{"id":2251,"date":"2019-09-26T17:02:54","date_gmt":"2019-09-26T17:02:54","guid":{"rendered":"http:\/\/www.anaadi.net\/?p=2251"},"modified":"2023-05-05T12:16:10","modified_gmt":"2023-05-05T12:16:10","slug":"ai-and-the-future-of-pr","status":"publish","type":"post","link":"https:\/\/www.anaadi.net\/blog\/2019\/09\/26\/ai-and-the-future-of-pr\/","title":{"rendered":"AI and (the future of) PR"},"content":{"rendered":"\n

Earlier this year I have been interviewed by Inpuncto, the newsletter of PilotProjekt<\/a>, about corporate communications and AI. This was right before the results of #PR2025<\/a> were released and after my contribution to AMEC’s Measurement Month<\/a> on measuring VR (virtual reality) and AR (augmented reality) for PR<\/a>. <\/p>\n\n\n\n

The interview has been translated in German. The English version is below.<\/p>\n\n\n\n

INPUNCTO: According to our research results to\ndate, the use of AI in corporate communication concentrates on the areas of\nmarketing as well as product and sales PR. Other fields of PR such as media\nrelations, human relations, public affairs, crisis PR or corporate identity do\nnot (yet) seem to be the focus. Does this statement apply, or do you have any\nhints or examples for the use of AI in these fields?<\/em><\/strong><\/p>\n\n\n\n

Ana Adi<\/strong>: Marketing and advertising are more keen to use AI or better said Machine Learning Systems and talk about it. It helps position themselves as innovative, cool, groundbreaking and different. That is mainly because they do have a B2C outlook. With PR\/corporate communication having multiple stakeholders to consider, the incorporation and use of AI\/machine learning depends on the relevant stakeholders. <\/p>\n\n\n\n

Moreover, machine learning (big data aggregation and analysis, warning systems) are certainly being used by organizations, especially by big organizations (big data means also bigger budgets) but as they are there to provide them with a business advantage, organizations will be less likely to publicly admit to using them. <\/p>\n\n\n\n

Think of banking, health care, politics. Their business success and\nlicence to operate are highly dependent on such discourses which is why such\norganizations would be prone to embedding extensive monitoring dashboards. This\nis insight, data driven insight and it is almost live, instant. You would not\nbe going about to tell your competitors that you are using that tool. Machine\nlearning that is supervised is being used already, more than probably people\nwill admit to. <\/p>\n\n\n\n

INPUNCTO: Do you know of PR campaigns that have\nbeen designed and implemented with the help of AI? If so, can you give examples\nand evaluate their success<\/em><\/strong><\/p>\n\n\n\n

Ana Adi<\/strong>: I do not think you can make that\nclear distinction, that very clear cut between advertising and PR in that\ncontext anymore. Let\u00c2\u00b4s take an example. One of the most recent examples that we\nhave seen is Lexus, using IBM Watson and a team of creative people. IBM Watson\nserved to write a script for an advertising spot and a very extensive team of\ncreative people to bring that script to life. The output of this effort is an\nad, so something that is aimed at driving sales, if you take the very strict\ndefinition of advertising. When watching the video as a potential car buyer you\nwould not know it has been scripted by IBM Watson. But you and I know about it,\nand that is PR work: all the actors involved and featured in the project spoke\nabout their collaboration in order to position themselves as innovative. This\nis a reputational dimension.  <\/p>\n\n\n\n

Most of the materials produced (and the coverage thereof) portray them\nas innovators, risk takers, creatives being on top of the curve; all that is\nPR. Equally,  if you look at the output\nas a result of the coverage and discussions in online forums about Lexus\u00e2\u20ac™ use\nof AI, this is not happening in the consumer driven areas (your regular\nYouTube, Facebook and the like) and most certainly is not about \u00e2\u20ac\u0153Cool. This ad\nmakes me wanna buy a Lexus\u00e2\u20ac\u009d. The discussion about Lexus\u00e2\u20ac™ use of Ai takes place\nin specialist forums, groups of communicators and creatives. That is PR.<\/p>\n\n\n\n

