AI — 6 questions you should ask before you buy
We are getting increasingly scared about the pace of technology change and how that will shape the future world we inhabit. Back in 1957 it would have been much easier to predict what the world might look like in 1967 than it is for us today to predict what it will be like in 2027. A vision for 2057 would seem simply impossible to comprehend. Ray Kurzweil is a futurologist I suggest you take a look at if you want to explore predictions further!
To lay any fears to rest, the development of ‘Real AI’, where an artificial consciousness exists, and machines can modify actions and behaviour based on self-awareness of their environment, remains a challenge for future generations. ‘Narrow AI’ is where we are today. The difference can be explained as creating a machine that can play Chess versus creating one that would choose to invent a game like Chess just because it could.
After working for many years to cut through the hype of speech analytics, I find myself battling similar challenges with AI. Google’s AlphaGo model beats Grand Masters, and the IBM Watson team do a great job of selling a vision. Turning that into the practical, benefit-led applications of the technology for businesses today is the challenge.
I know we see some high profile Narrow AI applications from self-driving cars to food monitoring fridges and medical imaging diagnostics. Customer operations should be considering the potential of developing chatbots or better predictive solutions for churn or resource forecasting, for example. So how do you start?
Google, Amazon and Microsoft now provide easy, free access to the comprehensive cloud-based tools and essential processing power to develop Narrow AI applications.
Many AI startups have taken advantage of this in recent years, and there are some established providers in the chatbot space who you can turn to for solutions. But this brings me back to my gripe with the hype. Whether it’s chatbots or predictive models, are you set up for success? Like all technology-enabled change, the same elements apply. Here are six questions that you should ask yourself, or AI partner, before investing in AI:
1. Is there a clear business problem to solve?
2. Would the AI approach be the best to address it?
3. How does it fit into and improve the customer journey?
4. How does it change our operational capabilities, such as skills needed by frontline staff?
5. How do we manage the business change?
6. How do we measure success against the business objectives (not just the quality of the model)?
Humanotics is working with Mazaru to help businesses build AIs that are valuable resources for organisations, customers and staff.
The six questions are part of our “AI Ready” assessment that helps service operations make better business cases for AI by choosing the best applications and thoroughly assessing the impact. If you’d like to know more about how we can help you better understand what AI can really do for you now — and in the future — get in touch.