If you’ve been working with digital for the past years, you have probably heard of mobile-first. When mobile-first was introduced by Google in 2010, it had a tremendous impact on how solutions were developed. Programmers and others started to think about smartphones and tablets before thinking about desktops and this required a huge change in thinking and also led to a fair share of confusion.

Fast-forward to 2017 and Google introduced AI-first. AI-first means to think about artificial intelligence at the beginning of each new initiative. How might AI help improve a solution? How might AI make for a better customer experience?

AI has tremendous potential, but how to capitalise on it? This was the theme of a workshop which was designed by UK-based MMT Digital and I had the pleasure of chairing as a part of the J. Boye Aarhus 17 conference.

Below I’ve shared some of my key learnings from the 3 hour session, but first thanks to Samuel Pouyt from the European Respiratory Society for kindly sharing his AI perspective and deep insight.

Learning #1: AI has been around for a while and we’re already using it

As Tracy Green shared in the beginning of the workshop, the term artificial intelligence was coined in 1955 by John McCarthy, a math professor at Dartmouth.

She also talked about general purpose technologies like the steam engine, electricity and quoted a recent Harvard Business review article titled The Business of Artificial Intelligence:

The most important general-purpose technology of our era is artificial intelligence

The article is a worthwhile read and also make a compelling case for how AI is poised to have a transformational impact on business.

I had brought my Amazon Echo Dot to the workshop which is one example of how AI has been made available to the consumers. While Amazon initially released the Amazon Alexa personal assistant in 2014, the Echo Dot became widely available in 2016. Today it sells for less than $50 on amazon.com. Since then Google has released their Home device which is also quickly finding its way into households.

workshop-participants-laugh-at-alexa
Amazon Alexa made people laugh during demo time, but the widespread and quick adoption in households, somewhat similar to the introduction of the iPad, means that expectations go up and AI also becomes expected in work projects.

How are you using AI today?

Learning #2: Voice is quicker and better than typing

For me personally, 2017 became the year, where I started using voice, instead of typing. Saying “Alexa” or “OK Google” has become a normal part of the day, yet this blog post was still typed the good old-fashioned way.

Tracy also brought a recent Stanford research project to the workshop which found that speech is 3x faster than typing for English and Mandarin text entry on mobile devices.

This brief video from the Stanford experiment shows speech recognition writes text messages more quickly than thumbs:

The HBR article on The Business of Artificial Intelligence also makes the point that the error rate is now lower for algorithms than humans.

If you are not sure, how widespread the adoption really is, according to eMarketer, forty-five million voice-assisted devices are now in use in the U.S. For more read: Alexa, Say What?! Voice-Enabled Speaker Usage to Grow Nearly 130% This Year

Voice search is one big topic to be further explored and Christian Köhler from byte5 in Frankfurt, shared valuable implementation insights, also from the perspective of search engine optimisation.

Learning #3: Chatbots are here to stay

I owe much of what I know about chatbots to Ditte Wolff-Jacobsen and have previously held a brief talk on chatbots, largely based on her insights.

Chatbots are conversational and Sara Walsh from Capital One has already shared extensively on designing the conversation. Take a look at this open source approach to turn your traditional web forms into conversational forms.

The use cases from chatbots are far ranging from the employee experience towards better customer experience. To mention just one example, the Dutch carrier KLM have come a long way this year to make chatbots a useful part of the travelling experience. Take a look at BB – their Blue Bot.

At the workshop Jake DiMare from Luminos Labs in Los Angeles, also brought 2 examples from the US:

  1. Gwen – Your personal gift concierge which is powered by IBM Watson
  2. Leading Hotels of the World who has been using AI to improve the hotel research and booking processes

Might chatbot be the wrong word for these use cases? IBM seems to call the same thing virtual assistants, which certainly sets a different level of expectation.

Tracy Green brought a local council example from the UK to the discussion. Read more in this article: Could AI chatbots be the new face of local gov? Enfield Council thinks so. The Council is half-way through a project to introduce IPSoft’s Amelia chatbot to act as a front end to digitised front line services.

Finally, Sharon O’Dea from the UK made the point that if you want to start with a chatbot, it might be smarter to explore internal use cases to build experience, instead of launching external ones first, where they might negatively impact the customer experience.

Learning #4: Metadata auto-tagging is one valuable use case

Metadata is vital to store and manage information about your content and with organisations drowning in content, be it text, video or images, there is a huge pain related to search & retrieval as well as sharing information. Manually tagging content with descriptions, copyright details and so on is incredibly time consuming.

Theresa Regli took the lead on this one during the workshop. She is a thought-leader on digital asset management and works as Chief Strategy Officer at KlarisIP. Theresa generously shared insights on the technologies for automatically generating metadata, including visual recognition, context comparison and machine learning.

She also shared key findings from a recent research, which included insights on the maturity of the currently available global API models, the error margin and on the significant time and effort which is required to train the tools.

Learning #5: The future of business is content-driven

Back in 2015, NY Times featured the now legendary quiz: Did a Human or a Computer Write This?

Do try it and you’ll likely be surprised at how well a computer can write.

Last year, content marketing guru Robert Rose held a popular keynote on strategic content at the J. Boye Philadelphia 16 conference, where he opened our eyes towards how far AI has come in terms of writing better content.

From the workshop last week, US-based content strategist Hilary Marsh said something which I agree with:

AI will push companies toward better, more user-focused content

Tobi Stadelmeier who is VP Engineering at German-based CoreMedia brought examples of what’s out there in terms of Natural Language Processing, Text sentiment analysis, video indexer and much more. He also shared the progress CoreMedia has made in terms of using AI to improve both the editorial experience inside the CMS and well as the customer experience.

Learn more about AI for your 2018 projects

There’s so much happening at the moment when it comes to AI. Jake DiMare has already shared some of his take aways in It’s AI-first at J. Boye 17.

In advance of the workshop, Ina Rosen from Copenhagen-based agency Operate not only reviewed my slides, but also shared some of these pointers:

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s