30 August 2019

By Johan Steyn, Senior Manager – Technology at IQbusiness 

 

With all the hype around the Fourth Industrial Revolution, many organisations are scrambling to implement AI and Machine Learning in their operations and client offerings. Many are failing. Where do you start and what are the steps to ensure a successful implementation?

Recently, at a conference where I was speaking, a delegate came up to me. “All this AI stuff you are talking about sounds very exciting,” he said.  “But where do we even start on the journey in my business?” That is a question that most business owners and senior executives are asking at the moment.

 

Most of us work in a “traditional business.” We have been around for many years, we have lots of technical debt and legacy systems, and our workforce may not all be ready or even suited for the introduction of new disruptive technology.

 

Many of us wish we worked for an “AI-first” business like Uber, or even for one of the “Trailblazers” like Google, Facebook or Alibaba. It would also be amazing to be part of an “AI Startup.” Imagine having AI and Machine Learning underscoring your whole business from day one?

 

So if you ask me, “Should we be on an AI journey in my business?” my answer will be “Absolutely!” But I will also want to add, “Maybe not now.”

 

“So why wait?” you may ask me. And I will advise you to ensure that you first lay the right foundation before you introduce AI and Machine Learning in your organisation.

 

 The important steps on your journey

Here are the important steps to take before you embark on an AI journey in your business:

 

First, and foremost, you have to align with the business strategy. What problems and challenges do you need to address? It is possible that AI or Machine Learning is not the answer to your problem?

 

Let me give you an example: I recently met with a banking client who wanted to introduce AI into their Human Capital Management Division. At the start of our meeting, I told the audience that they might not use words like “Artificial Intelligence,” “Robotics,” “Machine Learning” or any other technology term during the meeting.

 

Then I took a pen and drawing on a whiteboard I asked them to tell me about their business problems. You see, we often start a solution discussion with a possible answer already in mind. We wrongly start by assuming we know what kind of technology will work for us. But the right place to start is to look at the problem statement and the business objective.

 

During the client meeting, we discovered that they do not need Artificial Intelligence. They do not even need Robotic Process Automation. The main problem was that they did not have well-defined and documented processes in their department. So what was the answer to their problem? They needed a process engineering initiative, and they were able to use Microsoft Flow to automate the required tasks.

 

If we start at the problem we need to solve, we may discover that AI is not the answer.

 

Secondly, you need to understand your AI ambitions. What is the reason why you want to embark on this journey? Often, it is the classical “fear of missing out.” “Others are doing it, so we better do it too!” Sometimes a divisional executive will want to tell the Board that he/she is implementing AI. I call this the “AI tick-box” exercise. These initiatives cost money, divert unnecessary time and are often doomed to fail.

 

The following are relevant reasons to introduce any new technological capability to your business:

 

  1. Decreasing your business cost base
  2. Lowering your business risk exposure
  3. Improving customer experience

 

Thirdly, you need to assess your AI maturity. You may also call it an “AI readiness assessment” or an “AI Maturity Matrix.”

 

Map out your organisations’ main process areas. These could include  Customer Service, Finance, Operations, Human Capital Management, or Service Management. Then, as part of the matrix, map the maturity per process area in order, from Manual processing, Isolated automation with individual tools, Tactical automation utilising a variety of tools, and End-to-end strategic automation.

 

This matrix should give you a high-level view of the business area most ready for an AI initiative.

 

At the start of this video, I mentioned the question that was posed to me at the recent conference: “Where do we even start on the journey in my business?” The simple but important answer, in my mind: Start with any area that directly impacts the way you service your customers.

 

 

Avoiding Pitfalls 

I already referred to the importance of aligning with your business strategy, determining your AI ambitions and assessing your business readiness for AI.

 

Apart from this, it is imperative that you also keep the following in mind:

 

  1. Change Management: Many of your staff may feel insecure about their future when you start talking about the introduction of AI and Robotics. You need to take them by the hand on a journey of discovery. Rather speak about co-botics: the fact that this technology should enhance our jobs, rather than replace us.

 

  1. Regulatory Requirements and Labour Relations: If you work in a highly regulated industry, like Banking and Financial Services, you may be constrained to all the potential benefits that AI may bring to your business operation. You may also have an unionised workforce and will have to plan for the strategy and messaging to your staff and unions.

 

  1. Workforce upskilling: Intelligent Augmentation is key to the journey. We need a well-formulated plan regarding the impact of AI on our current way of work, on how AI will change the way we will be working, and the skills needed. New roles need to be introduced if you do not have it already, like Data Scientists and AI Engineers. You may also be working in a market where future skills are limited, in which case you need to consider a hybrid model of upskilling your staff while utilising the expertise of a third-party vendor.

 

  1. Data – its starts and ends with data! The lifeblood that AI and Machine Learning lives on is Data. Are you harvesting enough and suitable data from your clients (if you have their permission and adhere to regulation), and from your internal business operations? Behind every AI strategy is a data strategy.

 

 With all in place, it’s time to launch

Now that the right foundation is in place, you are ready to launch your first AI initiative. On the foundation of your AI strategy, you can now create your first AI build. A key consideration here is whether you should create it internally, or buy it as a solution from a vendor.

 

Next, you aim for your first Proof of Concept and Minimal Viable Product. In the spirit of the Agile process, you need to start small, fail fast and learn quickly. You need to build momentum to ensure your mandate is maintained, your current and future funding are secure and that the organisation sees value early on.

 

Conclusion

Every business is becoming a software business. It is through software that we manage our processes, build our offerings and service our customers. Artificial Intelligence and Machine Learning are imperative for every business. As long as you take the right steps, follow the right plans and take your organisation effectively on the journey with you, you will be successful.