2019 Chatbot Predictions Report - netdna-ssl.com

2019 Chatbot Predictions Report

T H E E V O L U T I O N O F C H AT B O T S I N 2 0 1 9

We live in an instant gratiication economy. Consumers have been trained by the likes of Amazon,
Google, Netlix, Lyft and Tinder to expect all of their needs to be fulilled in an instant. Whether
it’s searching for news, ordering toothpaste, watching a movie, booking a taxi, or inding a date,
everything needs to happen very fast and with little-to-no friction.

This has signiicantly raised the bar for every business. Consumers now expect the same standard
from every service provider they deal with. They don’t want to waste time in line, navigating complex
voice-menu systems or, worse, being placed on hold during a customer service enquiry. They don’t
want to trawl your website for operating hours, or link to support when an answer is not immediately
available. They want everything NOW, at their ingertips, with very little efort.

To meet these demands, companies will need to fundamentally rethink how they operate.
The winners will learn to adapt quickly, the losers will perish.

Conversational systems facilitating human-centred automation will be the secret weapon
of the victors.

Conversational computing will automate, streamline and optimize key human-centric business
processes. They will adapt to customers and employees (instead of the reverse), making employees
much more productive, while delivering a faster, more personalized experience for consumers.

In short, conversational computing will provide companies with an edge in a fast-moving world.

The following ive predictions represent our thoughts on how the technology will evolve from its
current state in 2019.

1   T H E D E M I S E O F T H E ‘ D U M B B OT ’

    Many companies have tried to deploy automated chatbots in an
    attempt to streamline operations, but have quickly come to realize
    how diicult it is.

    At the same time, many vendors make wild claims about the AI
    capabilities of their chatbots, but in reality most bots currently
    deployed are simple rule-based bots and include very little, if any,
    artiicial intelligence. Unsurprisingly, simple rule-based bots — those
    making use of basic robotic process automation that barely pushes the
    boundaries of smart email boxes — fail to deliver on the promise. These    Companies will
    dumb bots can’t deal with the complexities of human conversation.          replace 1st gen
    They have a hard time with misspelled words, identifying the right         rule-based bots
    intent, and managing non-linear dialogue.                                  with true AI bots,
    As a result, usage is not as expected, with dumb bots creating more        delivering on the
    friction in the customer experience, rather than less. Not surprisingly,   promise of human-
    the anticipated cost savings haven’t materialized.                         centric automation.

      PREDICTION
    Dumb bots will be on their way to the graveyard, as companies realize
    they can’t deliver the success rate of AI-based bots. They will start
    upgrading to bots with more AI capabilities, switching vendors to
    ensure their bots deliver on the promise.

2   C H AT B O T S W I L L M E E T R O B O T I C
    P R O C E S S A U T O M AT I O N ( R PA )

    In the face of an increasingly fast and unpredictable business environment,
    companies need to fundamentally rethink how they operate. Automation
    is becoming inevitable. But while traditional RPA functions (things like
    website scraping, form processing and client proile updates) are focused
    on machine-based automation, a much bigger opportunity exists to
    rethink human-machine automation.

    More sophisticated conversational interfaces will become a key                                           Conversational
    consideration in app design and consumer websites1 as companies see                                      computing will
    the beneit of human-machine interactions and expand their use cases,                                     emerge as the
    especially in the area of customer service.                                                              next frontier in
                                                                                                             smart automation.
        PREDICTION
    Conversational computing will emerge as the next frontier in smart
    automation. Forward-leaning companies will start piloting enterprise-
    grade platforms to help speed up operations and redeine how employees
    and customers interact with businesses.

    1
        https://www.dashbot.io/2018/12/06/the-biggest-trends-and-predictions-in-conversational-interfaces/

3   S U C C E S S F U L C H AT B O T D E P L OY M E N T S W I L L
    B E D E P E N D E N T O N H AV I N G T H E R I G H T P E O P L E
    A N D R I G H T D E S I G N F R A M E WO R K
    Chatbots are starting to have a signiicant impact on customer service and
    marketing functions.

    However, the promise of the technology extends far beyond these areas,
    with conversational computing set to be adopted through all parts of an
    organization, for both internal and external purposes.

    Companies need to build expertise in designing conversational interfaces, and
    train/attract the experts who can help them do so2. This isn’t just limited to
    those skilful in the art of technology architectures and data research. In order
    to create bots that can convincingly relate to and learn from a diverse range of
    customers, businesses will need to engage UX designers who understand how                                               Business Leads
    to design conversational interfaces and dialogues that are eicient and feel                                             will increasingly
    natural, while being transparent to the user.
                                                                                                                            take ownership of
    At the same time, input from the likes of customer service managers, marketing                                          chatbot deployment.
    leaders and operational experts will be critical to successful deployment.

