Blog post
June 25, 2019

Bring on the AI overlords: from a content marketer

Artificial intelligence (AI). Just saying the words invokes visions of an apocalyptic future teeming with deadly machines like The Terminator or even software like The Matrix’s Agent Smith. At least that’s the dystopia the scaremongers are peddling. If the latest hype is anything to go by, AI will not only change life on earth as we know it, it will probably take your job too.

As an editor, content marketer and millennial, it appears my head is on the chopping block. Gartner predicts that by 2018, 20 per cent of business content will be authored by machines, and many are speculating that journalists will cease to exist. Add Elon Musk comparing AI to a demon, and even I’m spooked.

But I won’t pack up my desk just yet. Here’s why.

We’re surrounded by AI

Let’s be honest: this is nothing new. Artificial intelligence, machine learning and automation have been around for quite a while, and we’ve all been targeted by Facebook’s AI-applied targeted advertising and subject to Google AdWords’ AI-powered, automated bidding for years.

Your top picks on Netflix? AI technology fuels its recommendation engine. Apple’s personal assistant, Siri? She’s machine learning to better predict, understand and answer your questions. Google? Depends on AI to rank your search results.

But the machines haven’t taken over yet. Despite it trickling into everyday life, AI is still in its infancy. Instead of conjuring images of alien robots, we should really think of the technology as a baby Bicentennial Man in nappies – waiting for us to teach it.

AI is growing up fast

To be useful for content marketing, AI needs a mammoth amount of fresh, structured data.

Its power lies in its ability to analyse large data sets to reveal patterns and trends. Feed it enough high-quality data and it will be able to predict share prices or a human’s lifespan and, in some cases, even write content.

Natural language generation (NLG) is a type of AI software capable of producing coherent, readable text. NLG robo-journalists are already creating basic sports content and corporate earnings reports. But, as smart as it is, NLG isn’t truly independent – it needs very specific data sets and templates before it can write, and it can’t create anything genuinely new.

Still, that doesn’t mean we can’t use the technology. In the realm of content marketing, AI can gather, sort and make sense of oceans of data – something the industry is swimming in.

AI: Spotting trends, making predictions

Ask any marketer and they’ll tell you they’re ‘data driven’.

Sure, we’re data driven. We look at engagement metrics to tell us what’s working, and change things accordingly to make them work better and inform future decisions. But it’s generally retrospective.

A lot of what we do is still based on instinct. We still speak to real people. We still search online to understand what people are asking. We still study search volumes.

What we need is the ability to predict something before it needs to be changed. This is where the opportunity for AI is in content marketing right now.

Exciting stuff for a content marketer working in a media and data intelligence business. We’re already using our own AI to process seven million news items every day, at a rate of 234 stories per second.

With that much data, our software can make strong recommendations about what type of content we should be creating, and for whom. As it evolves (and learns), it should be able to spot trends and patterns early, informing communications strategies and helping businesses to maximise opportunity and minimise risk.

Humans and AI, living together

AI and predictive analytics will help content marketers understand who they should be talking to and what they should be saying, but it’s up to us to create the content.

AI relies on human data and intelligence to function and learn. At least for now, this is where its limitations lie.

Humans are still needed to create original work that connects with its audience at an emotional level. To completely replace a writer or content marketer, AI would need to have an opinion, think abstractly, be curious and show emotion.

So, while your inbox might be full of propaganda alluding to our impending cyberdoom, we’re not there yet.

However, we shouldn’t be naïve, as the way we work is being transformed. To stay in the game, we should spearhead the change rather than hiding in the corner.

I for one welcome working with our new robot overlords, and I urge you all to join me. As the machine said, “Come with me if you want to live.”

Disclaimer: This article was not written by a robot.

Paige Richardson, Isentia Strategy & Content

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The immediate challenge is not killer robots, its job replacement. If individuals are automated out of jobs, the future for society is bleak.

Computers can already take orders, fold clothes and even drive cars, but where to from here?

The robots are coming. Although often spoken of in future tense, the truth is machine learning is well and truly here. Without realising, consumers interact with ‘smart’ technology at almost every touch point; from robotic vacuums to facial recognition technology, artificial intelligence (AI) is helping to complete tasks faster, cheaper and – sometimes - more effectively than ever before.

In an economy that’s driven by speed and efficiency, it should come as no surprise that a computer’s ability to communicate at a trillion bits per second is favoured above the human capability of about 10 bits.

McKinsey recently reported that 40 per cent of work tasks can be automated using existing technology, prompting everyone from factory workers to lawyers and accountants to consider the threat of being replaced by robots as not just inevitable, but imminent.

For technologists, we are witnessing first-hand how this emerging field is transforming the companies we work for.

In my work at Isentia, we use machine learning to process seven million news items each day. Not long ago this was a task relegated performed solely by humans with the mind-numbing task of flipping through newspapers in search of stories that might relate to a client.

We have a duty to empower those around us to learn everything they can about what their job may evolve into in order to become the very best man-machine partner possible.

Today, machines trawl video, audio and digital content across over 5,500 new sites at a rate of 234 stories per second and present meaningful summaries to clients in real-time.

Whether a story breaks on Twitter and then spills across news platforms and onto television and radio, machine learning can track and analyse how a story evolves with 99 per cent accuracy.

