There are several questions that must be answered before embarking on an AI journey, writes Johan Steyn, Portfolio Lead at IQbusiness, and Chair: Special Interest Group – AI and Robotics at IITPSA.

At a conference where I was speaking recently, a delegate asked me. “All this Artificial Intelligence (AI) stuff you are talking about sounds very exciting,” he said. “But I don’t even know where to begin?” This is a common question that many business owners and senior executives are asking at the moment, given the current hype around the fourth industrial revolution.

Most of us work in ‘traditional’ businesses – organisations that have been around for many years, with technical debt and legacy systems, and workforces that may not be ready or even suited for the introduction of new, disruptive technologies.

The reality is that, while many of us wish we worked for an AI-first organisation like Uber or one of the trailblazers like Google and Facebook, we don’t. That’s why we first need to lay the right foundation before we introduce AI and Machine Learning (ML) into our businesses.

Here are important questions to ask and considerations to make before you embark on your business AI adventure.

What problems/challenges do you need to address?

AI or ML is not necessarily the answer to your business concerns and assuming that this kind of technology will magically solve all our problems is dangerous. The best place to start is to look at a problem statement and a business objective – dig deep and ask yourself if your current processes align with your overarching business strategy. Then, question whether these problems can be solved with AI or merely require a simpler, process-centred initiative.

What are your reasons for wanting to implement AI?

The classical fear of missing out or needing to jump on the same AI-driven train everyone else is on are not good enough reasons to embark on a business transformation. How about that divisional executive who is telling the board they are supposedly implementing AI? I call this the ‘AI tick-box’ exercise – these initiatives will end up costing your business unnecessary time and money, and are often doomed to fail.

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

  • Decreasing your business cost base
  • Lowering your business risk exposure
  • Improving customer experience

What is your AI maturity?

Also referred to as an AI Readiness Assessment or AI Maturity Matrix, this is the step where you map out your business’s main process areas, including customer service, finance, operations, human capital management and service management. Then, as part of the assessment, rate the maturity per process in order, – from manual processing, isolated automation with individual tools, tactical automation utilising a variety of tools to end-to-end strategic automation.

This task will offer a high-level view of the business areas ready for an AI initiative, i.e. the area that directly impacts the way you service your customers.

Avoiding pitfalls

Once you have aligned with your business strategy, determined your AI ambitions and assessed your business readiness for AI, you should keep the following in mind:

  • Change management – it’s natural for your employees to feel insecure about their future when you start talking about the introduction of new technologies. Take them by the hand on a journey of discovery by rather speaking about co-botics the fact that this technology should enhance our jobs, rather than replace us.
  • Regulatory requirements and labour relations – if you work in a highly-regulated industry like banking or financial services, you may be constrained to all the potential benefits that AI may bring to your business. You may also have an unionised workforce, in which case you will have to plan for the strategy and message your staff and unions.
  • Workforce upskilling – intelligent augmentation is key here. You need a well-formulated plan regarding the impact AI will have on your current ways of working, how AI will change the way work will happen in the future, and the skills needed. Consider the new roles that will need to be introduced, such as 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.
  • Data – it starts and ends with data. Data is the lifeblood that AI and ML live on. Are you harvesting enough and suitable data from your clients (granted you have their permission to do so) and from your internal business operations? Behind every AI strategy is a data strategy.

With these stable foundations in place, your business is now ready to launch its first AI initiative. Consider whether you want to create the AI build internally or buy it as a solution from an external vendor.

Next, aim for the initial 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.

Ultimately, every business is being driven by software. Through this software, we can manage our processes, build our offerings and service our customers, and as such, AI and ML are imperative for every modern organisation. By following the right steps, building solid ground, and taking your employees along with you, your AI journey is sure to be a success.

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