Another example is AP. They have been using machine learning to write\nsport articles and financial reports for quite some time. We are thus talking\nabout AP using AI. But who do you think was telling us that story? It was not\nthe journalist or the IT person! It was a person from the communication\ndepartment who highlighted AP\u00e2\u20ac™s innovation. That means AP is at the top of the\ncurve. It\u00c2\u00b4s again a case of reputation and positive awareness. It is about positioning\nAP in peoples\u00e2\u20ac™ minds as an organization that is not afraid to explore, and an\norganization therefore worthy to collaborate with. This emphasis on innovation\nand exploration has an additional objective: citizenship. AP is contributing to\nthe teaching of the society. <\/p>\n\n\n\n

To sum up, businesses in organizations will embrace AI in an area that\nwill provide them with a business and reputational benefit, that will support\ntheir core activity. But the communication of that embracing that technology is\ndone and mediated by the communication department.<\/p>\n\n\n\n

INPUNCTO: How does AI change corporate\ncommunication and PR in particular? Are they getting better or more effective?  <\/em><\/strong><\/p>\n\n\n\n

Ana Adi<\/strong>: There are two elements. I think it\nis very important to go back and define AI. I more like to use the term machine\nlearning more. AI is more in line with Hollywood movies, of sentient machines.\nBut we are not there yet. We are talking about tasks that are handling a lot of\nData. ML is not a scary thing. It is about analysis, planning and prediction.\nSome of those systems work unsupervised, a lot more worked supervised. <\/p>\n\n\n\n

Machine Learning has the potential of improving someone\u00e2\u20ac™s job. Provided\nthat they deal with groups of stakeholders and with environments that are complex.\nIf I am working for a small shop in the corner of the street, I might not\nnecessarily need to be worrying about machine learning because truly the\naudience and the people that I care for are not that far away. But if I work\nfor a bigger organization, machine learning might be useful in various ways. It\nwould be a great research and insight resource. If an organization is big\nenough then machine learning, understood in a way of either aggregation\ncollection or analysis of Data, can only support communication professionals in\ngiving them more specific but also more contextual insight into various\nstakeholders. <\/p>\n\n\n\n

The challenge in this case is that communicators need to get their head\naround accepting that communication could not only planned but also made\nspecific to different stakeholders.<\/p>\n\n\n\n

PR is either seen as an art in which case is perceived as something\nintuitive, or at the opposite end, as persuasive communication in which case  the associations with manipulation, spin,\nevil are not too far. The fact is that all organizations would want to persuade\nstakeholders to support them because that would make business better and bring\nincreasing loyalty and revenue. But that doesn\u00e2\u20ac™t mean they go about it without\nany consideration of the others they engage with.  <\/p>\n\n\n\n

On the contrary, relationship building requires communication and it implicitly\ninvolves persuasion. Persuasion requires listening and  understanding of the interlocutor. <\/p>\n\n\n\n

It is here that technology can help. PR is there to support\norganizations to understand the demands of their multitude of stakeholders. And\nit is time to make it obvious that some demands are incompatible and therefore\ncannot be addressed either values-wise, ethically or financially. Technology\ncan help provide these insights. And that is a good thing.<\/p>\n\n\n\n

Communicators need to stop fearing that technology is either going to\ntake over their work or is going to make them obsolete. Even if technology can\ntake over about 15 or 20 per cent of the work (remember data gathering,\nplanning, automating tasks) that means that there is still a lot of\ninterpretation left for communicators to do, a lot of analysis, a lot of\nputting insights into context.<\/p>\n\n\n\n

If you are of the opinion that machine learning\n increases the quality of corporate\ncommunication, is it a competition-relevant factor that provides considerable\nadvantages for companies with a stronger budget?<\/em><\/strong><\/p>\n\n\n\n

Ana Adi<\/strong>: Potentially yes. It helps to listen,\nunderstand and then relay what various stakeholders expect from (and how are\nimpacted and how they can impact and) organizations. The more successful, the\nclearer the guidelines from the communication department will be, the more\ntailored the messages coming from an organization to particular stakeholders.\nThat would have a particularly positive influence on the organization. For big\nbusiness as for politics, it makes sense to understand the variances within the\nstakeholder group, to understand the supporters, distractors, time bombs and so\non, and communicate with them in a way that bring the organization closer to them\nin a collaborative manner. <\/p>\n\n\n\n

