In the next five years, media will be transformed by AI. AI will probably touch all aspects of the media value chain. We’re not at the beginning of this analytics revolution - we are at the end of the beginning, and the middle is going to be marked by widespread adoption of AI technologies across the foundations of the business.
The end of the beginning looked like this:
AI has been proven to change how audiences and content interact.
- Audiences are optimized using AI on digital marketing platforms
- Website visits are personalized by AI
- Recommendation engines with unsupervised learning are so ubiquitous that consumers expect smart recommendations on content
- And conversational devices like Alexa and Google Home are becoming the leading portal to audio content
A major characteristic of AI in the beginning phase has been that it was dominated by big digital brands - Netflix, Google, Apple, Microsoft, Amazon etc. We expect that to change.
The middle stage: We will see AI at Scale for Every Media Brand
The middle phase we are embarking on is driven by a confluence of key trends:
- AI economics radically change the value proposition
- Cloud architecture now delivers AI on demand
- Analytical pipelines and real-time data become easier to orchestrate
These trends lead AI technology to go from hypothetical to practical and from trial to scale.
We are seeing AI move from behind the scenes to changing how the media business creates and recreates content. The goal creating customized content at scale will become the norm. There are use cases, such as NBA teams using AI to create personalized fan-mail and european media companies personalize variations of articles that are intriguing prototypes that can allow writers to scale their reach.
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We are also seeing ad sales optimize by leveraging AI to manufacture new data sets from dark data, enhancing lead scoring and using that to reprioritize contact strategies. That trend is expected to grow quickly since Global SMB ad sales is coming into itself now as platform players grow their footprint. Local media will have to respond.
The consumer side will probably adopt AI in even more depth. For example, we see The Subscriber Journey being optimized at every touchpoint from acquisition of new subscribers, with AI driving hyper-targeted segments and personalized conversations. Every customer touchpoint will become smarter, more effective, and more efficient.
These capabilities are now more accessible than ever and available to the biggest and smallest competitors. And where previous automations like IVRs often drove savings at the cost of customer satisfaction, AI because linked with interactive interfaces, personalization and self-learning optimization can save money while delivering a better customer experience.
Better customer experiences linked to more efficient channel will drive and explosion of AI projects that demand more AI talent to support them.
The End Phase: Every Platform will have changed
AI will become boring, not through repetition but because it will be what we expect. It happens with every urgent technology. Think about smartphones, laptops, IVR’s, moveable print, and indoor plumbing. AI will be have a stake in everything. The next phase will see rapid change and adoption. Then it will all be invisible – except when it breaks or doesn’t work right.
And then AI will be boring.
But what will not be boring will be the growth of new types of jobs and demand for new skills. We need the talent to understand customer’s intentions to work with teams that have the talent to create custom digital treatments enabled by Machine Learning engineers to be able to harness data into a conversational dialog.
And that is what makes AI exciting.
For more content like this, don’t miss the next Data Science Salon in LA, on November 7 2019.