AiThority Interview Series with Rebecca Lieb, Analyst and Founding Partner at Kaleido Insights

Content isn’t only writing itself, but images, videos, and other forms of communication can now be created with little or no human intervention.

Know My Company

Tell us about your interaction with smart technologies such as AI and customer experience platforms such as Voice and Intelligent Assistants.

As an analyst firm, we are four partners, each of whom brings a unique perspective and field of expertise to examine new technologies. So, for example, in the case of our recent research, “Automated Content: How Artificial Intelligence Impacts Content Throughout the Organization,” I teamed with my colleague Jessica Groopman. Her work has focused extensively on the technology side of AI, as well as looking at diverse aspects such as ethical issues.

My focus is marketing, advertising, media, and content. In fact, I’ve published more books and research on content strategy than anyone else in the field. We also draw on the experience of our partners. Jaimy Szysmanski is laser-focused on customer experience, while Jeremiah Owyang concentrates on business transformation. Bringing these diverse lenses together is our strength — and hence, our reference to a kaleidoscope in our firm’s name.

How did you start in this space? What galvanized you to start Kaleido Insights?

See above! The four of us are a proven team, having worked together for years before we founded Kaleido Insights. We each have different, but complementary, areas of expertise. We’ve all co-authored and collaborated on research in the past, as well as on engagements for our clients. We’re also fast friends who greatly enjoy working together and have developed deep trust and reliance on one another’s insights. We feel strongly that together as a team we are greater than the sum of our parts.

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How do AI and Machine Learning techniques unlock new horizons for human efficiencies in business operations?

Businesses have become overwhelmed with the need to create content, for marketing and myriad other business functions. It’s a daunting and difficult task. ‘More’ content is never the solution. What’s needed is better, more tailored, appropriate, meaningful, timely, and personalized content, which can be achieved at greater scale and at a much lower expenditure of resources (staff and budget) via automation.

How do you differentiate between technologies for AI and Machine Learning?

AI is an umbrella term for a variety of technological tools and methods used to mimic cognitive functions across three areas: perception/ vision, speech/language; and learning/analysis. A machine’s ability to “cognate” is supported by multiple approaches—Machine Learning, Deep Learning, Natural Language Processing (NLP), computer vision, and other existing and emerging techniques—multiples of which can be used simultaneously for a given use case. We acknowledge discrete differences among techniques, but for simplicity, our report uses “AI” interchangeably for applications involving machine learning and other techniques.

Which sectors are most readily prepared to adapt AI/ML disruptions?

Our research deals with this extensively. Just as content isn’t ‘just’ a function of marketing, neither is automated content’s value limited to the marketing department. In fact, nothing could be further for the truth. Our research examines the value of AI and content automation across industries and business functions. Service and support; legal; HR; product and other business areas will be impacted by this trend, as will industries such as news and media, finance, energy, and beyond.

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Recent Insights and Analytics

Tell us more about the latest report on the role of AI in Automating Content Marketing.

Content isn’t only writing itself, but images, videos, and other forms of communication can now be created with little or no human intervention. Artificial Intelligence (AI) drives this trend (but other technologies are involved as well). The implications of automated content go far beyond marketing into numerous lines of business: service and support; legal; HR; product and other business areas will be impacted by this trend, as will industries such as news and media, finance, energy, and beyond. Our research defines automated content; present a portfolio of use cases; discuss the opportunities, risks and rewards of automated content; as well as its future state.

How could AI clear all the clutter from various content platforms, including Social Media and News?

AI can clear clutter not just for users but for the workforce, too. Consumers are overwhelmed with the sheer volume of notifications, news stories, updates, and email. The need to organize synthesize content is pressing not just for them, but also for information workers (financial services, corporate development, VC, etc.). Information velocity raises other challenges.

Keeping us with a flood of information and content becomes daunting, not only in terms of learning and research, but also in areas such as content curation and/or aggregation. Tailoring content to its intended audience in an appropriate and acceptable form or medium is far from a simple task. The “right” content may not be published in the proper format, at the right time, or on the appropriate channel or device for its intended audience. AI can — and already is — addressing these challenges.

Tell us more about the role of voice and chatbot in the automated content landscape.

Voice is big, obviously, and will continue to grow in importance. And chatbots, which emulate natural language, have become a standard element in consumer communications, particularly in customer support and service. We’ve been looking at technologies such as LivePerson’s tool that can partially automate consumer support, handing in queries back and forth between a live agent and a chatbot. This way routine queries are addressed quickly, but complex ones receive immediate human intervention in a seamless fashion that’s invisible to consumers. This type of technology is also useful for businesses. It alleviates boredom and increases job satisfaction for support agents at the same time.

