The value of A.I in an SME, and what does it mean for me?

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.

So what?

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 “Why would I get involved now when the technology might be out of  date tomorrow?”.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:

Dynamic Pricing:

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.

Inventory Management:

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.

Eamonn Barrett


Remi AI

Stay tuned on the Remi AI blog as we build out the complete supply chain offering!

Or, if you're ready to start seeing the benefits of A.I-powered inventory management, start the journey here.
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Remi AI is an Artificial Intelligence Research Firm with offices in Sydney and San Francisco. We have delivered inventory and supply chain projects across FMCG, automotive, industrial and corporate supply and more.
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