Digitalize or Die

We learned in the internet era that:

Shopping Mall + Website ≠ internet company

Even if a shopping mall built a website and sold things on a website, that by itself did not turn the shopping mall into a true internet company. What defines a true internet company is: Have you organized your company to do the things that the internet lets you do really well?

Over the past decade or so, a constant topic which has been on the top of the mind of many executives, business folks and even politicians for that regard is artificial intelligence or AI. The sharp decrease in the price of computational power, as well as the exponential increase of generated data, are making it possible for data scientists to produce excellent results on their complex learning algorithms. Here are some statistics to prove the above statements:

• Microsoft, Amazon, and Google offer almost cost-free data storage for implementing machine learning models. One can start with less than $100 per hour using the most-advanced hosting instances.
• Tesla is one of the first car companies to add self-driving capability in four-wheelers.
• Responsible adoption of AI will drive down around 69% of managers’ daily workflow, as per the latest report by Gartner.
•  AI-adoption will allow companies to become more diverse with, as it makes work more accessible for the disabled, said the report titled “Predicts 2020: AI and the Future of Work”.
• According to a New York Times article, China has stated that it aims to create a domestic AI market of 1 trillion Renminbi ($150 billion) and become a world-leading AI center by 2030.

It is not a secret to anyone that artificial intelligence and its subfields - machine learning, deep learning, and reinforcement learning will have a significant impact on individuals and corporations. Still, many questions are left unanswered:

• When are we going to see this massive adoption?
• How can I (individual or organization) participate in this future?

In this article, I will focus on how any organization, company, or institution can start adopting artificial intelligence and what are the first steps they can take. There is a big belief in the industry that the true explosion of AI will happen once companies start adopting these technologies to make their processes more efficient, reduce the cost of operation and create opportunities for new products.

Why is AI adoption not yet noticeable?

In 2018, McKinsey & Company conducted a survey of several thousand executive leaders. The results of it are as follows:

• Approximately 50% say their companies have embedded at least one AI capability in their business processes.
• Approximately 30% say they are piloting an AI capability.
• Approximately 21% say they have embedded AI in several parts of the business.
• Approximately 3% say they have integrated AI across their full enterprise workflows.

These results show that many organizations are willing to improve or even transform their processes with AI, but the rate of adoption is still slow. The top 3 challenges of adoption cited most often by executives are the following:

1. Lacking clear AI strategy which outlines the benefits of such adoption. Companies want to be able to understand what AI can bring to them and how impactful such implementation can be.
2. Finding AI talent is a huge obstacle for many enterprises. According to a New York Times report, fewer than 10,000 people in the entire world possess the necessary skills to tackle serious AI problems.
3. Low commitment to AI from the company's leaders. That leads to fewer investments in piloting projects, a short runway of these pilots, and eventually, the results are insignificant or non-existent.

In my opinion, it is just a matter of time for these obstacles to be overcome and a rapid adoption rate to take place. Many people and organizations are working hard on the above three challenges. For instance, the well-known AI pioneer Andrew Ng has built deeplearning.ai with the aim to educate people around the globe in the field of artificial intelligence and deep learning.

Nevertheless, companies themselves need to understand the influence of artificial intelligence techniques on their processes and act quickly if they want to stay relevant in the new age of automation.

Which area of your organization should you focus first?

Finding a specific area of focus is a rather complicated task and may take some time before one can make a final decision. I will try to give an initial direction to guide you towards your company's full AI transformation.

Artificial intelligence is a relatively old field that has been studied for more than 50 years. However, it was not so long ago when for the first time real-life practical applications have been found for long-lived AI research. It has finally come time for machine learning and deep learning to justify the investments and transform industries. Since this transformation had started 5-8 years ago, there are many characteristics yet to be understood. For example, it is challenging to accurately estimate the return on investment for every single AI technique. That makes it harder to convince senior management to allocate resources into AI development. Even if you possess the resources, you need to decide where to assign them.

Based on the state of your organization, you might want to choose to pilot an AI technique that improves an internal process, making it more efficient and cost-effective. On the other hand, you may want to focus on transforming an already established system that deals with your customer. The latter requires special attention to perfection since bad performance can lead to losing customers.

Andrew Ng once famously stated that "artificial intelligence is the new electricity". It will empower every organization as well as so many different aspects of human life. Your role as an executive is to begin transforming your organization, starting one business unit at a time. Following Andrew Ng's advice mentioned in his new report "AI Transformation Playbook", your first AI pilots should possess these characteristics:

• It is more important for your first few AI projects to succeed rather than be the most valuable AI projects. They should be meaningful enough so that the initial successes will help your company gain familiarity with AI and also convince others in the company to invest in further AI projects; they should not be so small that others would consider it trivial. The important thing is to get the flywheel spinning so that your AI team can gain momentum.
• It should ideally be possible for a new or external AI team (which may not have in-depth domain knowledge about your business) to partner with your internal teams (which have in-depth domain knowledge) and build AI solutions that start showing traction within 6-12 months.
• The project should be technically feasible. Too many companies are still starting projects that are impossible using today’s AI technology.
• Have a clearly defined and measurable objective that creates business value.

Once you have several successful projects in place, the company becomes willing to provide more resources and accept the AI transformation at the most crucial business units (ones bringing the most revenue).

How to run your organization's AI transformation strategy?

Having a conviction and an idea for an AI pilot is not enough - you will need a strategy to run your projects effectively. My observations have led me to 3 ways of how you can take your first actionable steps:

1. Subscribe to a full end-to-end solution provided by an external source.
2. Hire an agency to establish your AI foundation.

Build AI solutions using third-party providers.

Let's say your company is in the telecom sector and you want to automate the calls happening on a daily basis with your customers. You can hire a company that provides an end-to-end solution of handling calls, responding to requests, recording, and analyzing the information.

This approach is useful in case you want to automate only specific business units. If you are planning to empower your whole organization with AI, having external providers may cost you a fortune. Example organizations are:

• SenseTime (China) - facial recognition technology, used for video surveillance, credit card verification, security systems, and more.
• SoundHound (USA) - voice-enabled and conversational technology, used for taking the interactions between customers and brands on the next level.
• Element AI (Canada) - delivers AI software products that augment decisions to make your business stronger, safer, and more agile. Focus industries: banking & wealth management, capital markets, insurance, manufacturing, retail, transportation, and logistics. Element AI does not offer one single solution but instead provides a set of products accommodating your organization's needs.

Hire an agency to establish your AI foundation

If you want to transform your organization with the power of artificial intelligence, one should take on the challenge of building an entire AI team which will slowly reshape how all the business units work. This team will be in charge of making sure different AI projects are started within the company, these projects are managed carefully, and the results are tracked diligently so that any mistake is corrected on time.

Build AI solutions using third-party providers

Many companies may find this solution quite compelling since it eliminates the burden of forming an entirely new AI team. The organization solely relies on a third-party service to handle the overhead of building and training machine learning models. Amazon offers such provider under the name of Amazon SageMaker. Microsoft has a plethora of services under its Azure Services umbrella.

Final thoughts

The main objective of this article is to inform executive members in small and large companies about the first steps they can take to transform their organization with artificial intelligence. I have compiled the content from authorized sources like McKinsey&Company as well as my own personal opinion on the topic.

I hope you have found the above lines useful. Please leave any suggestions, comments, and ideas below. Thank you for reading!