This month Google’s Deepmind Artificial Intelligence (AI) application has beaten one of the world’s leading Go players, Lee Se-dol of South Korea, not really news that will excite the housing sector, but news nonetheless that it should take notice of.

Go, an ancient board game whereby players take turns in placing stones on a grid, is more complex than chess, when a player has typically 200 choices of moves compared to twenty in chess.

So why the interest? Well, according to DeepMind’s team there are more possible positions in Go than atoms in the universe, so the AI developed is incredibly effective and importantly it demonstrates how DeepMind is successfully responding to a changing environment and altering its behaviour and predictions with that of the circumstances of play around it.

This takes predictive analytics further and enables the ‘projections’ to change with the landscape around it. So what are the real world implications? Well software applications that can analyse live data and change its projections in line with the changing data will have huge implications for how organisations run and their bottom line.

All too often organisations are unable to see the changing landscape as they don’t have accurate and up to date information or the tools to analyse and present it. When the macro and micro environment change, if the leadership team know the details then often they would change the course of the organisation. As John Maynard Keynes famously once said, “When the facts change, I change my mind. What do you do, sir?”

AI is the next step beyond predictive and big data analytics when systems can monitor data and amend its output and projections along with changing data and its environment.

Big data analytics has a bright future, according to the CEBR, they estimate by 2020 it will deliver £220 billion in efficiency savings to the UK economy. So if big data analytics can deliver such mind boggling efficiencies what will AI do? It will create more informed and aligned organisations that have the ability to change their strategy in line with the environment around it, making it more successful, creating bigger savings and profits.

What would or could this mean for the housing sector? Without wanting to sound glib it would help banish the difficulties of the 1% rent cut in England and create organisations that have the finances to continue with social housing development.

In the short term however landlords should be harnessing the power of predictive and big data analytics that can begin delivering some much needed efficiencies today, whilst thinking about AI and the impact it could have on their organisations.

Why DeepMind’s Victory is Good News for Housing