Contact Center Automation Demo Series

Make Every Agent Your Best Agent With Real-time Speech Analytics & RPA

The Evolving Chat Bot

The Evolving Chat Bot

Share on facebook
Share on twitter
Share on linkedin

the evolving chat bot


Chat bot technology is being driven at a revolutionary pace. Yesterday’s chat bot provider is already obsolete, and today’s chat bot provider faces a juggernaut of competition the likes of which the technology world has never seen. Chatbot platforms are rapidly becoming commoditized as there are so many players with little to no differentiation. The next generation of chat bots will belong to the “Big Six” – Google, Amazon, Facebook, Microsoft, Apple and IBM.

Chat Bot Generations – where is your provider?

The maturity of chat bot providers can be gauged according to the following scale:

 chatbot Jacada

Figure 1 – Chat Bot Maturity
  • Generation 1 chat bots are largely glorified FAQ’s. They are able to take rudimentary questions from users and return static data. NLP capabilities are severely limited and in reality are more of a keyword scan. They have limited effectiveness but have the advantage of being extremely inexpensive to implement.
  • Generation 2 chat bots offered massive improvements over their predecessors. First, we saw the advent of true NLP such that a user’s intent could be better understood. Moreover, these chat bots could do more than just display information – they offered limited transactional capabilities thanks to improved dialog management. Dialog management allowed multiple questions to be tied into a continuous conversation where each subsequent question could be in context to previously answered questions.
  • Generation 3 chat bots was a natural evolution that improved all the core capabilities over generation 2. The AI and NLP technology developed significantly with the ability to understand nuances and semantics. Bots also started supporting multi-media to provide more sophisticated user interaction. Conversations became personalized and companies finally started to realize some promised benefits such as reduced call volume.
  • Generation 4 is where the world now sits as 2018 nears. The “big 6” combined are investing billions into AI research, which includes improvements to NLP, machine learning, dialog management and more. These chat bots will also be deployed across all channels and aim to become a ubiquitous part of our lives. The technology advancement in this generation is of such a pace and of such complexity that no other chat provider will be able to compete in this generation. Look for tremendous advancements from these vendors through 2018.

Voice First Browsing

In a piece entitled “Gartner predicts a virtual world of exponential change”, they make the claim that by 2020, 30% of web browsing sessions will be done without a screen. They go on to state that companies like Apple, Google and Amazon are “turning ‘voice first’ interactions into ubiquitous experiences”.1

This in part is what limits the playing field to the “Generation 4” maturity model above – only those chat bots that are truly multi-channel with the inclusion of voice will be able to reach this classification.

The future Chat Bot will be an Ecosystem

The sheer technological advancement coupled with the demanding requirements dictates that implementation of a fourth generation chat bot will be an assembly of best-of-breed components. No single vendor will have the capacity or appetite to deliver and end-to-end enterprise ready chat bot.

The vendors identified as fourth gen chat bot vendors will be leading the ecosystems. The core chat bot technology will be theirs. However, other vendors will opt-in to the ecosystem and provide significant value-add in being able to deliver an end-solution. These ecosystems will be so dominant that even existing 2nd or 3rd generation chat bot providers may end up breaking into their parts to play in the ecosystem in a bid to remain viable.

So what will make up the chatbot ecosystem?

Deploying a fourth generation chatbot into a complex enterprise is not without its challenges. While the sophisticated AI and NLP is sufficiently “black boxed”, there is still a tremendous amount of work that needs to be done around dialog management and integrating the various assets found in the enterprise.

 figure 2

Figure 2 – Conceptual chat bot architecture

Figure 2 shows a conceptual abstract chat bot architecture in an enterprise. Integrating to all the external systems, customized business logic, heavy services orchestration and dialog management all add up to a significant code investment.

In fact, none of the Generation 4 chatbot providers chatbot providers currently provide any mechanism to seamlessly integrate these components. The result is extensive coding to combine the elements, which is time consuming expensive and difficult to maintain……and relies on an already overburdened IT Services Roadmap.