        PREDICTION
    While ownership of most technology deployment has generally sat with IT
    departments, we will see an increased tendency towards Business Leads taking
    control of chatbot deployment. However to be successful, they will need to
    call on those who understand the business’s processes, alongside experts in
    developing conversational interfaces — a completely new design paradigm,
    and one that is very diferent from developing web or app interfaces.
    2
        Forbes, September 13, 2018. Why Data Scientists are Crucial for AI Transformation
        https://www.forbes.com/sites/cognitiveworld/2018/09/13/why-data-scientists-are-crucial-for-ai-transformation/#28ba60093f6f

4   S E L F - I M P R OV I N G A I W I L L L E A D TO B OTS
    R E Q U I R I N G L E S S T R A I N I N G D ATA

    2019 will bring new advances in AI algorithms, speciically in machine
    learning, into chatbots.

    Through a combination of both supervised and unsupervised learning,
    along with transfer learning algorithms, we can train and deploy smart
    conversational agents with much less training data3,4
                                                       .

    Once launched, a virtual assistant can quickly improve itself with adaptive
    learning algorithms, strategically selecting high-quality training data,
    drawing its own inferences, and actively asking humans to label elements                                                  Bots can be
                 .
    as necessary 5,6                                                                                                          deployed with
                                                                                                                              less training data
        PREDICTION                                                                                                            than ever before.

    With advancements in unsupervised learning and transfer learning
    algorithms, a wide range of AI-powered virtual assistants will be deployed
    in 2019 - with less training data required. Although these virtual assistants
    won’t behave exactly the same as humans (or pass the Turing test),
    they can complement and support human employees, delivering very
    solid KPIs and ROI.

    3
        BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, Jacob Devlin, Ming-Wei Chang, Kenton Lee Kristina Toutanova
    4
        A robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings, Mikel Artetxe, Gorka Labaka, Eneko Agirre
    5
        Interactive Language Acquisition with One-shot Visual Concept Learning through a Conversational Game, H Zhang, H Yu, W Xu
    6
        Learning to Ask Good Questions: Ranking Clarification Questions using Neural Expected Value of Perfect Information. Sudha Rao and Hal Daumé III.

5   V I R T U A L A S S I S TA N T S W I L L B E G I N T O M AT C H T H E
    PERSONALITY OF THEIR USERS

    AI-powered sentiment analysis based on text, speech and facial analysis
    has the potential to become more accurate than human judgment in
    certain contexts.

    As such, this technology will be very useful for developing chatbots.
    However, if and when it will be adopted depends on the market, since it
    may not be the irst priority for improving virtual assistant KPIs.
                                                                                  Companies will
    Sentiment analysis might be a handy tool at a later stage when optimizing
    virtual assistants. Largely relected in training data and conversational UI
                                                                                  begin to carefully
    design language, the personality of some virtual assistants will appear       design the personality
    to be inluenced by the sentiment, attitude and personality (race, style,      of their virtual
    gender, preferences) of the people who are chatting with them.                assistants in order
                                                                                  to make them more
      PREDICTION                                                                  likable and natural.
    Companies will begin to carefully design the personality of their virtual
    assistants in order to make them more likable and natural. Eventually,
    we will see chatbots with varying styles and personalities custom built
    to match diferent market segments. To achieve this, companies should
    consider the importance of diversity in gathering their training data and
    the team they bring together to develop them.

CONCLUSION

Our instant gratiication society means the bar has been set at a soaring height when it comes to
customer service expectations.

To fulil this monumental challenge, businesses need to act now in order to optimize the very real
capabilities AI can ofer, using human-centric automation to become more agile and lexible in the
face of constant and rapid change.

Business leaders need to ensure their conversational computing technology is based on solid AI
algorithms to deliver both fast and efective results. Without that, bots will fail.

It is important to choose platforms and products that can scale across use cases with control in the
hands of Business Leads, and develop expertise in building conversational interfaces by attracting
the right people and ofering them the right training.

Finally, those looking to succeed in such a competitive business landscape should establish guidance
and best practices, including how much training data is needed, measures for evaluating virtual
assistants, and expected KPIs in diferent tasks. Businesses with a scientiic evaluation methodology
and a solution that can systematically optimize evaluation measures are more likely to enjoy the
beneit of AI-powered technology.

ABOUT RULAI

Rulai is a new Enterprise Conversational Computing Platform provider. Rooted in academia, the
founding team has a combined 200 years experience in AI research, published over 400 research
papers and iled over 80 patents in advanced AI-based dialog management.

Its SaaS platform enables companies to build automated chatbots for customer service, marketing,
sales, logistics and HR use cases, and has been deployed across a wide variety of industries.

Rulai-based bots help companies automate many human-centric processes to create a fast and
frictionless experience for employees and customers. Its self-serve platform allows business users to
create and evolve bots with minimal use of precious IT resources. Rulai was recently recognized by
Gartner, Forrester, and Bloomberg.

                    To request a demo or learn more about how
                   Rulai can help your enterprise, visit www.rul.ai

1999 S Bascom Ave, Suite 270 Campbell, CA 95008
                  www.rul.ai
                  sales@rul.ai
                 408-438-5371