Through all of the froth and bubble around A.I in the headlines, it can be quite difficult to cut through the noise and answer a few simple questions: how big is this thing going to be, really? And should I leave it up to the major tech firms to deal with? Depending on who you believe, the answer to the first is usually somewhere in the ballpark of ‘big’, to ‘huge’, to ‘astronomical’. The answer to the second might depend on which salesman you’re talking to at the time. One thing I’m quite sure of is that no one knows for sure how large this opportunity is. Thomas Edison, arguably one of the most prolific inventors in the modern world, was confident Alternating Current (AC) would never catch on. Today, we struggle to imagine life without AC. Who could have known who was going to be right back when this argument was going on? A.I has the potential to have an event greater impact on our lives now, given the entrenched nature technology has in our lives.
In a recent research article put out by McKinsey and Company shows what the authors believe to be the potential distribution of A.I opportunities across 19 industries. Exhibit 5 may be the most relevant to an SME (closely followed by exhibit 4) as it shows the greatest opportunities to unlock value using A.I broken up into business functions with marketing and sales taking top spot, followed by supply chain and manufacturing.
You might be wondering how an SME can utilise A.I in these high value areas when the industry is supposedly pushing the boundaries on a daily basis. “Why would I get involved now when the technology might be out of date tomorrow?”. Good question, and my suggestion is that the appearance of AI as a Service (AIaaS) offerings by many startups as well as the major technology players is close to making this technology attainable by all businesses. The nature of these subscription services is such that you automatically have access to the latest updates as and when they are available. I have detailed some fascinating applications of A.I in sales, marketing, and supply chain below, and these are approaches that can be implemented in an SME with relative ease by a firm like Remi AI.
Approaches Available Today:
Most people are familiar with Uber’s surge pricing concept where drivers an incentivised to drive when demand is high by an increased fare. This concept can be applied to eCommerce with excellent success. The idea is that the A.I would track website traffic and lower prices to entice people to buy when traffic is low, and raise prices when traffic is high, all in real time. The advanced stage of this implementation is when you allow the A.I to predict the demand and alter the prices proactively. The demand for this function is growing and the team at Remi AI has implemented it with excellent results with several eCommerce clients to date.
My co-founder wrote an excellent blog post on A.I in inventory and so I won’t rehash his work in this post other than to say that the goals of good inventory management are to reduce dead stock (stock that is unable to be sold) and reduce stock outs (an inability to fill an order due to a lack of the required item on hand). Humans do a fantastic job of these tasks though as warehouse sizes grow, suppliers demand longer forward orders, and customers alter their demand with the wind, humans can only do so much. A.I can be brought into the mix in 2 stages:
1. Forecast demand using supervised learning: The idea here would be that humans could act on these forecasts with their ordering patterns. I will say that the data needs to be of high quality and as close to live as possible for this approach to be of use.
2. Allow a reinforcement learning (RL) agent to run your inventory operation: RL is a fascinating and advanced area of A.I where an A.I agent is allowed to act in an environment using pre-approved actions with a goal in mind, and it rewarded and punished depending on the result. Through this reward and punishment the A.I agent ‘learns’ which approach is best in different situations and so improves through time. This approach is close to complete inventory management automation and so is a large undertaking, and the potential savings are significant.
A.I in Paid Search and SEO
Most businesses these days have a website and will be familiar with what can be the mammoth task of digital marketing for your website. Many SMEs hire digital marketing firms to run this operation for them which is entirely understandable. A.I is shaking things up in this space, driving costs down and performance up and I have detailed 2 of the more interesting approaches below.
Paid search using RL: It just so happens that the paid search area is a perfect application for RL given that it is data heavy and the data quality is high. These days it is possible to run entire paid search campaigns using RL and the results that I have seen have improved on the incumbent by a considerable margin.
Intelligent Google Ads: Imagine that an A.I was able to read your entire website, followed by all of your competitor’s websites, decide on the most important keywords and craft Google ads around these keywords including all descriptions and titles without any input from a human other than to approve the ads if required. This isn’t too good to be true, is 100% possible, and could save SMEs thousands on SEO costs each month.
A.I as a Service (AIaaS):
This phenomenon has been building over the past several years with a goal of putting the most advanced A.I methods in the hands of non-technical users. The approaches described above are excellent in their domain, but the AIaaS offerings coming out at the moment allow users to build their own predictive models for multiple applications. A business owner may want to predict revenue in the coming months and assess whether the weather or stock market have any influence on these figures. A manufacturer may way to predict when their vehicles will break down and service them in a predictive rather than preventative model. Platforms allowing users to do both tasks using one service are available and SMEs should absolutely take note in my opinion.
The Road Ahead:
The approaches described above are those that I believe to be salient as well as realistic to SMEs. There is no doubt that the A.I opportunity is large and can be a daunting one for those without a billion dollar budget. My suggestion is to begin to educate yourself on the topic from some trusted sources (think journals and universities if you’re looking for any hard facts). I would then ask yourself whether there is any part of your business that generates surplus data, and where a prediction is made on this data by an employee or subcontractor. Chances are that this task could benefit from A.I, and that there is already a service on offer that you could utilise such as those described above. SMEs can certainly keep up with the latest A.I technology, and there is no better time to start (if you haven’t already) than right now.
Remi AI can provide each of the services listed and I would encourage anyone interested to reach out for a discussion on how these approaches may be applied to your business.