Don’t get left behind in the AI race

AI is improving business performance across a wide range of industries, failing to grasp the opportunity leaves those who don’t at risk of being unable to compete in the future

Nothing is affecting more lives today than AI. Most people are aware of AI but far less understand its power or how AI-driven products are impacting lives. Every industry touched by AI develops new efficiencies or increases sales opportunities. Across most industries there are examples of companies that successfully apply AI and enjoy an advantage that quickly puts a distance between themselves and their competition.

Ocado, an online grocer, receives around 10,000 e-mails from customers every day. It replies to the most urgent ones first using AI to detect the prevailing sentiment in them. In the future its AI will route complaints to agents with expertise in the relevant field.

Private bank Credit Suisse have applied AI to enhance their electronic communication surveillance to make themselves more efficient at identifying fraudulent behaviour. Using Deep Learning they can better decipher the vast volume of unstructured data exchanged (emails, chat boxes and phone communications) between people and can more accurately focus on suspicious behaviour.

$600M INVESTMENT IN AI STARTUP

Ping An, a Chinese insurance company, uses AI to spot dishonesty. Customers apply for loans through its app and answer questions about their income and repayment plans by video. AI monitors their facial expressions to determine truthfulness and pick out which customers require further investigation.

Tech giant Alibaba recently made SenseTime Group the most richly valued AI startup ($3 billion) following their $600 million investment. If you’ve ever been snapped with a Chinese-made phone or visited China, it’s more than likely your face has been digitally crunched by the software the company has installed in over 100 million devices.

AI is being successfully applied everywhere. However, smaller companies often dismiss AI through fear of the costs involved. Others don’t understand how AI could apply to their business and wait for others to make the first move.

BETTER USE OF DATA

For data-rich businesses, AI offers the most efficient way to make the best use of it. The revelations about data usage on Facebook and its application through AI has shed some light about its potential uses. The public are now waking up to the value of their own data. For years people have been oblivious to what AI can extrapolate from a few likes on a social media platform. There’s been a collective gasp that Cambridge Analytica’s software knows you better than your work colleagues after just 10 ‘likes’.

That gives way to the shock with the revelation that after 300 ‘likes’ it knows you better than your spouse.

Many smaller businesses remain unconvinced about the benefits of leveraging data. However, data is now the world’s most important resource. The flow of data contributes more to world GDP than the flow of physical goods.

Amazon is perhaps the best example of successful data usage. In 2017 they accounted for 44% of the US e-commerce market (39% in 2016) by being better at using data than the competition.

Small businesses might dismiss the relevance of Amazon as an example because of the budget spent on developing their advantage. However, it should be remembered that it started less then 25 years ago as an online book seller working out of Jeff Bezos’ garage.

OPT FOR VALUE

If AI isn’t embraced, sticking with the past is a guarantee of being left behind. Instead of fearing the cost of AI implementation, a better approach is to gauge the best value solution for the budget available.

Creating an in-house solution gives a business the greatest chance of getting out ahead of the competition. However, given the cost of creating an in-house AI team most brokerages are going to look at two other possible solutions.

1. Identify an AI partner who can build a custom solution.

2. Use a turnkey solution.

Building on top of machine-learning-as-a-service (MLaaS) platforms from Google Cloud, Amazon or Microsoft is the starting point for most AI partnerships. These are integrated with their cloud solutions and offer common technical capabilities.

They enable companies that store their data with cloud providers to take advantage of built-in machine learning tools. This avoids the cost (and time) of building from scratch. However, your AI partner will still need to customise the solution and that requires them to fully understand your market and identify exploitable opportunities.

LEVERAGE DATA BETTER

AI plug-and-play solutions exist for businesses that want to better leverage data. Off-the-shelf AI can also streamline operations, cut costs, sync operations and help to deliver a better overall service.

Depending on the scope of your ambition there are AI vendors that specialise in CRM, Sales, Marketing and other common business functions like Telecoms. These solutions work out of the box or require a limited integration period.

The increasing impact of AI means the option of sticking with tried and trusted methods will soon be off the table. Watching and waiting for two or three years before establishing an AI strategy will only make it more difficult later.

Today’s businesses will face the same problem former retail giants are going through now with Amazon. Over time the e-commerce giant has become so rich and powerful that they are struggling to find the opportunities and resources to compete with Amazon.

Building an in-house AI team gives your business the opportunity to create a unique solution that can help it increase market share. If it creates a solution that sets a new benchmark for the industry it becomes sought after and opens up new, repeating revenue streams through licensing to others.

However, time and investment costs make this prohibitive for most smaller businesses and is only an option for companies with the biggest war chests.

The more cost-effective options involve a partnership with an AI developer or adapting existing AI solutions. Both offer advantages. The former leans towards the more ambitious and the later towards the business looking for an immediate return on their investment