A little box in the corner of the room that squawks at you when you ask it questions.
Online advertising that tries to learn your preferences.
Chatbots that try to be your best friend and solve problems for you.
Artificial intelligence and machine learning are becoming a bigger part of our daily lives. And despite communications being one of the more people-oriented professions, speculation has already begun about how clever algorithms could start to take hold in what we do.
Are jobs at risk? Will technology enable communications to become more effective and more measurable? What aspects of what we do will likely never become the preserve of machines?
These are relatively early days. Yet some of that speculation, and some of the data-driven services already starting to be applied to the communications mix, have hinted at how algorithms could become part and parcel of several aspects of our work.
No-one quite knows how this will shape up. But here are nine areas where artificial intelligence, and more immediately machine learning, may start to take hold in communications and PR:
- Listening: an obvious area perhaps, given the rise of voice-activated assistants like Amazon’s Alexa on the Echo, and Google’s OK Google, but the potential for machines to monitor conversation and enable communicators to tune in more closely to what audiences really say and think seems irresistible. It raises many moral questions of course, and huge swathes of data will need to be amassed. But the ability to listen harder, and to know rather than guess what audiences need and their reactions, is a huge area. And one where reducing guesswork can help us all
- Media intelligence: algorithms will simply make it easier to keep track of media needs, editorial content as it evolves, and how the focus of media titles is changing, as the frenzied evolution continues. The tools are improving all the time, and expect a lot of focus in this area to help automate some of the more thankless tasks of our industry
- Sentiment analysis: similarly, amassing big data and being able to analyse it in seconds will mean more and more content and conversation can be assessed and acted upon. And the sharper those tools get, the more accurate they should be, able to filter factors like sarcasm
- CRM/sales cycle intelligence: providing the data sets can be pooled and crunched effectively, the impact of communications persuasion and influence on sales cycles of varying length, and the involvement of influencers and advocates along the way, should all be mappable. The ability to manage communications around genuine and immediate needs, and at points where it’s most impactful to do so, should be realistic. Of course, human behaviour will always produce variables, but if the advances are welcome then it can address a whole heap of unwelcome attention, as the technology improves
- Predictive crisis management: “when will these companies ever learn” is a question levelled at many a reputational clanger by the public. Well, the tools for monitoring risk are getting better all the time despite the speed at which crises evolve, as covered in this *cough* best-seller a few years back. So the ability to analyse issues as they bubble to determine what may burst into a crisis, and even patterns of corporate behaviour that may lead to trouble, is far from far-fetched.
- Understanding emotions: again, behavioural patterns can be identified and better understood as data sets build and points of data entry increase. In particular, how individuals react to content – editorial they share or comment on, how long they linger, device or medium, and time of day are all factors that can be assessed individually already, but with more information we’ll be able to see clearer pictures of emotional reactions. They may not be foolproof, but they should be amongst the most powerful applications of AI for communication
- Closer brand relationships: ah, this has already got creatives excited, and probably a little bit concerned too. Machine learning applied to AI applications that can interact through voice, listening and type with human beings means brands may actually be able to build closer and more empathetic relationships with audiences, despite the dialogue being with machines. Certainly AI has the potential to improve customers ‘experiences’, so should have a knock-on effect on reputation
- Media ‘tuning’: data-driven intelligence has the capability to inform media planning mid-activation and steer media targeting, and even content development, quickly depending on how the audience reacts and media coverage a story editorially. Automatic and immediate media monitoring feeding agile planning, if you will
- General admin and organisation: like any profession, communications has its fair share of necessary evil time, the grunt work that needs to be done just to get the job done. Scheduling meetings, changing call times, sharing basic information. Automation being able to handle that may eliminate some of that human toil, but it could free us up for more important tasks (like, er, communication)
Will all of this happen? Perhaps, and not overnight, but the momentum is building.
If the task is currently too manual, or the prize of having the capability, then the algorithm is gonna get you (as Gloria Estefan did not say).
Will bots change our jobs? Yes, to a degree, and they’re already beginning to. Human factors will always be central and the data can’t do everything, but reduction of the guesswork alone is shaping up to be a giant step forward.