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How do you see the raging trend of including AI and Machine learning in a modern CMO’s stack budget?

We strongly believe AI isn’t “just for marketing.” Our research has identified over 40 distinct applications of AI and Machine Learning to content, as stated above in areas as diverse as legal, HR, customer service and support, and business intelligence. So yes, we do believe that marketing will have to invest in AI technologies as part of the stack, but these investments will be shared and used across the organization. Just as content isn’t only a marketing need or function, neither is AI.

What are the biggest challenges and opportunities for businesses in leveraging AI and Machine Learning technology to optimize their Customer Support and Customer Success?

Nailing brand voice is a challenge across the board for automated content. We recommend human editors and human intervention and frequent checkpoints, particularly in this early stage of the evolution of the technology. And as with any other kind of automated content, garbage in = garbage out. Algorithms and data must be impeccably defined and checked and governance put into place to monitor, optimize and fine-tune service and support initiatives.

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Hacks on Performance Improvement 

How should young technology professionals train themselves to work better with automation and AI-based tools?

Automated content is part of a much broader trend in how automation is impacting the way humans work. Individuals should make an effort to keep up with news and trends in both their industries and their own lines of business. At the same time, organizations will need to train their workforce in the use of new technologies, the skills necessary to use them, and the implications for the business itself. Training and education is, for the foreseeable future, an ongoing necessity for individuals and the companies that employ them.

What is the biggest challenge to digital transformation in 2019? How does Kaleido contribute to a successful digital transformation?

Digital transformation challenges are ongoing and ever-changing. This year it may be voice and AI, whereas 20 years ago it was email and search. Kaleido Insights’ mission is to enable organizations to decipher, foresee, and act on technological disruption with agility, based on our rigorous original research, trends analysis, events, and pragmatic recommendations. We help organizations, from start-ups to Fortune 50s to non-profits, stay ahead in a rapidly changing world as trusted advisors.

How potent is the human-machine intelligence for businesses and society? Who owns Machine Learning results?

Clearly, human-machine intelligence has massively important implications for society. Ever more data and equally critically the ability to process and analyze it in real or near-real time can — and is — changing the way we work and live. Who owns that data? This is not a simple question to answer. It’s also not a new question, there are many precedents. I used to work in cable television. Thirty years ago people were asking who owns the data from the set top box: The consumer? Hardware manufacturer? Carrier? Programmer? New technology always poses new puzzles and conundrums even as it clarifies and illuminates other previously dark corners.

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Where do you see AI/Machine Learning and other smart technologies heading beyond 2020?

There will be very rapid adoption in content automation across the enterprise. The groundwork has already been laid for this trend with technologies such as CRM and Marketing Automation. These technologies are already integrating with AI capabilities and platforms. Additionally, AI is permeating mobile phones, cameras, IoT devices, cars, and infrastructure all around us. What can be digitized — our voices, expressions, bodies, spaces, etc. — is changing. All of these are becoming data sources that, in turn, feed content creative, distribution, and targeting.

What is your opinion on the “Weaponization of AI and Automation”?

My report co-author, Jessica Groopman, is the expert in this field. She’s written extensively on The Rise of Digital Ethics.

The Crystal Gaze

What Cloud Customer experience and SaaS start-ups and labs are you keenly following?

We’re analysts, our job is to follow the industry microscopically, regularly conducting briefings with big players as well as dozens and dozens of start-ups. This isn’t the place for call-outs.

As a tech leader, what industries you think would be fastest in adopting analytics and AI/ML with smooth efficiency? What are the new emerging markets for these technology markets?

As stated above, we’ve identified 40 distinct applications of AI to content. These span not only different areas of the organization but also a variety of industries: news, media, agencies, law, finance, etc. Larger enterprises are already investing in and experimenting with content automation. Meanwhile, enterprise technology platforms such as Salesforce, IBM’s Watson and Adobe are incorporating AI into their core products. So many organizations that aren’t directly investing in AI per se are already beginning to incorporate its potential into content initiatives, perhaps without explicitly defining it as such.

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What’s your smartest work-related shortcut or productivity hack?

Feeds, feeds, feeds. I need to keep up with a constant flow of news and information, so customized Google News and Feedly are my go-to tools.

Tag the one person in the industry whose answers to these questions you would love to read:

My co-author on this report, Jessica Groopman.

Thank you, Rebecca! That was fun and hope to see you back on AiThority soon.