There’s plenty of stories around AI right now. Whether you prefer the term Deep Learning, Machine Learning, Artificial Intelligence, cognitive computing et al, you’ll be all too aware that your job is about to be taken over by an algorithm that has more ability to interpret learnt behavior, better than you ever could.
But before the drive for super efficiency creates this dystopian view of commerce let’s just think of what steps we need to take to get there and what barriers we need to overcome.
The revolution is currently being driven by excitable technologists under the guise of data scientist. However, like most things in corporate life, the majority adopters will only advocate investment when they see their competition
AI promises to drive out inefficient common tasks and replace them with highly informed learnt behavior using a combination of real time and historic data, that can interpret it into prescriptive actions. All very promising if you know what behaviors to look for, how to detect them and how to apply them. Enter the data scientist, the source of all AI wisdom. The analytical brain that can decipher code, recognize the patterns and apply them to create prescriptive tasks.
Begin with the end in mind
And here’s the problem. Typically AI projects run by data scientists do not start with a complete business view. They typically start with a finite business problem that needs solving. Reducing waste, Understanding traffic flow in order to improve efficiency – you get the idea. These style of projects quickly provide a return in the form of insight that the business is unable to act upon in a way that will have an ongoing affect on performance – The true benefit of AI projects. To this end, any AI project needs a business objective and total commitment from the business to take all findings seriously and, moreover, take the steps necessary to take the analytical insight to change operational behavior and working practice often ingrained by those to affected by it.
We’re currently undertaking a number of AI projects using various Deep Learning frameworks. This experience has highlighted the real need for business decision makers to be involved in measuring the success of these projects. Right from the start.
Until senior business decision makers understand the opportunity AI represents and puts up and sponsors the objectives, AI is destined for the IT vendors workbench and tech billionaires pet projects.
The human factor
AI projects often aim to replace the admin tasks with better decision making, based on solid evidence that cold hard data can bring. However, driver less cars are still far from a reality and people still trade on stocks and share. The immediate opportunity AI provides is for human beings to make informed decisions with evidence backed data behind them. Clearly the opportunity this world presents is far from the view of the world where humans have lost control by handing over decisions to a well informed algorithm. For now, the human race is safe. We will be better informed, better armed to adjust and change common behavior; So, until such time we are willing to place all trust in a system of working that will ensure our betterment, which will probably be never, given our nature to distrust everything.
The super efficient beige machine
Right now we are experiencing innovation at a level the human race has never seen before. Largely driven by the need to drive out costs and strive for ultimate efficiency, this new ‘super efficient’ form of capitalism promises to reduce costs and drive buying. But this brave new world can’t resolve all issues. Business still has to innovate and produce that flair of magic and creative desire that cannot be data driven. Human’s remain the creative spark that enable us to develop the obscure that, in turn, converts into new products, new markets, new ways of working.
You’re probably waiting for your competitors to announce how much value they’ve derived from their AI investment before you’re in a position to build a business case for investment. The reality Machine learning takes time to deliver results. It takes huge amounts of data to iron out anomalies and contradictions in order that insights can be reliable and trustworthy and implimented. This all takes time. So don’t wait to the competitions announcement – it will be too late for you. Start identifying your pain points and ask yourself “If I understood the problem better, I’ll be in a position to do something about it”. In essence that’s what AI does. Grab you’re head of customer services, if they’re good they’ll want to know exactly who their most important customers are just as they want to know what customers are taking up too much time. Insight of this nature can only serve you well in the future. But don’t wait start learning more about your organisation, your market and your custom ers now.
If you’re looking to take advantage of AI and Deep Learning Recarta can help. Our RecartaAI platform can give you a a POC environment with out the capital costs. To speak to a qualified consultant call us today on 0800 8007821.