legal cases and won 160,000 appealing over $4m of parking tickets.

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