If you have a good monitoring system that you can pick up information\nthat is sensitive (changes in public discourse and mood) it would be useful to\nbe able to address it. An organization would be monitoring various influencers as\nwell. As a communicator it is very useful to know what they are writing about\nand also have the context in which they are writing (so not only limited to the\norganization). It is the context that allows communicators to engage with them\nand see what whether and how collaborations are possible.<\/p>\n\n\n\n

The more you know how to ask for Data (clustering, classifying,\ncombining), the better and the easier it is to work with Data. It\u00e2\u20ac™s almost like\nplaying with Lego blocks: understanding and knowing what data elements are\navailable, one can create a different story at different times with a different\ntonality which would resonate differently with different stakeholders. This, in\nthe long run, can help organizations. <\/p>\n\n\n\n

Let\u00e2\u20ac™s also speak about readability and comprehensibility of texts, so how\nquickly you can one read a text and how easy it is to grasp its content.as\nthese are also elements prone to machine learning. <\/p>\n\n\n\n

A simple example: The PR department wants to write a digital story on a\ngiven topic. So an employee writes the text. Through such automated  an analysis, the text is then examined for\nits readability and comprehensibility before it is published. Are the sentences\ntoo long or the words too complicated? Then they can be improved accordingly. Once\nthe number of texts optimized in such a way is large enough, the algorithm\ncould be then trained to make suggestions for changes: Shorten this sentence,\nreplace this word with a synonym, write this passage more understandable. This sort\nof technology already exists but it is, to my knowledge, used little by\ncommunicators. It has however great potential to improve the work of\ncommunicators. Of course, this is only part of the work. The communicators\nneeds to also ensure that they track the impact of these texts (whether\ncompletion of reading, aided\/unaided recall, understanding of the message).<\/p>\n\n\n\n

INPUNCTO: Machine learning is being used with\nincreasing success in investment, tax and legal consulting, and deep learning\nmethods are also already showing considerable success in diagnostics. Is it\nonly a matter of time before a virtual PR assistant becomes the most important\nor influential “conversation partner” of a company’s chief\ncommunicator?<\/em><\/strong><\/p>\n\n\n\n

Ana Adi<\/strong>: There are already virtual\nassistants like Alexa, Siri and Google. However, they still solve quite simple\ntasks at the moment. What a PR department needs is a technology that could\nhandle more complex input. Companies, for example, are still very weak at using\nthe data they sit on. If I remember correctly, a recent study pointed out that\nperhaps only about 10 percent of a company’s communicative output is based on\nstories told by employees in the communications department. That means there is\nanother 90 percent of data in the company, in various forms (from meeting notes\nto reports, all of them available somewhere) that are not used in any way. So\nit’s very difficult for the communicators to find out in time what stories are\nlying dormant in the company, which have a high information value and a high\nutility value in order to be able to prepare and communicate them promptly. A\nsolution where information would be flagged up at an early stage would be\nuseful. Provided it has the necessary parameters to recognize which\ninformation, which story is interesting and can be of use to the company. But\nfor such a system to work, one needs to first know what and how to supply it\nand how to classify the information. We\u00e2\u20ac™re speaking here of taxonomies, but\nbuilt into data design and not just as an afterthought. <\/p>\n\n\n\n

A virtual PR assistant does not yet exist. The technology still lacks a\nlevel of interpretation and context reference. There is no doubt that machine\nlearning can be used to relieve communicators of many routine tasks. But beyond\nthat, the current state of the art cannot yet achieve anything. Human\ncommunicators will not be to be replaced soon.<\/p>\n\n\n\n

INPUNCTO: How will or must the job profile of\ncorporate communicators change in the near future? Will they also have to be IT\nand data experts in the future?<\/em><\/strong><\/p>\n\n\n\n

Ana Adi<\/strong>: It is interesting that you ask\nthat. I am currently running a study called PR2025. It is a Delphi method study\nwhose aim is to identify the trends, competences and solutions that\ncommunicators should consider in the mid-term in order to maintain their\nrelevance and confidence in the profession and the future. One of the questions\ncommunicators are asked refers to the technological competence that\ncommunicators should have, considering that technology is playing an\nincreasingly important role in our daily life. Some of the responses from the\n69 participants include<\/p>\n\n\n\n