To begin this discussion, let’s start with a clear definition of what artificial intelligence is:

AI uses computer systems to do tasks that typically only humans have been able to do. A quintessential example is IBM Watson’s ability to learn games to the point of beating human chess and “Jeopardy” champions. And within AI lies a set of techniques called machine learning, which enables “computers to get better at tasks with practice. And within machine learning is deep learning, involving algorithms by which computers train themselves using multi-layered neural networks and vast quantities of data,” explains Fortune.

Artificial intelligence is a $15 billion industry and growing. With more than 2,600 companies developing intelligent technology, the value of AI is expected to rise to more than $70 billion by 2020. Fast Company Design

Artificial intelligence to reach 70 billion by 2020

By 2025, the AI market will surpass $100 billion. — Constellation Research

It’s been six years since IBM’s Watson defeated two of “Jeopardy’s” leading human players on Earth, and we will certainly see an avalanche of developments over the next six years. As the sophistication and ability of artificial intelligence grows, so does that of content intelligence. Together, these two intelligences can unlock higher content ROI through, for example, content creation and creating hyperpersonalized content. Perhaps one of the most useful developments in AI is the movement toward more natural, plainer language.

IBM Watson Wins on Jeopardy

The move toward natural language interfaces has already picked up steam with the explosion of companies focused on enabling chatbots, digital assistants, and even messaging apps eclipsing social networks in monthly activity. — Narrative Science, 2017 Predictions for Artificial Intelligence and Communication

This move provides organizations enormous opportunities. “To engage consumers directly at scale is very appealing to businesses and organizations of all sizes. We are already seeing brands and media companies adopting messaging app based chatbots for distribution as well as customer engagement. Having interacted with about 40 bots and seeing some of the upcoming technologies, I believe chatbots will focus on three key social consumer experiences: content consumption (informational and entertainment), customer service, and productivity (including shopping experiences),” explains Edelman’s Adam Hirsch.

By 2020, AI bots will power 85% of all customer service interactions. Gartner

And this goes beyond just smartphone and computer interactions. The explosion of AI and machine learning “will be embedded into everyday things such as appliances, speakers, and hospital equipment. This phenomenon is closely aligned with the emergence of conversational systems, the expansion of the IoT into a digital mesh, and the trend toward digital twins,” Gartner predicts in their Top 10 Strategic Technology Trends for 2017.

Artificial intelligence will continue to show up in more and more household appliances

In 2018, Ericsson expects the number of IoT connected devices to surpass mobile devices.

Microsoft UX Lead Joseph Dickerson agrees: “As machine learning and web-based computing power increases, the power of these devices will become even more impressive to consumers. Expect a critical mass to occur with consumers this year as more devices get into homes and people get used to asking computers for help.”

Currently, four virtual assistants dominate the AI landscape: Amazon Echo’s Alexa, Microsoft’s Cortana, Apple’s Siri, and Android’s Google Now. Although each are in their infancy, one Business Insider tech reporter spent eight hours talking with these robots and believes, “Ultimately, you’re looking to the future with these things. Going forward, Google has the most cushion to lean on … [it’s] sitting on a treasure trove of data.”

Chatbots and Intelligent assistants will become more popularPutting your head in the sand will not make this reality disappear or pause, so it’s imperative business leaders prepare for this new wave of change. Proper content engineering is a crucial aspect of preparing for the impact artificial intelligence will have on every organization, and Content Science CEO Colleen Jones points to nine content engineering activities teams can start or ramp up:

  1. Modeling content structures, schemas, and semantics
  2. Architecting content using taxonomies and other metadata magic
  3. Designing content delivery
  4. CEM lifecycle planning (including when to archive!) and implementation specifications
  5. Marketing automation workflow planning
  6. Designing content management workflows, reporting, and user support services
  7. Content reuse planning, adaptive content strategy, and content personalization architecture
  8. Audience- and session-based analytics personalization rules and scoring, validating content targeting against user task success
  9. Multisite content syndication and content API definitions

As machine learning progresses at a rapid pace, top executives will be called on to create the innovative new organizational forms needed to crowdsource the far-flung human talent that’s coming online around the globe. Those executives will have to emphasize their creative abilities, their leadership skills, and their strategic thinking. — McKinsey, Artificial Intelligence Meets the C-Suite

New organizational forms will be required to crowdsource human talentHarvard Business Review also advocates that artificial intelligence will redefine management, and managers are ready, with 86% saying “they would like AI support with monitoring and reporting.” Half of respondents in a 2020 McKinsey study say their organizations have adopted AI in at least one function. The same study found that most respondents at “high performers” say their organizations have increased investment in AI in each major business function in response to the pandemic, while less than 30 percent of other respondents say the same.

Perhaps one of the most important points about AI is that it should be used with, not in replacement of, the smart people on your content team.

The fact is that AI technologies can be incredibly effective at helping you create better content faster than you otherwise could. Content that’s on-brand and on-target. But it needs to be used in collaboration with your content creators, gently nudging them with the appropriate guidance while they write and offering the governance necessary to ensure consistency. In other words, you can’t simply rely on these technologies blindly. To reap their benefits, you have to embed them into your existing teams and workflows. Andrew Bredenkamp, CEO Acrolinx

The Author

Content Science partners with the world’s leading organizations to close the content gap in digital business. We bring together the complete capabilities you need to transform or scale your content approach. Through proprietary data, smart strategy, expert consulting, creative production, and one-of-a-kind products like ContentWRX and Content Science Academy, we turn insight into impact. Don’t simply compete on content. Win.

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