While AI is revolutionising the way that we work, the impact is far greater for those in the tech industry. In our mission to develop software that can learn complex problems without needing to be taught how, the success of the AI industry ultimately comes down to technology professionals: our ability to automate, and the pace at which we expand the field of machine learning.

With an annual growth rate of 19.7 per cent percent (predicted to be worth $15.3 billion by 2019), it’s safe to say our foot is well and truly on the pedal. While this relies greatly on our technical capabilities, it is something that challenges many of us ethically: what set of values should AI be aligned with?

Two of the greatest technologists of our times, Elon Musk and Stephen Hawking, have spoken about both the potential benefit and the harm that an AI arms race could deliver. An eradication of disease is not unfathomable, but nor is a threat to humanity. They hold grave concerns as to whether or not robots can be controlled against misuse or malfunction.

While thought provoking, the immediate challenge is not killer robots, it’s job replacement. Employment may not seem like an ethical problem, but if individuals are automated out of jobs, the future for society is bleak. While the phrase ‘Thank God it’s Friday’ has forged its way into the 9-to-5 vernacular, for most people, jobs create a huge sense of personal and professional satisfaction… not to mention a means to pay bills.

An apocalypse might be somewhat melodramatic, however I do agree that it is important to consider just how closely we should merge biological and digital intelligence.

Computers can already take orders, fold clothes and even drive cars, but where to from here? It’s both exciting and terrifying. The last time we experienced a revolution like this was in the early 1900s when cars, telephones and the airplane all emerged at once.

Contrary to the hype, there lies an enormous opportunity for humans to work with artificial intelligence, not be replaced by it.

Make no mistake: at some level every job can be carried out by a robot. But there are certain jobs, particularly in technology, that require decision making, planning or coding software.

While computers do a brilliant job of executing well-defined activities - such as telling us the fastest route to get from home to work - it is safe to say that humans are an essential component of goal setting, interpreting results, humour, sarcasm and implementing common sense checks.

The most difficult jobs to automate are those that involve managing and developing people. While in this industry most of our jobs are safe (for now), we should heed the advice of Musk and Hawkings and protect those outside our field by proceeding with caution. How then to facilitate human and robots working together harmoniously without the workforce morphing into cyborgs? The secret is to not sail out farther we can row back.

As technologists, we also have a duty to empower those around us to learn everything they can about what their job may evolve into in order to become the very best man-machine partner possible. It's the best, and most ethical, way to prepare for the inevitable advent of AI.

First publish in CIO New Zealand

Andrea Walsh, CIO

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Blog
It’s time to slow down the AI arms race

Computers can already take orders, fold clothes and even drive cars, but where to from here?

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Every stakeholder relationship is different, and managing them effectively takes more than a one-size-fits-all approach.

From campaign planning to long-term engagement, having the right tools and strategy in place can make the difference between missed connections and meaningful impact.

This guide covers:

  • Identifying and understanding your key stakeholders
  • Mapping and modelling for influence and engagement
  • Equipping your team to maintain and grow strategic relationships

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Blog
The fundamentals of stakeholder strategy

A practical guide to tailored stakeholder management, offering strategies and tools to identify, map, and nurture relationships.

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Across the communications landscape, teams are being asked to do more with less, while staying aligned, responsive and compliant in the face of complex and often shifting stakeholder demands. In that environment, how we track, report and manage our relationships really matters.

In too many organisations, relationship management is still built around tools designed for customer sales. CRM systems, built for structured pipelines and linear user journeys, have long been the default for managing contact databases. They work well for sales and customer service functions. But for communications professionals managing journalists, political offices, internal leaders and external advocates, these tools often fall short.

Stakeholder relationships don’t follow a straight line. They change depending on context, shaped by policy shifts, public sentiment, media narratives or crisis response. A stakeholder may be supportive one week and critical the next. They often hold more than one role, and their influence doesn’t fit neatly into a funnel or metric.

Managing these relationships requires more than contact management. It requires context. The ability to see not just who you spoke to, but why, and what happened next. Communications teams need shared visibility across issues and departments. As reporting expectations grow, that information must be searchable, secure and aligned with wider organisational goals.

What’s often missing is infrastructure. Without the right systems, strategic relationship management becomes fragmented or reactive. Sometimes it becomes invisible altogether.

This is where Stakeholder Relationship Management (SRM) enters the conversation. Not as a new acronym, but as a different way of thinking about influence.

At Isentia, we’ve seen how a purpose-built SRM platform can help communications teams navigate complexity more confidently. Ours offers a secure, centralised space to log and track every interaction, whether it’s a media enquiry, a ministerial meeting, or a community update, and link it to your team’s broader communications activity.

The aim isn’t to automate relationships. It’s to make them easier to manage, measure and maintain. It’s about creating internal coordination before the external message goes out.

Because in today’s communications environment, stakeholder engagement is not just a support function. It is a strategic capability.

Interested in how other teams are managing their stakeholder relationships? Get in touch at nbt@isentia.com or submit an enquiry.

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Blog
SRM vs CRM: which is right for PR & Comms teams?

Across the communications landscape, teams are being asked to do more with less, while staying aligned, responsive and compliant in the face of complex and often shifting stakeholder demands. In that environment, how we track, report and manage our relationships really matters. In too many organisations, relationship management is still built around tools designed for […]

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