The primary areas that the ecosystem can provide to aid in the implementation of a fourth generation chatbot are:

  1. Orchestration and Business Logic – A customer interaction should be transactional, and these transactions will typically span multiple systems in an enterprise. For example, it may need to pull information from a knowledgebase, update a billing system, retrieve previous interaction history from a context store, and more. All of these inner workings need to be orchestrated in a visual, no-coding paradigm to ensure changes can be made quickly, all with a low total cost of ownership.
  2. Dialog Management – Consumers today expect both “linear and lateral” conversations – Having a framework to aid in managing dialog only improves the capabilities already provided by the fourth generation providers. This allows consumers to have a dialog with the chat bot instead of a series of questions and answers.
  3. Access to Transactions – Despite the sophistication in the AI layer, even fourth generation chat bots are only going to be as good as their access to underlying data and transactions. Data for which access is often restricted, and for transactions that often don’t exist. To truly remove the human element and be entirely transactional, it will be necessary to introduce Robotic Process Automation to surface transactions. The coupling of fourth generation chat bot technology with robotic process automation finally starts to deliver on the promised value of chat bots.

So what’s an organization to do?

Given this strong convergence of technology with a limited number of fourth generation chatbot vendors, organizations may rightfully be confused as to what implementation strategy they should use. Answering that question in part depends on where you are in your chat bot journey.

 figure 3

Figure 3 – Chat bot implementation journey

“We’ve never implemented a chat bot before but would like to get started”

This may be one of the times you’re being rewarded for not being an early adopter! If you’re now in the consideration phase of chat bot implementation, it is a critical moment to step back and reassess your approach. If your chat bot vendor is not one of the identified fourth generation chat bot vendors, you may be limiting yourself right out of the gate. You would be strongly encouraged to reassess your bot engagement strategy.

“We’ve implemented a chat bot but we’re not getting the results we had hoped for”

This is a refrain that is unfortunately becoming all too familiar. While organizations saw some initially encouraging results, as customer inquiries become more complex, the chabots became less and less useful. Whether this is due to limitations in the NLP, a lack of machine learning, a lack of dialog management or the inability to be full transactional, the limitations of current chatbots are quickly becoming evident. Organizations falling into this category should start planning to move to a fourth generation chatbot provider in order to future-proof their virtual customer assistant platform.

“We’re already using Google API.AI/Facebook/Amazon but are struggling to bring it all together”.

Congratulations on using a fourth generation chat bot provider. You’ve made the right decision and you are on a future-proof platform. However, we understand the challenges you face in implementing this in the enterprise and tying together all the various components. At Jacada, we provide the first graphical drag-and-drop chat bot design environment that brings together the sophistication of the fourth generation AI technology, coupled with dialog management and transactional capabilities – all in a code-free environment. This allows for the rapid assembly of fourth generation chat bots by selecting the best components in the ecosystem and seamlessly bringing them together.


Fourth generation chat bots are going to be cross channel industry leading AI engines, coupled with an ecosystem of supplemental technologies.

At Jacada we help organizations in developing their chat bot roadmap, and we provide a unique “bot framework” to assist in fourth generation chat bot implementation.

This bot framework includes the ability to create sophisticated dialog management, centralize all the orchestration between the components, and use robotic process automation to surface more transactions and remove the human element. All through a visual code-free environment.

For more information, visit

[About the author]chris headshot As Chief Marketing Officer, Chris’ responsibilities at Jacada include global Go-To-Market strategy, corporate positioning, and marketing strategy and campaigns. Chris has over 20 years of experience in product management, marketing and software development having held several senior leadership positions. Before joining Jacada, Chris founded a successful software consulting company providing large scale software systems to Fortune 500 companies. Outside of work, Chris enjoys app development, automated trading algorithms and provides pro-bono legal services. Chris holds a BS Computer Science and a JD, and is admitted to practice in the State Bar of California

1 –

Request a Demo

Talk to an Expert

Real-time Agent Assist

Get the Worksheet