At birth, we humans are helpless. We spend about a year unable to walk, about two more before we can articulate full thoughts, and many more years unable to fend for ourselves. We are totally dependent on those around us for our survival. Now compare this to many other mammals. Dolphins, for instance, are born swimming; giraffes learn to stand within hours; a baby zebra can run within forty-five minutes of birth.

Across the animal kingdom, our cousins are strikingly independent soon after they’re born. On the face of it, that seems like a great advantage for other species – but in fact it signifies a limitation. Baby animals develop quickly because their brains are wiring up according to a largely pre-programmed routine. But that preparedness trades off with flexibility.

In contrast, humans can thrive in many different environments, from the frozen tundra to the high mountains to bustling urban centres. This is possible because the human brain is born remarkably unfinished. Instead of arriving with everything wired up a human brain allows itself to be shaped by the details of life experience.

Now imagine a technology like Artificial Intelligence (AI) that uses an associative data index that shapes itself by the connections that exists in the data. Instead of arriving with everything wired up by a developer for the pre-canned business questions, it knows the connections in the data and allows users to explore the data from any directions and perspectives based on their intuition. This would provide companies with huge flexibility and advantage because every day they have a new business question, and with the “livewired” data, they can explore it and gain unexpected insights.

This new breed of AI is what we call ‘augmented intelligence.’ Essentially this means placing human intuition in the middle of data analytics and advanced algorithms. Here are three considerations for businesses bringing humans and AI together:

Embrace human brain power with cognitive computing

By investing in cognitive computing platforms, businesses can look to extract contextual information as humans can, adapting as requirements and targets change. Unlike fixed algorithms, cognitive computing platforms can resolve ambiguity and tolerate unpredictability, using probability to support decisions even with little representative data.

Although such technology is still evolving and has a long way to go before mimicking the human brain, human attributes are being woven into analytics platforms themselves to support effective decision making.

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Fuel AI innovations with associative data

Accessing and associating all the data will be the key enabler as AI comes of age. There are vast amounts of enterprise data in various organisational silos as well as public domain data sources.

To enable a holistic view of a complex problem, making connections between these data sets is critical, from which new AI-driven insights can be identified. Essentially, if the analytics technology does not allow businesses to get the full story from their data, building AI around it will only make the problem more evident.

Ensure data is trusted through data governance

With vast amounts of data coming from multiple disparate systems, an effective data governance strategy also becomes important for AI to produce trustworthy insights. Data governance offers a simple and direct way to ensure that right data is used to generate insights, but also identifies data errors and quickly flags and resolves those errors to help maintain the organisation’s confidence on data and ultimately on the insights generated.

To take this confidence one step further, a data catalog integrated with data governance empowers an organisation with quick and efficient insight discovery, so data users spend less time searching for the trusted data they need to feed into AI.

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Putting humans at the centre

Despite the key role that automation and advanced algorithms must play in data analytics, the ideal model will always put humans at the centre.

Afterall, we humans bring awareness, perception and ultimately decision making. That’s why rather than replacing business intelligence tools or teams, augmenting users will expand adoption by helping them become more data literate and allowing them to uncover insights in an easier and more ‘governed’ manner.

Elif Tutuk, Senior Director of Research at Qlik