Ready for the artificial intelligence advance?

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My in-box is filling up with invitations to analytics and research conferences. What always jumps out at these events is the range of approaches – from familiar analytics based on segmentation and econometric modelling to new thinking and the next big bets. Keeping abreast of advancements in analytics is an important part of my job and, right now, we see an interesting industry dynamic on show at these events. The noise and activity around larger data sets and applying cognitive research solutions is growing. At the heart of this is the progress of artificial intelligence (AI).

What really excites me about AI is that, for some time, it has felt like a distant, complex science, but now there is an opportunity for us to use it at scale. On a personal level, that means understanding its value to our industry and how to bring to life these analytical approaches in my day-to-day work. This is an opportunity to learn, and the increase in AI papers being presented at conferences is one way to do that.

I am sure I am not the only one in our industry who is motivated, but also challenged, by how technical this area appears to be and how to bring it to life. So how will AI develop within our industry?

The role and value new data approaches bring to an organisation, and how big data sits alongside traditional consumer-based market research, is a regular debate when research budgets are being allocated. In the near term, marketing research based on direct questioning of consumers will not go away, but it is now more likely to be superseded by new, more complex data drawn from different sets of observable people-based data.

When we link this consumer data to other meta data, we will increase our ability to connect attitudes to the outcome for brands and services through key performance measures such as sales and loyalty. Predictive research approaches, such as AI, are founded on these evolving data sets.

To make AI the norm, organisations will need to adapt to changes in this data provision. What is pleasing to see is that the technical foundations relating to data and storage are falling into place. Hosting these growing data sets at scale is a prerequisite and access to ‘storage space’ is more manageable than ever before. Being able to activate against the full potential of AI will mean shifting from traditional research time-frames. This will require insight and technology teams to create the foundations for faster sharing and recommendations.

It is against this backdrop that AI will begin to make a big difference – as the multiple factors affecting consumer behaviour are brought together in the same data sets. AI is not new, but the environment we all work in has changed. As we close out the decade, we will see an acceleration in the use of AI.

So is advancing AI a reality for us all in the research world? Absolutely, and our challenge is having the right skill sets in place. It will fall to analytic organisations to adopt AI through demystifying the approach, building trust and reinforcing the value it brings to organisations. I, for one, look forward to building my knowledge and continuing to develop the capability of my team to make the artificial a reality.