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From GenAI to ‘Real AI’: why comms needs to care about data

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by Silvia Cambie:

Artificial intelligence is nothing new. It has been around since the 1950s when computer scientist John McCarthy coined the term.

In the past ten years, thanks to big data, Cloud computing and mobile devices, AI has been able to go mainstream and enter our daily lives.

Of those three elements, data is the one I believe communicators should focus on.

It hasn’t happened yet.

Since the rise of ChatGPT in late 2022, the comms profession has been busy concentrating on the content creation part of AI, which includes producing text, images, videos.  The curation part that enables applications to learn from data and extract insight that can be used for decision making has been forgotten.

This is both regrettable and dangerous. I believe a familiarity with data and how to apply AI to business challenges is what the comms profession has been desperately looking for.

You will agree that, in the past few years, comms roles have been progressively stripped of their strategic relevance and gravitas. Communicators are increasingly seen as mere tactical resources in charge of operational tasks like organising events, updating web content or producing newsletters.

According to a recent Weber Shandwick study, only 17% of CEOs believe their communication and public affairs teams are well prepared to navigate fast-moving economic, geopolitical, and cultural shifts.

Seventy per cent of executives expect greater instability this year, but many lack confidence in their comms teams’ ability to provide effective guidance.

A capacity to understand the strategic importance of data and how AI can make the future more predictable is what could help us gain back our executives’ trust.

Curation AI, by being probabilistic, helps predict how audiences react. It gives us the ability to understand behaviours by applying sentiment analysis to data, like for example to helpdesk conversations.

Traditionally, a large part of communicators’ time has been spent on measurement, which is often based on gut feeling. A knowledge of analytics and AI would enable us to measure in a more scientific data-driven way.

And the experience of measuring with AI would help us prove our strategic value to execs. Also, it is a transferable skill. It’s a mindset that combines data and AI as a way to get insight from the business, predict trends and patters and find early solutions to problems.

Equipped with this experience, communicators can become part of the AI centres of excellence (CoEs) that companies are currently setting up. Organisations use the CoEs to coordinate and guide the proofs of concept (POCs) their business units are conducting for all types of use cases, from areas like health & safety to knowledge management to carbon reduction.

I believe communicators would play a valuable role and contribute much more than their  measurement experience. Here is how we could help AI CoEs succeed:

  • In order to be able to scale those POCs, companies need to address employees’ reluctance to AI and take away the fear. Communicators know how to strike the right tone. We know how to read the current sentiment and position the messaging in a non-threatening way that lands.
  • Any POC that requires buy-in from users and testers is reliant on solid feedback and input. Communicators know how to mobilize feedback. We know the ‘internal influencers’ who can tap into their circles of contacts and get employees to contribute insight in the form of ideas, evaluations and perspectives. Through us, the CoE would acquire a powerful network of contacts and a way to get through to them.
  • In my experience, every successful AI upskilling program needs a strong peer-to-peer learning component. It is only by getting employees to showcase their AI projects to colleagues across units and geos that we can lower the entry barrier and alleviate anxiety. Being trained by peers makes AI more accessible to reluctant employees who feel it is too steep a learning curve or too remote from their day-to-day job. This is another area where communicators’ internal networks come in handy. We know how to spot people involved in AI projects across the company. We know how to convince them to volunteer their time. We can coach them, help them tell their AI story and turn it into learning content.

Communicators without an IT background often think data is not for them. They believe they can only support but not actively contribute to their companies’ AI plans. This is just another way how comms has been underestimated. Let’s step up and embrace curation AI.

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Silvia Cambie is an accomplished professional who works at the crossroads of communication and technology. A former business journalist, Silvia’s background spans PR, corporate affairs, enterprise social networking and internal comms. Her experience in tech includes digital transformation, Cloud, AI and change management. She is a #WeLeadComms honouree and a published author.

Written by: Editor

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